Inside Google Cloud

What’s new with Google Cloud

Fri, 27 Feb 2026 17:00:00 +0000

Want to know the latest from Google Cloud? Find it here in one handy location. Check back regularly for our newest updates, announcements, resources, events, learning opportunities, and more.

Tip: Not sure where to find what you’re looking for on the Google Cloud blog? Start here: Google Cloud blog 101: Full list of topics, links, and resources.

Mar 2 - Mar 6

Introducing Gemini 3.1 Flash-Lite, our fastest and most cost-efficient Gemini 3 series model. Built for high-volume developer workloads at scale, 3.1 Flash-Lite delivers high quality for its price and model tier. Gemini 3.1 Flash-Lite can tackle tasks at scale, like high-volume translation and content moderation, where cost is a priority. And it can also handle more complex workloads where more in-depth reasoning is needed, like generating user interfaces and dashboards, creating simulations or following instructions.

Starting today, 3.1 Flash-Lite is rolling out in preview to enterprises via Vertex AI and developers via the Gemini API in Google AI Studio.

Feb 23 - Feb 27

Pro-level image generation gets faster and more accessible with Nano Banana 2. Nano Banana 2 is our state-of-the-art image generation and editing model. It delivers Pro-level image generation and editing at the speed you expect from Flash — making the quality, reasoning, and world knowledge you loved about Nano Banana Pro more accessible. Learn more about the model here.

The Intelligent Path to Compliance: Transforming Regulatory QC with Google Cloud
Reducing "Refuse to File" (RTF) risks and submission cycle times is critical for life sciences leaders. Google Cloud’s Regulatory Submission Semantic QC Auditor leverages Gemini and RAG architecture to transform Quality Control from a manual burden into an active, intelligent workflow.

By automating semantic cross-referencing, narrative coherence checks, and dynamic guidance-based auditing, this solution ensures rigorous accuracy and auditability. Operating within a secure GxP-ready environment, it empowers teams to detect subtle inconsistencies and generate remediation plans without sacrificing data privacy.

Learn more.
Stop typing, start interacting! The Gemini Live Agent Challenge is here. Build immersive agents that can help you see, hear, and speak using Gemini and Google Cloud. Compete for your share of $80,000+ in prizes and a trip to Google Cloud Next '26!

Submissions are open from February 16, 2026 to March 16, 2026. Learn more and register at geminiliveagentchallenge.devpost.com

Feb 9 - Feb 13

Introducing Gemini 3.1 Pro on Google Cloud.
3.1 Pro is a noticeably smarter, more capable baseline for complex problem-solving. We’re shipping 3.1 Pro at scale, building upon our goal to help you transform your business for the agentic future. Learn more about the model’s capabilities here. Gemini 3.1 Pro is available starting today in preview in Vertex AI and Gemini Enterprise. Developers can access the model in preview via the Gemini API in Google AI Studio, Android Studio, Google Antigravity, and Gemini CLI.

Automate Storage Compatibility with GKE Dynamic Default Storage Classes
Managing storage across mixed-generation VM clusters in GKE just got easier. With the new Dynamic Default Storage Class, Google Kubernetes Engine automatically selects between Persistent Disk (PD) and Hyperdisk based on a node's specific hardware compatibility. This abstraction eliminates the need for complex scheduling rules and manual pairing, ensuring your volumes "just work" regardless of the underlying infrastructure. By defining both variants in a single class, you reduce operational overhead while maintaining peak performance and cost-efficiency across your entire cluster.

Explore automated disk type selection
Community TechTalk: AI-Powered Apigee Development with strofa.io
Join the Apigee community on February 26 for a deep dive into strofa.io. Guest speaker Denis Kalitviansky will demonstrate how this new AI-powered tool automates and orchestrates Apigee development, from local emulators to large-scale hybrid environments. Discover how to scale your API management and streamline team collaboration using the latest in AI-driven automation.

Register now to reserve your spot.

Jan 26 - Jan 30

Simplify API Governance with Native OpenAPI v3 Support
Eliminate integration debt and accelerate deployment velocity with the General Availability of OpenAPI v3 (OASv3) support for API Gateway and Cloud Endpoints. You no longer need to downgrade modern specifications to OASv2. Instead, you can now define API contracts and enforce critical policies—including telemetry, quotas, and security—using native Google-specific extensions directly within your OASv3 files. This update ensures your APIs are secure by design while remaining fully compatible with the modern developer ecosystem and Google Cloud’s AI services.

Get started with OpenAPI v3 on API Gateway and Cloud Endpoints.

Accelerate API Testing with the New Open Source API Tester
Start validating your APIs with API Tester, a simple, YAML-based Test Driven Development (TDD) framework. Designed for the Apigee community, this tool allows you to write human-readable tests, run them instantly via a web client or CLI, and perform deep unit testing on Apigee proxies. With native support for JSONPath assertions and Apigee shared flows, you can verify everything from payload data to internal variables like proxy.basepath without leaving your terminal.

Explore the API Tester guide and start testing your proxies today.
Secure Sensitive Data with Kubernetes Secrets in Apigee hybrid
Enhance security in Apigee hybrid by accessing Kubernetes Secrets directly within your API proxies. This hybrid-exclusive feature keeps sensitive credentials within your cluster boundary and prevents replication to the management plane. It supports strict separation of duties: operators manage secrets via kubectl, while developers reference them as secure flow variables—ideal for high-compliance and GitOps workflows.

Implement Kubernetes Secrets in your hybrid proxies.
See the Console in a Whole New Light: Dark Mode is Now Generally Available in Google Cloud
Elevate your cloud management workflow with Dark Mode, now generally available in the Google Cloud console. We have delivered a modern, cohesive, and accessible experience reimagined for maximum comfort and productivity—especially during extended working hours and low-light environments. Dark Mode can be enabled automatically based on your operating system's preference, or manually through the Settings -> Appearance menu.

Switch to Dark Mode today to enjoy a modern, comfortable, and productive environment!
Apigee X Networking: PSC or VPC Peering?
Deciding how to connect Apigee X? Watch this video to compare Private Service Connect and VPC Peering. We break down northbound and southbound routing, IP consumption, and how to reach targets on-prem or in the cloud. Learn to simplify your architecture and avoid common networking "gotchas" for a smoother deployment.

Watch the video.

Jan 19 - Jan 23

Bridge the Gap: Excel-to-API Conversion in Apigee Portals
Give your customers more ways to connect! This new article by Tyler Ayers explores how to extend the Apigee Integrated Portal to support direct Excel file uploads. By leveraging SheetJS and custom portal scripts, you can enable users to upload spreadsheets, preview data, and submit it directly to your APIs, all without writing a single line of integration code themselves. It’s a powerful way to simplify onboarding for those who aren't yet API-ready.

Learn how to build it.
Elevate your applications with Firestore’s new advanced query engine
We have fundamentally reimagined Firestore with pipeline operations for Enterprise edition. Experience a powerful new engine featuring over a hundred new query features, index-less queries, new index types, and observability tooling to improve query performance. Seamlessly migrate using built-in tools and leverage Firestore’s existing differentiated serverless foundation, virtually unlimited scale, and industry-leading SLA. Join a community of 600K developers to craft expressive applications that maximize the benefits of rich queryability, real-time listen queries, robust offline caching, and cutting-edge AI-assistive coding integrations.

Learn more about Firestore pipeline operations.

What’s new with Google Cloud - 2025

Fri, 26 Dec 2025 17:00:00 +0000

Want to know the latest from Google Cloud? Find it here in one handy location. Check back regularly for our newest updates, announcements, resources, events, learning opportunities, and more.

Tip: Not sure where to find what you’re looking for on the Google Cloud blog? Start here: Google Cloud blog 101: Full list of topics, links, and resources.

Dec 22 - Dec 26

To design production-ready AI agents, you must choose the right tools for memory, reasoning, and orchestration. To simplify this process, Choose your agentic AI architecture components provides an iterative framework to help you select products and tools that best match your workload characteristics. To build and deploy secure and reliable single-agent AI systems on a scalable serverless platform, see our Single-agent AI system using ADK and Cloud Run architecture guide.

Dec 15 - Dec 19

Announcing Advanced Governance Capabilities to Vertex AI Agent Builder: Today, with the integration of the Cloud API Registry, we’re excited to bring enhanced tool governance capabilities to Vertex AI Agent Builder. With this latest update, administrators can now manage available tools for developers across your organization directly in Vertex AI Agent Builder Console, and developers can leverage tools managed by the registry with a new ApiRegistry.

Following last month's expansion of our Agent Builder platform, we are also introducing new capabilities across the entire agent lifecycle to help developers build faster using new ADK capabilities and visual tools, and scale with high performance through the expansion of Agent Engine services, including the general availability of support for sessions and memory. Read more below.

Vertex AI Agent Builder provides the unified platform to manage the entire agent lifecycle, helping you close the gap from prototype to a production-ready agent. To explore these new features, visit the updated Agent Builder documentation and release notes.
Single-tenant Cloud HSM is now Generally Available: We’re thrilled to announce the General Availability (GA) of Single-tenant Cloud HSM - a standards compliant, highly available, and scalable HSM cluster that provides you complete control over your cryptographic keys for highly sensitive workloads in the cloud for general purpose applications.

Customers have complete control over their cryptographic keys and the ability to manage their own admin credentials through our gcloud APIs, which establish a cryptographically isolated cluster of dedicated HSM partitions for each customer.

Single-tenant Cloud HSM is integrated with Cloud KMS, allowing its use with Customer-Managed Encryption Keys (CMEK). Single-tenant Cloud HSM is available in the following regions: us-central1, us-east4, europe-west1, and europe-west4.
Advanced AI, data, and compliance security capabilities are now available to Security Command Center (SCC) Premium pay-as-you-go (PayGo) customers. Previously exclusive to Enterprise and Premium subscriptions, we now offer to PayGo customers the AI Security Dashboard, Data Security Posture Management (DSPM), Compliance Manager, and Security Graph, including Graph Search and Correlated Threats. This update can help you address novel risks from generative AI and autonomous agents by offering integrated, automated protection for both traditional and AI workloads in Google Cloud. Customers can start a 30-day free trial to access the full SCC Premium experience.

Dec 8 - Dec 12

Application Design Center is now Generally Available
We're excited to announce the General Availability (GA) of Application Design Center, enabling platform teams and developers to streamline cloud application infrastructure design, deployment, and evolution, ensuring security and best practices.

This GA launch includes powerful new capabilities such as enterprise-grade governance with public APIs and gcloud CLI support; bring your own Terraform, full compatibility with VPC Service Controls; and simplified onboarding with app-managed project support.

To learn more, read the Application Design Center GA launch blog.
Apigee Feature Templater Simplifies API Proxy Development for Everyone
The new open-source Apigee Feature Templater (AFT) streamlines API proxy authoring by turning complex policies into reusable building blocks called "features." Non-experts can quickly assemble robust proxies—including AI Gateways, security, and data masking—using simple CLI or REST commands. AFT accelerates time-to-market by enabling expert developers to delegate feature creation and empowering a broader team to compose APIs. Read the full release details.
Navigating the Industry Shift in Client Authentication for Apigee mTLS
An industry policy change is phasing out the Client Authentication Extended Key Usage (EKU) in public certificates, directly impacting server-to-server mTLS for Apigee. This shift forces organizations away from Public CAs to manage their own Private PKI to maintain service continuity by mid-2026. This article presents the two paths: implementing a Private Certificate Authority (Private CA), ideally using Google Cloud Certificate Authority Service (CAS) for immediate mTLS continuity; or modernizing long-term with Demonstrating Proof of Possession (DPoP) for maximum operational efficiency. Read about the two paths to mTLS continuity.
Learn how to implement Kubernetes Secrets in Apigee hybrid
Apigee hybrid introduces direct, read-only access to custom Kubernetes Secrets within API proxies. This exclusive feature offers a superior way to handle highly sensitive credentials (like private keys and backend passwords) compared to KVMs. Secrets never leave the cluster boundary, ensuring enhanced compliance and security. It enables a clean separation of duties, allowing cluster operators to manage credentials via GitOps workflows while API developers securely reference them using flow variables, without ever viewing the raw sensitive data. Read the full article.
Don't let your AI program fail at the final hurdle. Our new guide, Successful Chatbot: 5 Steps from ROI to Rollout, outlines the essential practices for rigorous customer testing and strategic deployment. Learn how to align testing with business goals, define clear evaluation criteria, and drive actionable insights. The post emphasizes that delivering a successful AI program requires more than just domain expertise, highlighting the importance of clear scoping, strategic staffing, and disciplined financial planning. This is crucial for maximizing confidence in your AI's long-term impact, especially in regulated industries like healthcare.

Useful Product links - Google Cloud's Vertex AI & Agentspace, Google Cloud's Healthcare API, and, Google Cloud's Natural Language API
Apigee Now Supports Model Context Protocol (MCP) for Secure Agentic Tools
Google has expanded support for Model Context Protocol (MCP) with the release of fully-managed, remote MCP servers, giving developers worldwide consistent and enterprise-ready access to Google and Google Cloud services. This includes support for MCP in Apigee, which makes it possible for agents to use your secure, governed APIs and custom workflows cataloged in Apigee API hub as tools to complete tasks for end users.

With Apigee’s support for MCP, you don’t need to make any changes to your existing APIs, write any code, or deploy and manage any local or remote MCP servers. Apigee uses your existing API specifications and manages the underlying infrastructure and transcoding, so that you can focus on the business logic for your agents. Read the full announcement.
Introducing Fully-Managed MCP Servers to Power Agentic AI
Google Cloud is announcing fully-managed, remote Model Context Protocol (MCP) servers, enhancing Google’s API infrastructure to provide a unified, enterprise-ready layer for AI agents. This eliminates the burden on developers to install and manage individual MCP servers. Now, AI agents can reliably use trusted Google services like Google Maps, BigQuery, Compute Engine, and GKE as tools to perform complex tasks. This unified approach, managed via Cloud IAM and Apigee API Hub, ensures rigorous governance, security, and observability for all agentic interactions. Read the full announcement.
Marketplace Customer Credit Program now available for Marketplace Channel Private Offers
Google Cloud's Marketplace Customer Credit Program offers up to 3% in Google Cloud credits when customers purchase an eligible cloud marketplace solution for the first time, whether directly through an ISV or via a chosen channel partner. Learn more.
Two-step control plane minor upgrades with rollback safety in Public preview
Upgrading a production Kubernetes cluster can be a stressful, high-stakes event. GKE's new two-step control plane minor upgrade with rollback safety gives you a safe window to validate a new minor version before committing, with a simple rollback option if you find any issues. By decoupling control plane binary changes from new API and feature changes, you can easily revert to the previous minor version if issues arise during the validation period. Learn more about this new, safer upgrade process.

Google named a Leader in the 2025 IDC MarketScape for Worldwide Hyperscaler Marketplaces
IDC Marketscape has positioned Google as a Leader in the 2025 IDC MarketScape for Worldwide Hyperscaler Marketplaces. We believe this recognition underscores our commitment to deliver a cloud marketplace experience that fuels the AI agent economy and accelerates innovation. This achievement reflects our dedication to creating an open and interoperable agentic AI ecosystem for our customers and partners. Learn more.

Dec 1 - Dec 5

Unlock the full potential of your data with Object Contexts in Google Cloud Storage
This new feature provides a foundation for semantic storage and actions, allowing you to integrate Gemini with GCS objects and enrich your objects in a more intelligent and meaningful way. Learn how to get started with Object Contexts and revolutionize your data workflows. Learn more.

Nov 24 - Nov 28

Boost API Security: IP Allowlisting and ML Enhancements for Apigee Abuse Detection
To keep your applications safe, it’s critical to detect and block attacks on your APIs as quickly as possible. In the past few months, we’ve made some changes to Advanced API Security’s Abuse Detection feature to make it easier and faster to identify legitimate attacks and take action. Get all the details on Apigee's new IP allowlisting.
Apigee AI Gateway Deep Dive on December 11
Join the final Apigee Community Tech Talk of the year for a deep dive into the Apigee AI Gateway. This session provides practical details on integrating, proxying, and converting complex MCP protocol services with traditional REST backends. Learn specific techniques for securing, monitoring, and gaining technical control over MCP backends to meet enterprise-grade governance requirements. Register now

Nov 10 - Nov 14

Deploy n8n to Cloud Run
With just a few commands, you can deploy n8n to Cloud Run and have it up and running, ready to supercharge your business with AI workflows that can manage spreadsheets, read and draft emails, and more. n8n and Cloud Run are both easy to use and powerful tools that empower developers to do more with AI. Learn more here.
GKE Node Memory Swap in Public preview
You can now configure swap space on your GKE Standard nodes to provide a crucial buffer against Out-of-Memory (OOM) errors for memory-intensive applications, especially during unexpected usage spikes. Enabling swap can improve workload resilience, reduce pod evictions due to memory pressure, and enhance overall application stability and cost-effectiveness. This feature is currently available in a public preview.

Nov 3 - Nov 7

Announcing the Data Engineering Agent
Data teams can now automate complex SQL pipeline tasks with the new Data Engineering Agent for BigQuery, available in Preview. This agent simplifies development, maintenance, and troubleshooting, allowing engineers to focus on strategic initiatives. It supports natural language pipeline creation, intelligent modification, and seamless migration from legacy tools.

Transform your data engineering workflows today!
From Threat Model to TTX: Bringing a New Design Partner to the Table
Gain an overview of threat modeling, how threat models can be performed rapidly, and why threat model scenarios make excellent tabletop scenarios - especially for products that are still in development.

To get more information about threat modeling or tabletop exercises, check out The Defender’s Advantage or reach out to a Mandiant cybersecurity expert for specialized assistance.
Application Monitoring now includes a Topology.
Application Monitoring now includes a graphical representation of runtime dependencies (i.e Topology) for your App Hub defined application. This now allows you to quickly understand your app architecture, spot anomalous runtime interactions and resolve issues flagged from alerts quicker. Runtime dependencies are extracted from the OpenTelemetry traces you send to Cloud Trace from your App Hub registered workload.

Follow the outline here to register your app and unlock the benefits of Application Monitoring and its newly launched Topology
Supercharge AI Agents: Apply Enterprise Governance to GenAI Workflows with Apigee
As Generative AI agents move to production, you need control over cost, reliability, and security. A powerful new pattern introduces Apigee as the unified AI Agent Gateway for Large Language Model (LLM) calls. Route agent traffic through Apigee to gain immediate enterprise-grade governance, including dynamic circuit breaking, token consumption quotas, and sensitive data masking. A new Apigee wrapper for the Agent Development Kit (ADK) simplifies implementation. Turn your agents into manageable, secure AI products.

Read the full article and explore the new pattern.

Oct 20 - Oct 24

Dataframe visualization in Colab Enterprise. Use visualization cells to create custom, stylized visualizations of your DataFrames: no coding required! Choose your fields, chart type, aggregation, and color scheme, then see a visualization of your data without leaving your notebook. Check out the tutorial and get started with data visualization today.

Oct 13 - Oct 17

Build Serverless AI in the Cloud Run Hackathon
Ready to go from idea to global scale in minutes? The Cloud Run Hackathon is here! Build serverless AI apps with AI Studio, orchestrate intelligent agents, or harness the power of GPUs. Compete for a share of $50,000+ in prizes!
- Submissions are open from Oct 6, 2025 to Nov 10, 2025.
- Learn more and register: run.devpost.com

Oct 6 - Oct 10

Multi-agent AI systems help you optimize complex and dynamic processes by segmenting them into discrete tasks that multiple specialized AI agents collaboratively execute. To get started with building secure and reliable multi-agent AI systems, see this reference architecture guide: Design a multi-agent AI system in Google cloud. The example architecture in this guide showcases a couple of agent patterns: sequential, and loop. For a comprehensive review of all the possible agent design patterns and for help with choosing patterns that are appropriate for your use cases, see this design guide: Choose a design pattern for your agentic AI system.

Sept 29 - Oct 3

Announcing Koog Supports for Agent2Agent protocol (A2A)
The future of interconnected AI is here. We're thrilled to announce that Koog now supports A2A, a protocol that lets agents talk directly, securely, and seamlessly across companies and clouds. For Kotlin developers, this unlocks a new era of powerful, enterprise-grade AI. Build sophisticated agents that automatically discover and collaborate with other services, all while calling on Google Cloud's state-of-the-art models like Gemini directly from your workflows. Stop building bridges and start creating truly intelligent, interconnected systems today. Learn more about building with Koog, A2A, and Google Cloud.

Sept 15 - 19

Your AI is Now a Local Expert: Grounding with Google Maps is GA
We are excited to announce the General Availability (GA) of Grounding with Google Maps in Vertex AI. This feature lets developers build generative AI applications that are connected to real-world, up-to-date information from Google Maps, using its data on over 250 million places worldwide.

To learn more and get started, visit our documentation and check out our demo.
Production-ready YOLO model training serving workflow on Vertex AI
This guide walks you through a complete, automated workflow for training a custom YOLO model on Vertex AI. You'll learn how to use a custom training job, package the model in a custom prediction container, and register it in the Vertex AI Model Registry, making it ready for easy deployment. Best of all, this approach is designed to work directly with existing Vertex AI managed datasets for object detection, meaning you can reuse the same data you're already using for AutoML models.

Checkout details on developer forums

Sept 8 - 12

Scaling Inference To Billions of Users And AI Agents: Discover the architecture required to serve AI models at a planetary scale. This article details how Google Cloud’s ecosystem—from the GKE Inference Gateway for smart load balancing to the power of custom TPUs and open-source engines like vLLM—provides a production-ready path. Move beyond the hype and learn how to build for the next wave of AI. Explore the technical deep-dive.
We're celebrating the one-year anniversary of bringing Confidential Computing with Intel TDX to Google Cloud. We've been shipping new capabilities to help you protect your most sensitive data while it's in use. Now Generally Available:
- Confidential GKE Nodes with Intel TDX: Secure entire Kubernetes clusters, node pools, and workloads.
- Confidential Space with Intel TDX: Build secure data clean rooms for collaboration on sensitive information.
- Confidential GPUs: Protect cutting-edge AI workloads with Confidential NVIDIA H100s GPUs on GCE and GKE.
  
  We've also expanded Intel TDX to more regions! Read the blog

Aug 25 - 29

Applied AI for Modern Manufacturers: New original growth series, hosted by Jake Hall, The Manufacturing Millennial, that dives into leading trends, best practices, and what companies are doing right now with AI in manufacturing. Hear from industry thought leaders - Rick Bullotta, Jonathan Wise, Walker Reynolds and Berardino Baratta - and Google Cloud experts - Praveen Rao, Eric Lam, Dave Nguyen Ph.D., Geoffrey Hirschheim, and Jim Anderson. Watch Modules 1 and 2 now, where we delve into the AI Innovation and trends and AI Costs and ROI in the Era of Digital Manufacturing. Next module kicks off Tuesday, Sep 2. Join now
Firestore with MongoDB compatibility is now generally available (GA): Developers can now build cost-effective, scalable, and highly reliable apps on Firestore's serverless database using a familiar MongoDB-compatible API. With the general availability of Firestore with MongoDB compatibility, the 600,000 active developers within the Firestore community can now use existing MongoDB application code, drivers, and tools, as well as the open-source MongoDB ecosystem, with Firestore's serverless service. Firestore offers benefits like multi-region replication, virtually unlimited scalability, up to 99.999% SLA, single-digit millisecond read performance, integrated Google Cloud governance, and pay-as-you-go pricing. Register now for the webinar on September 9th for a deep dive into Firestore with MongoDB compatibility.

Aug 18 - 22

Earth Engine in BigQuery is now Generally Available, bringing advanced geospatial analytics directly to your BigQuery workflows. Unlock insights with satellite data!

Aug 11 - Aug 15

New HPC VM and Slurm-gcp Images: A new HPC VM Image (under the project cloud-hpc-image-public) is now available, featuring a Rocky Linux 8-based image, IntelMPI v2021.16, and RDMA drivers. In partnership with SchedMD, new Slurm images (Slurm 25.05) have also been released. These are based on the latest HPC VM Image and are available for Ubuntu 22.04/24.04 Accelerator Images (ARM/AMD64) and Debian 12. These releases allow for the deployment of Slurm-ready clusters on GCP, providing the advantages of an HPC-optimized and performance-tested foundation. Read more.
Scaling our Gemini Embedding model in Vertex AI. Following increased popularity from its General Availability launch in May, we've recently increased quota and input size limits for customers of Vertex AI's most powerful text embedding model, gemini-embedding-001.
- Customers can now send up to 250 input texts per request (generating 250 embeddings) instead of only a single piece of text, bringing improved throughput and decreased round-trip network latency to large-scale embedding applications.
- We've increased quota limits for this model by 10x for most users, allowing hassle-free scaling of embedding applications to millions of tokens per minute and beyond.
  
  Get started with Gemini Embeddings today!

Aug 4 - Aug 8

GKE Node Memory Swap in private preview: You can now configure swap space on your GKE Standard nodes to provide a crucial buffer against Out-of-Memory (OOM) errors for memory-intensive applications, especially during unexpected usage spikes. Enabling swap can improve workload resilience, reduce pod evictions due to memory pressure, and enhance overall application stability and cost-effectiveness. This feature is currently available in a private preview.
- Contact your Google Cloud account team for more information and to request access.
- If you'd like to see more configurations, please contact your account team or make a feature request on our issue tracker!
Unlock Peak Performance: GKE Topology Manager is Now Generally Available: For customers running performance-sensitive workloads like AI/ML and HPC, GKE Topology Manager is now GA and ready to optimize your performance through NUMA alignment. By ensuring CPU, memory, and GPU resources are allocated on the same NUMA node, the Topology Manager minimizes cross-socket latency and maximizes throughput for your most demanding applications. Configure your alignment policies via the NodeConfig API to achieve significant performance gains.
- Achieve these performance gains by configuring your alignment policies via the NodeConfig API.
- If you'd like to see more expansion of Topology manager, please contact your account team or make a feature request on our issue tracker!
Fine-Tune at Scale: A Massive GKE NodeConfig Expansion for All Workloads: GKE has massively expanded node customization capabilities, adding nearly 130 new Sysctl and Kubelet configurations. This gives you finer-grained control for any workload needing node customization, performance requirements, or application-specific tuning. By replacing complex DaemonSets with native controls, you can benefit from enhanced security, high flexibility, faster node startup times, and less operational management.
- Check out our public documentation to learn how to consume these new NodeConfig options.
- If you'd like to see more configurations, please contact your account team or make a feature request on our issue tracker!
New capability for managing licenses in Compute Engine: We are announcing a new capability in Compute Engine which allows users to easily change the OS licenses on their VMs. Users can now append, remove, or replace OS licenses, enabling seamless transitions between license types—such as converting Red Hat Enterprise Linux from pay-as-you-go (PAYG) to bring-your-own subscription (BYOS), or upgrading from Ubuntu to Ubuntu Pro—without needing to redeploy instances. This feature empowers customers to meet their evolving licensing with speed and flexibility. To learn more, read about managing licenses on Compute Engine.
GKE Turns 10 Hackathon: Calling all developers! Google Kubernetes Engine (GKE) is turning 10, and we're celebrating with a hackathon! Join us to build powerful AI agents that interact with microservice applications using Google Kubernetes Engine and Google AI models. Compete for over $50,000 in prizes and demonstrate the power of building agentic AI on GKE.
- Submissions are open from Aug 18, 2025 to Sept, 22 2025
- Learn more and register: gketurns10.devpost.com

Jul 28 - Aug 1

Now GA: C4 VMs with Local SSD, bare metal, and larger shapes, on Intel Xeon 6: C4's expanded shapes are now GA! This expansion introduces C4 shapes with Google’s next-gen Titanium Local SSD, C4 bare metal instances, and new extra-large shapes, all powered by the latest Intel Xeon 6 processors, Granite Rapids. We’re excited to be the first leading hyperscaler to bring Xeon 6 to customers, delivering performance gains of up to 30% for general compute and up to 60% for ML recommendation workloads, and up to 35% lower access latency on Titanium Local SSD shapes. Learn more here!

Jul 14 - 18

DMS SQL Server to PostgreSQL migrations are now generally available! Accelerate your SQL Server modernization to Cloud SQL for PostgreSQL or AlloyDB for PostgreSQL with:
- Automatic database schema and code conversion
- Gemini augmented code conversion
- Gemini assisted PostgreSQL training and code improvements
- Low-downtime, CDC based data movement

Learn more and start your migration journey today!

Jul 7 - 11

Level up your AI Agent game with "The Agent Factory," a new video podcast for developers! We're going beyond the buzz to explore practical design, build, deploy, & management strategies for production-ready AI agents using Google Cloud. Expect code snippets, architecture deep dives, and integrations with open-source frameworks. Subscribe now!

Jun 23 - 27

Announcing partnership between Maxim AI and Google Cloud's Vertex AI to evaluate agentic applications — Maxim AI offers a comprehensive platform to help teams build, evaluate, and observe their AI agents with greater speed and confidence, covering the entire AI lifecycle from prompt engineering to production monitoring. This new partnership deeply integrates Vertex AI's Gen AI evaluation service directly within the Maxim AI environment, allowing users to leverage Gemini to power assistant responses and evaluate them using Vertex AI's comprehensive suite of evaluators. This provides access to metrics such as helpfulness, relevance, safety, and trajectory. The setup allows users to simulate, evaluate, and trace complex multi-turn interactions on Maxim, helping teams bring reliable AI products to market faster through a seamless developer experience. To learn more, check out this blog from Maxim AI
Run non-request workloads at scale with Cloud Run Worker Pools, now in Public Preview — Looking for the ease-of-use and scalability of serverless, without being limited to HTTP request-driven workloads? Cloud Run Worker Pools provide the same elasticity and high-quality developer experience as Cloud Run Services, but are designed for non-request workloads. Worker Pools are ideal for pull-based use cases like processing messages from Pub/Sub or Kafka, and other backend processing. Check out the public documentation to learn more about how to choose between Services, Jobs, and Worker Pools. Then give Worker Pools a try by deploying a sample Worker Pool.
Building a Multi-Agent Research Assistant for Financial Analysis with Schroders & Google Cloud — Financial analysts spend hours grappling with ever-increasing volumes of market and company data to extract key signals, combine diverse data sources, and produce company research. To maximise its edge as an active manager, Schroders wants to enable its analysts to shift from data collection to the higher-value strategic thinking that is critical for business scalability and client investment performance. To achieve this, Schroders and Google Cloud collaborated to build a multi-agent research assistant prototype using Vertex AI Agent Builder. Find out more here.

Jun 16 - 20

Simplify Your Multi-Cloud Strategy with Cloud Location Finder, now in Public Preview: As cloud environments expand beyond traditional architectures to include multiple clouds, managing your infrastructure effectively becomes more complex. Imagine effortlessly accessing consistent and up-to-date location information across different cloud providers, so your multi-cloud applications are designed and optimized with performance, security, and regulatory compliance in mind. Today, we are making this a reality with Cloud Location Finder, a new Google Cloud service which provides up-to-date location data across Google Cloud, Amazon Web Services (AWS), Azure, and Oracle Cloud Infrastructure (OCI). Now, you can strategically deploy workloads across different cloud providers with confidence and control. Cloud Location Finder is accessible via REST APIs and gcloud CLI, explore the Cloud Location Finder documentation and blog to learn more.
SOTA Gemini Text Embedding is Now Generally Available in Vertex AI: We recently launched a new Gemini Embedding text model (gemini-embedding-001) through the Vertex AI GenAI API. This groundbreaking model, leveraging Gemini's core language understanding, sets a new benchmark for text embeddings. It's the first unified model to excel across English, multilingual text, and code, outperforming previous models (text-embedding-005, text-multilingual-embedding-002) and achieving top ranking on the MTEB Multilingual leaderboard (100+ tasks). Our internal benchmarks demonstrate substantial performance improvements across various industry verticals, including retail, news, finance, healthcare, legal, and code. Detailed results are available in our technical report.
Backup vaults now support disk backups and multi-regions: We’ve added exciting new features to Google Cloud Backup and Disaster Recovery service! You can now secure your Persistent Disk and Hyperdisk backups in backup vaults, protecting them from cyber attacks and accidental data loss. In addition, backup vaults can now be created in multi-region storage locations, maximizing your data resilience and supporting compliance with business continuity requirements. Check out the blog to learn more!
DeepSeek R1, a powerful 671B parameters model, is now available as a fully managed API on Vertex AI in Preview, making advanced AI capabilities more accessible to developers. This Model as a Service (MaaS) offering eliminates the need for extensive GPU resources and infrastructure management, allowing developers to focus on building applications. DeepSeek R1 on Vertex AI provides a simple, scalable API with features like transparent "chain-of-thought" reasoning and enterprise-ready security. It's currently available at no additional cost during the preview, and can be accessed via UI, REST API, or the OpenAI Python API Client Library. Learn more.

Jun 9 - 13

Serverless Spark Now GA in BigQuery: Unified Analytics, Accelerated: Google Cloud Serverless for Apache Spark is now generally available in BigQuery, offering a unified developer experience in BigQuery Studio. Run Spark and SQL side-by-side on the same data, powered by the Lightning Engine for up to 3.6x faster performance and enhanced with Gemini productivity. Simplify your data pipelines and accelerate insights with this deeply integrated, zero-ops solution.
Cloud Pub/Sub introduced Pub/Sub Single Message Transforms (SMTs) to make it easy to perform simple data transformations right within Pub/Sub: An overarching goal of Pub/Sub is to simplify streaming architectures. We already greatly simplified data movement with Import Topics and Export Subscriptions, which removed the need to use additional services for ingesting raw streaming data through Pub/Sub into destinations like BigQuery. Pub/Sub Single Message Transforms (SMTs), designed to be a suite of features making it easy to validate, filter, enrich, and alter individual messages as they move in real time. The first SMT is available now: JavaScript User-Defined Functions (UDFs), which allows you to perform simple, lightweight modifications to message attributes and/or the data directly within Pub/Sub via snippets of JavaScript code. JavaScript UDFs as the first Single Message Transform is generally available starting today for all users. You'll find the new "Add Transform" option in the Google Cloud console when you create a topic or subscription in your Google Cloud project. You can also use gcloud CLI to start using JavaScript Single Message Transforms today.
This analysis evaluates the efficiency of fine-tuning a Llama 3-8B model on Vertex AI using both a single A100 GPU and a distributed four-A100 setup with Axolotl. While both methods achieved similar model convergence, the results underscore the power of distributed training. The process, which took 1 day and 20 hours on a single device, was completed in just 11 hours in the distributed environment—a dramatic acceleration. This speed was achieved with consistently high GPU utilization (94%), though at the cost of higher system and GPU memory overhead. For a detailed breakdown of the methodology, resource utilization metrics, and performance curves, you can review the complete work here.

May 26 - 30

Cloud Run GPUs are now GA: NVIDIA GPU support for Cloud Run is now generally available, offering a powerful runtime for a variety of use cases that’s also remarkably cost-efficient. Developers can now get on-demand access to GPUs with our serverless runtime, Cloud Run. Follow the footsteps of customers like MidJourney, vivo, and Wayfair. Read blog.
Datastream now supports MongoDB as a source! Seamlessly ingest data from MongoDB (Replica Sets, Sharded Clusters, self-hosted, AtlasDB) into BigQuery/Cloud Storage. Enjoy scalable, fully-managed data streaming with backfill and CDC, enabling real-time insights and data-driven decisions. Link

May 19 - May 23

Beyond cuts and fades: Understanding narrative flow with Gemini for accurate scene transition detection — Google Cloud's Gemini models are revolutionizing video understanding by accurately detecting narrative scene transitions, moving beyond simple cuts and fades. This breakthrough technology understands the holistic context of videos by analyzing visual, audio, and textual elements simultaneously. Media companies can now convert passive video assets into structured data, enabling intelligent content discovery, strategic ad placement, and personalized viewing experiences. The result? Up to 38% increased viewer engagement and 27% reduced abandonment rates.
- Read more on the medium blog.
- Learn more and access the code repository: View Code Repo
Announced at I/O: Deploy AI apps to Cloud Run from AI Studio and MCP — We are making AI deployments easier and more accessible by introducing new ways to deploy your apps to Cloud Run.
- You can deploy applications developed in AI Studio with a click of a button to Cloud Run, including Gemma 3.
- Model Context Protocol(MCP) is becoming a popular open protocol standardizing how AI agents interact with other tools. Now with Cloud Run MCP server, you can deploy apps from compatible AI agents like from Claude or VS Code Copilot.
- Read blog to learn more.

May 12 - May 16

Google for Startups Accelerator: AI For Energy now accepting applications!
Applications are now open for startups headquartered in Europe and Israel, working on solutions for utilities, grid operators and energy developers; solutions for residential and commercial end-use customers focused on demand flexibility and solutions for industrial customers. This equity-free program offers 10 weeks of intensive mentorship and technical project support to startups integrating AI into their core energy services or products. Selected startups will collaborate with a cohort of peer founders and engage with leaders across Google and the energy sector. The curriculum will provide founders with access to AI tools and include workshops on tech and infrastructure, UX and product, growth, sales, leadership and more. Learn more and apply before June 30th, 2025.
Extending Google Cloud Workstations containers to run any GUI based programAre you having difficulty customizing Google Cloud Workstations to run a GUI program outside of the supported configurations of IDE’s? If so, you’re not alone. In this article we discuss how to use the base Workstations Docker image and build it to run a terminal and Google Chrome.
Google Cloud Marketplace simplifies deals and improves economics. Announcing three initiatives that build upon Google Cloud Marketplace as a growth engine for customers and partners:

1. Improving partner deal economics to help partners retain more earnings by moving to a variable revenue share model
2. Simplifying commit drawdown for purchases through channel partners
3. Unlocking new workloads with the Marketplace Customer Credit Program incentive
  
  Learn more

2025 Google Cloud DORA Awards are now open for submission!Has your team achieved remarkable success through DORA principles? It's time to shine. We're thrilled to announce the launch of the 2025 Google Cloud DORA Awards, celebrating outstanding achievements in technology delivery and operational performance. Submit your story today!

May 5 - May 9

AI assisted development with MCP Toolbox for Databases
We are excited to announce new updates to MCP Toolbox for Databases. Developers can now use Toolbox from their preferred IDE, such as Cursor, Windsurf, Claude Desktop, more and leverage our new pre-built tools such as execute_sql and list_tables for AI-assisted development with Cloud SQL for PostgreSQL, AlloyDB and self-managed PostgreSQL.
- Get Started with MCP Toolbox for Databases

Apr 28 - May 2

Itching to build AI agents? Join the Agent Development Kit Hackathon with Google Cloud! Use ADK to build multi-agent systems to solve challenges around complex processes, customer engagement, content creation, and more. Compete for over $50,000 in prizes and demonstrate the power of multi-agent systems with ADK and Google Cloud.
- Submissions are open from May 12, 2025 to June 23, 2025.
- Learn more and register here.

Apr 21 - Apr 25

Iceland’s Magic: Reliving Solo Adventure through Gemini
Embark on a journey through Iceland's stunning landscapes, as experienced on Gauti's Icelandic solo trip. From majestic waterfalls to the enchanting Northern Lights, Gautami then takes these cherished memories a step further, using Google's multi-modal AI, specifically Veo2, to bring static photos to life. Discover how technology can enhance and dynamically relive travel experiences, turning precious moments into immersive short videos. This innovative approach showcases the power of AI in preserving and enriching our memories from Gauti's unforgettable Icelandic travels. Read more.
Introducing ETLC - A Context-First Approach to Data Processing in the Generative AI Era: As organizations adopt generative AI, data pipelines often lack the dynamic context needed. This paper introduces ETLC (Extract, Transform, Load, Contextualize), adding semantic, relational, operational, environmental, and behavioral context. ETLC enables Dynamic Context Engines for context-aware RAG, AI co-pilots, and agentic systems. It works with standards like the Model Context Protocol (MCP) for effective context delivery, ensuring business-specific AI outputs. Read the full paper.

Apr 14 - Apr 18

What’s new in Database Center
With general availability, Database Center now provides enhanced performance and health monitoring for all Google Cloud databases, including Cloud SQL, AlloyDB, Spanner, Bigtable, Memorystore, and Firestore. It delivers richer metrics and actionable recommendations, helps you to optimize database performance and reliability, and customize your experience. Database Center also leverages Gemini to deliver assistive performance troubleshooting experience. Finally, you can track the weekly progress of your database inventory and health issues.

Get started with Database Center today
- Access Database Center in Google Cloud console
- Review the documentation to learn more

Apr 7 - Apr 11

This week, at Google Cloud Next, we announced an expansion of Bigtable's SQL capabilities and introduced continuous materialized views. Bigtable SQL and continuous materialized views empower users to build fully-managed, real-time application backends using familiar SQL syntax, including specialized features that preserve Bigtable's flexible schema — a vital aspect of real-time applications. Read more in this blog.
DORA Report Goes Global: Now Available in 9 Languages!
Unlock the power of DevOps insights with the DORA report, now available in 9 languages, including Chinese, French, Japanese, Korean, Portuguese, and Spanish. Global teams can now optimize their practices, benchmark performance, and gain localized insights to accelerate software delivery. The report highlights the significant impact of AI on software development, explores platform engineering’s promises and challenges, and emphasizes user-centricity and stable priorities for organizational success. Download the DORA Report Now
New Google Cloud State of AI Infrastructure Report Released
Is your infrastructure ready for AI? The 2025 State of AI Infrastructure Report is here, packed with insights from 500+ global tech leaders. Discover the strategies and challenges shaping the future of AI and learn how to build a robust, secure, and cost-effective AI-ready cloud. Download the report and enhance your AI investments today. Download the 2025 AI infrastructure report now
Google Cloud and Oracle Accelerate Enterprise Modernization with New Regions, Expanded Capabilities
Announcing major Oracle Database@Google Cloud enhancements! We're launching the flexible Oracle Base Database Service and powerful new Exadata X11M machines. We're rapidly expanding to 20 global locations, adding new Partner Cross-Cloud Interconnect options, and introducing Cross-Region Disaster Recovery for Autonomous Database. Benefit from enhanced Google Cloud Monitoring, integrated Backup & DR, plus expanded support for enterprise applications like SAP. Customers can run critical Oracle workloads with more power, resilience, and seamless Google Cloud integration. Get started right away from your Google Cloud Console or learn more here.

Mar 17 - Mar 21

Cloud CISO Perspectives: 5 tips for secure AI success - To coincide with new AI Protection capabilities in Security Command Center, we’re offering 5 tips to set up your organization for secure AI success.
Our 4-6-3 rule for strengthening security ties to business: The desire to quickly transform a business can push leaders to neglect security and resilience, but prioritizing security can unlock value. Follow these 4 principles, 6 steps, and 3 metrics to use a security-first mindset to drive business results.
The new Data Protection Tab in Compute Engine ensures your resources are protected: Not only have we co-located your backup options, but we also have introduced smart default data protection for any Compute Engine instance created via Cloud Console. Here’s how it works.
DORA report - Impact of Generative AI in Software Development
This report builds on and extends DORA's research into AI. We review the current landscape of AI adoption, look into its impact on developers and organizations, and outline a framework and practical guidance for successful integration, measurement, and continuous improvement. Download the report!

Mar 10 - Mar 14

Protecting your APIs from OWASP’s top 10 security threats: We compare OWASP’s top 10 API security threats list to the security capabilities of Apigee. Here’s how we hold up.
Project Shield makes it easier to sign up, set up, automate DDoS protection: It’s now easier than ever for vulnerable organizations to apply to Project Shield, set up protection, and automate their defenses. Here’s how.
How Google Does It: Red teaming at Google scale - The best red teams are creative sparring partners for defenders, probing for weaknesses. Here’s how we do red teaming at Google scale.
AI Hypercomputer is a fully integrated supercomputing architecture for AI workloads – and it’s easier to use than you think. Check out this blog, where we break down four common use cases, including reference architectures and tutorials, representing just a few of the many ways you can use AI Hypercomputer today.
Transform Business Operations with Gemini-Powered SMS-iT CRM on Google Cloud: SMS-iT CRM on Google Cloud unifies SMS, MMS, email, voice, and 22+ social channels into one Smart Inbox. Enjoy real-time voice interactions, AI chatbots, immersive video conferencing, AI tutors, AI operator, and unlimited AI agents for lead management. Benefit from revenue-driven automation, intelligent appointment scheduling with secure payments, dynamic marketing tools, robust analytics, and an integrated ERP suite that streamlines operations from project management to commerce. This comprehensive solution is designed to eliminate inefficiencies and drive exponential growth for your business. Experience the Future Today.
Join us for a new webinar, Smarter CX, Bigger Impact: Transforming Customer Experiences with Google AI, where we'll explore how Google AI can help you deliver exceptional customer experiences and drive business growth. You'll learn how to:

Transform Customer Experiences: With conversational AI agents that provide personalized customer engagements.
Improve Employee Productivity & Experience: With AI that monitors customers sentiment in real-time, and assists customer service representatives to raise customer satisfaction scores.
Deliver Value Faster: With 30+ data connectors and 70+ action connectors to the most commonly used CRMs and information systems.

Register here

Mar 3 - Mar 7

Hej Sverige! Google Cloud launches new region in Sweden - More than just another region, it represents a significant investment in Sweden's future and Google’s ongoing commitment to empowering businesses and individuals with the power of the cloud. This new region, our 42nd globally and 13th in Europe, opens doors to opportunities for innovation, sustainability, and growth — within Sweden and across the globe. We're excited about the potential it holds for your digital transformations and AI aspirations.
[March 11th webinar] Building infrastructure for the Generative AI era: insights from the 2025 State of AI Infra report: Staying at the forefront of AI requires an infrastructure built for AI. Generative AI is revolutionizing industries, but it demands a new approach to infrastructure. In this webinar, we'll unveil insights from Google Cloud's latest research report and equip tech leaders with a practical roadmap for building and managing gen AI workloads, including: the top gen AI use cases driving the greatest return on investment, current infrastructure approaches and preferences for Generative AI workloads, the impact of performance benchmarks, scalability, and security on cloud provider selection. Register today.
Cloud CISO Perspectives: Why PQC is the next Y2K, and what you can do about it: Much like Y2K 25 years ago, post-quantum cryptography may seem like the future’s problem — but it will soon be ours if IT doesn’t move faster, explains Google Cloud’s Christiane Peters. Here's how business leaders can get going on PQC prep.
How Google Does It: Using threat intelligence to uncover and track cybercrime — How does Google use threat intelligence to uncover and track cybercrime? Google Threat Intelligence Group’s Kimberly Goody takes you behind the scenes.
5 key cybersecurity strategies for manufacturing executives — Here are five key governance strategies that can help manufacturing executives build a robust cybersecurity posture and better mitigate the evolving risks they face.
Datastream now offers Salesforce source in Preview. Instantly connect, capture changes, and deliver data to BigQuery, Cloud Storage, etc. Power real-time insights with flexible authentication and robust backfill/CDC. Unlock Salesforce data for Google Cloud analytics, reporting, and generative AI. Read the documentation to learn more.
Find out how much you can save with Spanner - According to a recent Forrester Total Economic Impact™ study, by migrating to Spanner from a traditional database, a $1 billion per year B2C organization could get a 132% return on investment (ROI) with a 9-month payback period, and realize $7.74M in total benefits over the three years. To see how, check out the blog or download the report.
GenAI Observability for Developers series: The Google Cloud DevRel team hosted a four-part webinar series, "Gen AI Observability for Developers," demonstrating observability best practices in four programming languages. Participants learned to instrument a sample application deployed on Cloud Run for auditing Vertex AI usage, writing structured logs, tracking performance metrics, and utilizing OpenTelemetry for tracing. The series covered Go, Java, NodeJS, and Python, using common logging and web frameworks. Missed it? Recordings and hands-on codelabs are available to guide you at:
- Gen AI O11y for Go Developers
- Gen AI O11y for Java Developers
- Gen AI O11y for NodeJS Developers
- Gen AI O11y for Python Developers
  
  Stay tuned for future events at cloudonair.withgoogle.com.

Feb 24 - Feb 28

Rethinking 5G: Ericsson and Google Cloud are collaborating to redefine 5G mobile core networks with a focus on autonomous operations. By leveraging AI and cloud infrastructure, we aim to enhance efficiency, security, and innovation in the telecommunications industry. This partnership addresses the increasing demands of 5G and connected devices, paving the way for a more dynamic and intelligent network future, and setting the stage for next-generation technologies like 6G. Learn more here.
Adopt a principles-centered well-architected framework to design, build, deploy, and manage Google Cloud workloads that are secure, resilient, efficient, cost-efficient, and high-performing. Also get industry and technology-focused well-architected framework guidance, like for AI and ML workloads.

Feb 17 - Feb 21

Easier Default Backup Configuration for Compute Engine Instances - The Create a Compute Instance page in the Google Cloud console now includes enhanced data protection options to streamline backup and replication configurations. By default, an option to back up data is pre-selected, ensuring recoverability in case of unforeseen events. Learn more here.

Feb 10 - Feb 14

[Webinar] Generative AI for Software Delivery: Strategies for IT Leaders: Generative AI is transforming the way organizations build and deploy software. Join Google Cloud experts on February 26th to learn how organizations can leverage AI to streamline their software delivery, including: the role of gen AI in software development, how to use gen AI for migration and modernization, best practices for integrating gen AI into your existing workflows, and real-world applications of gen AI in software modernization and migration through live demos. Register here.

Feb 3 - Feb 7

SQL is great but not perfect. We’d like to invite you to reimagine how you write SQL with Google’s newest invention: pipe syntax (public available to all BigQuery and Cloud Logging users). This new extension to GoogleSQL brings a modern, streamlined approach to data analysis. Now you can write simpler, shorter and more flexible queries for faster insights. Check out this video to learn more.

Jan 13 - Jan 17

C4A virtual machines with Titanium SSD—the first Axion-based, general-purpose instance with Titanium SSD, are now generally available. C4A virtual machines with Titanium SSDs are custom designed by Google for cloud workloads that require real-time data processing, with low-latency and high-throughput storage performance. Titanium SSDs enhance storage security and performance while offloading local storage processing to free up CPU resources. Learn more here.

Jan 6 - Jan 10

A look back on a year of Earth Engine advancements: 2024 was a landmark year for Google Earth Engine, marked by significant advancements in platform management, cloud integration, and core functionality and increased interoperability between Google Cloud tools and services. Here’s a round up of 2024’s top Earth Engine launches.
Get early access to our new Solar API data and features: We're excited to announce that we are working on 2 significant expansions to the Solar API from Google Maps Platform and are looking for trusted testers to help us bring them to market. These include improved and expanded buildings coverage and greater insights for existing solar installations with Detected Arrays. Learn more.
Google for Startups Accelerator: Women Founders applications are now open for women-led startups headquartered in Europe and Israel. Discover why this program could be the perfect fit for your startup and apply before January 24th, 2025.
Best of N: Generating High-Quality Grounded Answers with Multiple Drafts - We are excited to announce that Check Grounding API has released a new helpfulness score feature. Building on top of our existing groundedness score, we now enable users to implement Best of N to improve RAG response quality without requiring extensive model retraining. Learn more about Best of N and how it can help you here.

The Year in Google Cloud — 2025

Fri, 19 Dec 2025 17:00:00 +0000

In the AI era, when one year can feel like 10, you’re forgiven for forgetting what happened last month, much less what happened all the way back in January. To jog your memory, we pulled the readership data for top product and company news of 2025. And because we publish a lot of great thought leadership and customer stories, we pulled that data too. Long story short: the most popular stories largely mapped to our biggest announcements. But not always — there were more than a few sleeper hits on this year’s list. Read on to relive this huge year, and perhaps discover a few gems that you may have missed.

January

2025 started strong with important new virtual machine offerings, foundational AI tooling, and tools for both Kubernetes and data professionals. We also launched our "How Google Does It" series, looking at the internal systems and engineering principles behind how we run a modern threat-detection pipeline. We showed developers how to get started with JAX and made AI predictions for the year ahead. Readers were excited to learn about how L’Oréal built its MLOps platform and Deutsche Börse’s pioneering work on cloud-native financial trading.

Product news

Thought leadership:

Customer stories

February

There are AI products, and then there are products enhanced by AI. This month’s top launch, Gen AI Toolbox for Databases, falls into the latter category. This was also the month readers got serious about learning, with blogs about upskilling, resources, and certifications topping the charts. The fruits of our partnership with Anthropic made an appearance in our best-read list, and engineering leaders detailed Google’s extensive efforts to optimize AI system energy consumption. Execs ate up an opinion piece about how agents will unlock insights into unstructured data (which makes up 90% of enterprises’ information assets), and digested a sobering report on AI and cybercrime. During the Mobile World Congress event, we saw considerable interest in our work with telco leaders like Vodafone Italy and Amdocs.

Product and company news:

Thought leadership

Customer stories

March

Back when we announced it, our intent to purchase cybersecurity startup Wiz was Google’s largest deal ever, and the biggest tech deal of the year. We built on that security momentum with the launch of AI Protection. We also spread our wings to the Nordics with a new region, and announced the Gemma 3 open model on Vertex AI. Meanwhile, we explained the threat that North Korean IT workers pose to employers, gave readers a peek under the hood of the Colossus file system, and reminisced about what we’ve learned over 25 years of building data centers. Readers were interested in Levi’s approach to data and weaving it into future AI efforts, and in honor of the GDC Festival of Gaming, our AI partners shared some new perspectives on “living games.”

Product and company news

Thought leadership

Customer stories

April

With April came Google Cloud Next, our flagship annual conference. From Firebase Studio, Ironwood TPUs, and Google Agentspace, to Vertex AI, Cloud WAN, and Gemini 2.5, it’s hard to limit ourselves to just a few stories, there were so many bangers (for the whole list, there’s always the event recap). Meanwhile, our systems team discussed innovations to keep data center infrastructure’s thermal envelope in check. And at the RSA Conference, we unveiled our vision for the agentic security operations center of the future. On the customer front, we highlighted the startups who played a starring role at Next, and took a peek behind the curtain of The Wizard of Oz at Sphere.

Product and company news

Thought leadership

Customer stories

May

School was almost out, but readers got back into learning mode to get certified as generative AI leaders. You were also excited about new gen AI media models in Vertex AI, the availability of Anthropic’s Claude Opus 4 and Claude Sonnet 4. We also learned that you’re very excited to use AI to generate SQL code, and about using Cloud Run as a destination for your AI apps. We outlined the steps for building a well-defined data strategy, and showed governments how AI can actually improve their security posture. And on the customer front, we launched our “Cool Stuff Customers Built” round-ups, and ran stories from Formula E and MLB.

Thought leadership

Customer stories

June

Up until this point, the promise of generative AI was largely around text and code. The launch of Veo 3 changed all that. Developers writing and deploying AI apps saw the availability of GPUs on Cloud Run as a big win, and we continued our steady drumbeat of Gemini innovation with 2.5 Flash and Flash-Lite. We also shared our thoughts on securing AI agents. And to learn how to actually build these agents, readers turned to stories about Box, the British real estate firm Schroders, and French luxury conglomerate LVMH (home of Louis Vuitton, Channel, Sephora and more).

Thought leadership

Customer stories

July

Readers took a break from reading about AI to read about network infrastructure — the new Sol transatlantic cable, to be precise. Then it was back to AI: new video generation models in Vertex; a crucial component for building stateful, context-aware agents; and a new toolset for connecting BigQuery data to Agent Development Kit (ADK) and Multi-Cloud Protocol (MCP) environments. Developers cheered the integration between Cloud Run and Docker Compose, and executive audiences enjoyed a listicle on actionable, real-world uses for AI agents.

On the security front, we took a back-to-basics approach this month, exploring the persistence of some cloud security problems. And then, back to AI again, with our Big Sleep agent. Readers were also interested in how AI is alleviating record-keeping for nurses at HCA Healthcare, Ulta Beauty’s data warehousing and mobile record keeping initiatives, and how SmarterX migrated from Snowflake to BigQuery.

Thought leadership

Customer stories

August

AI is compute- and energy-intensive; in a new technical paper, we released concrete numbers about our AI infrastructure’s power consumption. Then people went [nano] bananas for Gemini 2.5 Flash Image on Vertex AI, and developers got a jump on their AI projects with a wealth of technical blueprints to work from. The summer doldrums didn’t stop our security experts from tackling the serious challenge of cyber-enabled fraud. We also took a closer look at the specific agentic tools empowering workers at Wells Fargo, and how Keeta processes 11 million blockchain transactions per second with Spanner.

Thought leadership

Customer stories

September

AI is cool tech, but how do you monetize it? One answer is the Agent Payment Protocol, or AP2. Developers and data scientists preparing for AI flocked to blogs about new Data Cloud offerings, the 2025 DORA Report, and new trainings. Executives took in our thoughts on building an agentic data strategy, and took notes on the best prompts with which to kickstart their AI usage. And because everybody is impacted by the AI era, including business leaders, we explained what it means to be “bilingual” in AI and security. Then, at Google's AI Builders Forum, startups described how Google’s AI, infrastructure, and services are supporting their growth. Not to be left out, enterprises like Target and Mr. Cooper also showed off their AI chops.

Thought leadership

Customer stories

October

Welcome to the Gemini Enterprise era, which brings enhanced security, data control, and advanced agent capabilities to large organizations. To help you prepare, we relaunched a variety of enhancements to our learning platform, and added new commerce and security programs. And while developers versed themselves on the finer points of Veo prompts, we discussed securing the AI supply chain, building AI agents for cybersecurity and defense, and a new vision on economic threat modeling. We partnered with PayPal to enable commerce in AI chats, Germany’s Planck Institute showed how AI can help share deep scientific expertise, and DZ Bank pioneered ways to make blockchain-based finance more reliable.

Thought leadership

Customer stories

November

Whether it was Gemini 3, Nana Banana Pro, or our seventh-generation Ironwood TPUs, this was the month that we gave enterprise customers access to all our latest and greatest AI tech. We also did a deep dive on how we built the largest-ever Kubernetes cluster, clocking in at a massive 130,000 nodes, and we announced a new collaboration with AWS to improve connectivity between clouds.

Meanwhile, we updated our findings on the adversarial misuse of AI by threat actors and on the ROI of AI for security, and executives vibed out on our piece about vibe coding. Then, just in time for the holidays, we took a look at how Mattel is using AI tools to revamp its toys, and Waze showed how it uses Memorystore to keep the holiday traffic flowing.

Thought leadership

Customer stories

December

The year is winding down, but we still have lots to say. Early returns show that you were interested in how to mitigate the React2Shell vulnerability, support for MCP across Google services, and the early access launch of AlphaEvolve. And let’s not forget Gemini 3 Flash, which is turning heads with its high-level reasoning, plus amazing speed and a flexible cost profile.

What does this all mean for you and your future? It’s important to contextualize these technology developments, especially AI. For example, the DORA team put together a guide on how high-performing platform teams can integrate AI capabilities into their workflows, we discussed what it looks like to have an AI-ready workforce, and our Office of the CISO colleagues put out their 2026 cybersecurity predictions. More to the point (guard), you could do like Golden State Warrior Stephen Curry and turn to Gemini to analyze your game, to prepare for the year ahead. We’ll be watching on Christmas Day to see how Steph is faring with Gemini’s advice.

Thought leadership

Customer stories

What Stephen Curry learned about his game from a custom Gemini agent

And that’s a wrap on 2025! Thanks for reading, and see you next year!

Google Cloud Europe establishes new European Advisory Board

Fri, 07 Nov 2025 16:00:00 +0000

Across the world, organizations are partnering with Google Cloud to tackle their toughest challenges, drive digital transformation, and unlock new levels of growth. In Europe, organizations face unique and complex regulatory challenges. To ensure we're delivering the best possible value and experience for our customers here, we have established a new European Advisory Board. This distinguished group of leaders from across various industries will act as a vital feedback channel, help customers navigate complex regulatory landscapes, and foster a strong, sustainable digital economy. Their counsel is key to ensuring Google Cloud products not only meet but exceed European requirements, driving our regional expertise and differentiation and ultimately supporting Europe’s digital transformation.

The board comprises renowned leaders with deep expertise spanning technology, finance, retail, and public service.

The new board members are:

Jim Snabe (Chair): A global business leader and current Chairman of Siemens AG. With a long career at the intersection of technology and innovation, including his time as Co-CEO of SAP AG, Jim brings deep expertise in guiding multinational organizations through digital transformation and growth. His leadership will be pivotal in steering the board’s strategic direction.
Stefan F Heidenreich: A business leader with extensive experience in the consumer goods industry, including as Chairman of the Management Board and CEO of Beiersdorf AG. His knowledge of brand management, market strategy, and organizational leadership will provide valuable commercial insights.
Nigel Hinshelwood: An expert in financial services with significant leadership roles at institutions like HSBC and Lloyds Banking Group. His understanding of Europe’s financial sector and regulatory environment will be crucial for guiding Google Cloud's work with major banking and financial services clients.
Christophe Cuvillier: A prominent French businessman and former CEO of Unibail-Rodamco-Westfield. With a background in luxury, retail, and real estate, Christophe's perspective on customer-centricity and business transformation in the consumer sector will be a key asset to the board.
Tim Radford (from Jan 2026): A former British military leader and operational commander with a background in defense and large-scale project delivery. His insights into leveraging technology to achieve strategic business objectives will be vital to the board's discussions.

"It is a privilege to chair Google Cloud’s EMEA advisory board," said Jim Snabe. "Europe is at a critical juncture in its digital evolution. This board's mission is to provide counsel that helps Google Cloud not only accelerate innovation but also ensure it is done in a way that aligns with Europe’s values and priorities, fostering a secure and inclusive digital future."

The formation of this board underscores Google Cloud's ongoing commitment to a European-first strategy, collaborating closely with local leaders to build technology solutions that are tailored to the continent's unique needs and opportunities. The board will meet periodically to advise Google Cloud leadership on a range of strategic issues, from product development and market entry to policy and sustainability initiatives.

Cool stuff Google Cloud customers built, Oct. edition: Research agents, a World Series hit, agentic "teams" & more

Fri, 31 Oct 2025 15:00:00 +0000

AI and cloud technology are reshaping every corner of every industry around the world. Without our customers, there would be no Google Cloud, as they are the ones building the future on our platform. In this regular round-up, we dive into some of the exciting projects redefining businesses, shaping industries, and creating new categories.

For our latest edition, we look into new research agents from Deutsche Bank and The Max Planck Institute; helping devs strut their stuff with new databases for Rent the Runway; mortgage lender Mr. Cooper’s “team” of AI agents answering tough customer questions; an AI assistant for doctors at Seattle Children’s; FOX Sports brings AI to the World Series broadcast booth & SmarterX helps customers build custom LLMs

Be sure to check back in September to see how more industry leaders and exciting startups are putting Google Cloud technologies to use. And if you haven’t already, please peruse our list of 1,001 real-world gen AI use cases from our customers.

Deutsche Bank reimagines research with AI agents

Who: At Deutsche Bank Research, the core mission of analysts is delivering original, independent economic and financial analysis. However, creating research reports and notes relies heavily on a foundation of painstaking manual work.

What they did: To enhance the research analyst experience and reduce the reliance on manual processes and outsourcing, the team at Deutsche Bank created DB Lumina — an AI-powered research agent that helps automate data analysis, streamline workflows, and deliver more accurate and timely insights — all while maintaining the stringent data privacy requirements for the highly regulated financial sector. DB Lumina’s core conversational interface enables analysts to interact with Google’s state-of-the-art AI foundation models , including the multimodal Gemini models orchestrated through Vertex AI.

Why it matters: DB Lumina is already in the hands of around 5,000 users across Deutsche Bank Research, with plans to roll out to 10,000 by year end. Analysts reported significant time savings, saving 30 to 45 minutes on preparing earnings note templates and saving up to two hours when writing research reports and roadshow updates. Analysts are also reporting increased depth in their work, with one analyst achieving 50% more detail, adding additional sections by region and activity.

Learn from us: “DB Lumina has proved the value of combining RAG, gen AI, and conversational AI, but this is just the start of our journey. We believe the future lies in embracing and refining the ‘agentic’ capabilities that are inherent in our architecture. We envision building and orchestrating a system where various components act as agents — all working together to provide intelligent and informed responses to complex financial inquiries.” – Max Sommerfeld, Head of Applied AI Engineering , Deutsche Bank, & Crispin Velez, Global AI incubation, Google Cloud

Rent the Runway supercharges developer speed and insights

Who: Rent the Runway gives customers a “Closet in the Cloud” — on-demand access to designer clothing without the need for ownership. To address both our operational complexity and the high expectations of customers, Rent the Runway is investing heavily in building modern, data-driven services that support every touchpoint.

What they did: The team migrated to CloudSQL with the help of Database Migration Service. The new platform offered the benefits of a managed service — automated backups, simplified disaster recovery, no more patching – while preserving compatibility with the MySQL stack Rent the Runways systems already relied on.

Why it matters: A big win was the developer experience. With built-in query insights and tight integration with Google Cloud, Cloud SQL made it easier for engineers to own what they built. With better visibility and guardrails, our teams are shipping higher-quality code and catching issues earlier in the lifecycle. Meanwhile, our DBAs can focus on strategic initiatives — things like automation and platform-wide improvements — rather than being stuck in a ticket queue. The migration also saved $180,000 annually.

Learn from us: “We’re building toward a platform where engineering teams can move fast without trading off safety or quality. That means more automation, more ownership, and fewer handoffs. With Cloud SQL, we’re aiming for a world where schema updates are rolled out as seamlessly as application code.” – Marcus Creavin, Senior Director, Head of Data, Rent the Runway

Mr. Cooper’s “team” of agents solves complex mortgage questions

Who: Mortgage lender Mr. Cooper’s mission is to “Keep the dream of homeownership alive,” aiming to keep rates and services affordable in one of the most expensive consumer markets there is. We partnered with Google Cloud Consulting to develop an agentic AI system designed to complement and support our team. We call it the Coaching Intelligent Education & Resource Agent, or CIERA.

What they did: Rather than a single agent, CIERA is just like any effective team, with individual agents contributing discreet skills that work together synergistically. There’s a head agent interpreting and overseeing the initial prompt, an orchestrator agent, task and data specialists, a memory agency with recall of past actions, and an evaluation agent that tests accuracy and detects hallucinations. CIERA was built with Vertex AI.

Why it matters: For customers, Mr. Cooper projects a reduction in wait times and a higher rate of first-contact resolution. By automating tedious research for human agents, CIERA will free them to focus on sensitive and complex customer relationships that require a human touch and create better tools and resources for more engaging work. The company anticipates a major reduction in average handling times for a large segment of inquiries and faster, more accurate resolutions.

Learn from us: "The architectural patterns developed with CIERA are not limited to mortgage servicing. This agentic approach — of using an orchestrator to manage a team of specialized AI agents—is a powerful blueprint that can be applied to any industry, including healthcare, logistics and manufacturing, by grappling with information and task complexity." – Meenakshi Subramanian, Senior Principal Architect, Mr. Cooper & Shrihari Srinivasa Murthy, Lead Software Development Engineer, Mr. Cooper

Seattle Children’s AI assistant helping doctors work faster and better

Who: Seattle Children’s is the largest pediatric healthcare system in the world, with 48 hospitals across Alaska, Montana, Idaho, and Washington. With so much ground to cover and diverse patient populations to treat, Seattle Children’s created its pediatric clinical pathways, a set of standardized protocols designed to help clinicians make quicker and more reliable decisions. It’s a critical tool, but cumbersome and PDF- or paper-based.

What they did: Using Vertex AI and Gemini, Seattle Children’s was able to quickly develop its Pathways Assistant. After processing a question, Pathway Assistant searches its PDF metadata, which contains semi-structured data in JSON format that’s been extracted from the PDFs by Gemini and curated by clinicians. It then selects the most relevant PDFs, parses the information — including any complex flowcharts, diagrams, and illustrations embedded in them — and answers the clinician’s question in just a few seconds.

Why it matters: Pathways Assistant has greatly increased the speed and effectiveness with which clinicians get to the right decisions at the point of care, drastically reducing research time and improving patient safety and outcomes. Ultimately, clinicians can spend more time with more patients, not with more PDFs.

Learn from us: "Ultimately, Pathway Assistant is not a decision-making tool but rather an information-finding tool. Research into critical, evidence-based guidelines that used to take hours now takes minutes." – Dr. Darren Migita, Medical Director, Clinical Effectiveness, Seattle Children’s Hospital & Jérôme Massot, Gen AI Cloud Architect, Google Cloud

FOX Sports pitches AI-powered player insights at The World Series

Who: Since 2000, FOX Sports has been the broadcast home of the MLB World Series. The production team is always looking to keep storylines fresh for commentators and analysts like Joe Davis, John Smoltz, and Alex Rodriguez.

What they did: The new FOX Foresight tool is an AI platform built with Vertex AI that was trained on data from many seasons of major league play, down to the smallest details. This allows the production team to ask incredibly specific questions and get answers in seconds. For example, if a certain left-handed hitter is coming up to bat, they could ask: “Who are the top five left-handed batters who played in this year’s playoffs? Now who was best in the ninth inning, and what about when the bases are loaded?

Why it matters: Had they relied on traditional research methods alone, this kind of cross-referencing could have taken minutes or more — long enough that an entire inning might have passed by. But with FOX Foresight, this task takes seconds.

Learn from us: “It helps us spot the big stories — like who’s heating up, who’s struggling and which performances are shaping this postseason,” – Alex Rodriguez, FOX Sports MLB Analyst and former Yankees All-Star

Max Planck Institute shares expert skills with multimodal agents

Who: The Max Planck Institute of Biochemistry in Germany is one of the world’s leading research labs. Part of what makes scientific work so difficult and time consuming is the years it can take to develop expertise, for example on mass spectrometry equipment used for studying cells.

What they did: Researchers at the institute and Google Cloud built a Proteomics Lab Agent that simplifies performing complex scientific procedures through personalized AI guidance — making them easier to execute while automatically documenting the process for others to study. The agent was built using the Agent Development Kit (ADK), Google Cloud infrastructure, and Gemini models, which offer advanced video and long-context understanding uniquely suited to the needs of advanced research.

Why it matters: By making it easier to spot mistakes and offering personalized guidance, the agent can reduce troubleshooting time and build towards a future where real-time AI guidance can help prevent errors from happening. In early tests, the agent successfully identified 74% of all procedural errors (a metric known as recall) with an overall accuracy of 77% when comparing 28 recorded lab procedures against their reference protocols. Researchers also reported creating reference protocols 10-times faster, in about 2.6 minutes.

Learn from us: "This approach helps us capture and share the practical knowledge that is often lost when a researcher leaves the lab. This collected experience will not only accelerate the training of new team members but also creates the data foundation we need for future innovations like predictive instrument maintenance for mass spectrometers and automated protocol harmonization within individual labs and across different labs." – Matthias Mann, Director, Research Department Proteomics and Signal Transduction, Max Planck Institute

SmarterX delivers custom LLMs for its customers

Who: SmarterX is an AI consultancy that helps retailers, manufacturers, and logistics companies minimize regulatory risk, maximize sales, and protect consumers and the environment by giving them AI-driven tools to safely and compliantly sell, ship, store, and dispose of their products

What they did: SmarterX uses BigQuery, Gemini models, and Vertex AI to collect, process, and analyze vast amounts of unstructured regulatory and product data from across the web, using it to train custom, highly accurate large language models for customers. Many don’t have the resources for their own data scientists and programers, so these SmarterX is helping these large consumer packaged goods brands and retailers sell, ship, store, and dispose of regulated products compliantly, for example.

Why it matters: SmarterX has found that built-in grounding — the ability to connect model output to verifiable information sources — makes Gemini a safer, more conscientious way to assemble data for SmarterX customers. And retrieval-augmented generation, or RAG, allows SmarterX to connect Gemini with customers’ proprietary databases, enhancing the LLMs’ accuracy and relevance while helping ensure the security of his customers’ data.

Learn from us: “In the past, you’d need to know how to use a modeling tool, a database tool, and an API deployment tool, as well as understand the math underlying a particular model and how to write code in order to build and deploy a model. Having it all in a single environment with familiar user interfaces enables people without a data science background to be much more productive. It’s incredibly freeing and empowering for them.” – Russell Foltz-Smith, executive vice-president for product and technology, SmarterX

Cool stuff customers built, Sept. edition: Modern edge, faster blockchains, AI for nurses & more

Mon, 29 Sep 2025 16:00:00 +0000

For our latest edition, we explore Uber’s revamped network with modern edge; smarter, AI-infused site search at Target; a wicked fast blockchain built by Keeta Network; HCA Healthcare empowers its nurses with a new AI-powered information portal; Deutche Telecom enhances its data science workloads; Google’s AI infrastructure delivers vastly improved inference for Baseten; Major League Baseball throws fans just the stats they want; and Kakao finds new ways to scale AI workloads.

Be sure to check back in October to see how more industry leaders and exciting startups are putting Google Cloud technologies to use. And if you haven’t already, please peruse our list of 601 real-world gen AI use cases from our customers.

aside_block: <ListValue: [StructValue([('title', 'Try Google Cloud for free'), ('body', <wagtail.rich_text.RichText object at 0x7fdc70baaf70>), ('btn_text', 'Get started for free'), ('href', 'https://console.cloud.google.com/freetrial?redirectPath=/welcome'), ('image', None)])]>

Uber streamlines global network with hybrid edge

Who: Uber operates across six continents, connecting millions of riders and drivers while handling more than 100,000 concurrent trips and more than a million HTTP requests per second.

What they did: When Uber's existing edge architecture had sub-optimal routing paths, the company partnered with Google Cloud to redesign their global network approach. This work involved moving away from the distributed Envoy VMs and using Google Cloud's Hybrid Network Endpoint Groups (NEGs) instead. This new architecture directs traffic from Google's Global External Application Load Balancer — fronted by Google Cloud Armor for DDoS protection and Cloud CDN for caching — directly to Uber's on-premises infrastructure via Cloud Interconnect.

Why it matters: The results of migrating to Hybrid NEG-based load balancers were immediate. By removing all edge VMs, the traffic path became significantly more efficient, allowing Google's global network to handle the long-haul transit over optimized channels. This shift delivered a 2.6% latency improvement at the 50th percentile and 10% at the 99th percentile, directly improving service responsiveness. Removing the entire fleet of edge Envoy VMs resulted in significant cost savings, as well.

Learn from us: "At Uber, every millisecond defines the user experience for millions of people. By re-architecting our global edge with Google Cloud and Hybrid NEGs, we've created a more direct, lower-latency path for our services. This not only enhances today's user experience but also provides the high-performance foundation necessary for our next generation of AI applications, all while significantly reducing operational overhead for our engineering teams." – Harry Liu, Director of Networking, Uber

Target rebuilds search experience with AlloyDB AI hybrid search

Who: Target is one of America's largest retailers, serving millions of guests through its digital storefront and physical stores nationwide and has been a long-time pioneer of omnichannel retail experiences.

What they did: Target reimagined its site search using hybrid techniques that bring together traditional and semantic methods, backed by a powerful new foundation built with AlloyDB AI. Their new hybrid search platform combines classic keyword matching with semantic search to handle queries like "eco-friendly water bottles under $20" or "winter jackets for toddlers" that blend semantic nuance with structured constraints like price, category, brand, sizes or store availability.

Why it matters: Target has seen up to 10x faster execution, product discovery relevance improved by 20%, and half the number of 'no results' queries. Additionally, Target has reduced vector query response times by 60%, which resulted in a significant improvement in the guest experience while maintaining more than 99.99% uptime.

Learn from us: "Search at Target is evolving into something far more dynamic — an intelligent, multimodal layer that helps guests connect with what they need, when and how they need it. As our guests engage across devices, languages, and formats, we want their experience to feel seamless and smart." – Vishal Vaibhav, Principal Engineer, Target

Keeta Network hits 11 million transactions per second with Spanner

Who: Keeta Network is a layer‑1 blockchain that unifies transactions across different blockchains and payment systems, eliminating the need for costly intermediaries, reducing fees, and enabling near‑instant settlements.

What they did: Keeta built a layer‑1 blockchain that unifies transactions across different blockchains and payment systems, eliminating the need for costly intermediaries, reducing fees, and enabling near‑instant settlements. The company engineered its network to meet the stringent regulatory and operational requirements of financial institutions using Spanner as the foundation for its distributed ledger, leveraging Spanner's availability and elastic scalability to scale up or down as needed without downtime or costly over-provisioning.

Why it matters: By facilitating cross-chain transactions and interoperability with existing payment systems, Keeta bridges the gap between cryptocurrencies and fiat, enabling a secure, efficient, and compliant global financial ecosystem. The company's architecture natively supports asset tokenization and digital identity, making it an ideal platform for stablecoins and real-world asset transfers while eliminating costly intermediaries and reducing fees for financial institutions.

Learn from us: "Keeta Network is unbounded by design, enabling it to scale horizontally to handle the increasing demand of participants. Similarly, Spanner’s scale-out architecture allows for linear read and write scaling in dozens of regions globally, all while maintaining consistency and latency." –Ty Schenk, CEO, Keeta Network

HCA Healthcare streamlines nurse shift changes with AI-powered handoff app

Who: HCA Healthcare is America's largest for-profit hospital network, operating 190 hospitals and approximately 2,400 ambulatory sites of care with 99,000 nurses across their system.

What they did: HCA Healthcare's Digital Transformation & Innovation department developed a tool for nursing staff, using Google's generative AI foundation models, that can ingest, analyze, and develop a cohesive and concise view of pertinent patient information for the oncoming nurse for handoff. The Nurse Handoff app shows nurses the electronic health record on one side and the AI-generated output on the other, allowing nurses to easily review and add information throughout their shift using hospital-provided mobile devices.

Why it matters: This innovation addresses a massive operational challenge across HCA Healthcare's system: Nurse handoffs occur approximately 60,000 times daily across their facilities, with each handoff taking about 40 minutes per shift, totaling 10 million aggregate hours annually for all HCA Healthcare nurses. Nurses have rated the Nurse Handoff app as 86% factual and 90% helpful. The smoother the handoff, the more time nurses can spend with patients.

Learn from us: "One of DT&I's guiding principles for digital transformation is to address the administrative burden on clinicians. ... We wanted to train a large language model system to organize information like a nurse and figure out key pieces of information that it needs to extract from the chart, then organize them in an intelligent way that the oncoming shift could easily consume. To transform patient care, the needs of caregivers must be prioritized, too." –Dr. Michael Schlosser, Senior Vice President and Chief Transformation Officer, HCA Healthcare

Deutsche Telekom transforms data science workloads with BigQuery DataFrames

Who: Deutsche Telekom is one of Europe's leading telecommunications companies, serving millions of customers across multiple markets and maintaining a significant presence in the global telecommunications industry.

What they did: Deutsche Telekom migrated their critical data science workloads from legacy on-premises PySpark systems to BigQuery DataFrames, executing a strategic two-phase migration that leveraged Gemini AI for accelerated code conversion. The team moved their CLV calculations and other distributed Python data processing workloads to BigQuery, standardizing on a single data processing technology while maintaining familiar pandas-like APIs.

Why it matters: The transformation eliminated performance bottlenecks from legacy systems, enabling faster time to insights, improved scalability, and reduced operational risk while allowing the team to leverage existing data science skills.

Learn from us: Deutsche Telekom completed their entire migration in just one person-week, with AI doing 95% of the heavy lifting on code conversion. Sometimes the biggest transformations require the smallest teams when you let technology do what it does best.

Baseten achieves 225% better cost-performance for AI inference

Who: Baseten is a six-year-old Series C company that partners with Google Cloud and NVIDIA to provide enterprise companies a scalable inference platform for their proprietary models as well as open models like Gemma, DeepSeek, and Llama, with an emphasis on performance and cost efficiency.

What they did: By leveraging the latest Google Cloud A4 virtual machines (VMs) based on NVIDIA Blackwell, and Google Cloud's Dynamic Workload Scheduler (DWS), Baseten has achieved 225% better cost-performance for high-throughput inference and 25% better cost-performance for latency-sensitive inference. Their approach is rooted in coupling the latest accelerated hardware with leading and open-source software to extract the most value possible from every chip, made possible with Google Cloud's AI Hypercomputer.

Why it matters: This breakthrough in performance and efficiency enables companies to move powerful agentic AI and reasoning models out of the lab and into production affordably. This unique combination enables end-users across industries to bring new applications to market, such as powering agentic workflows in financial services, generating real-time audio and video content in media, and accelerating document processing in healthcare — all happening at a scale and cost that was previously unattainable.

Learn from us: "Dynamic Workload Scheduler has saved us more than once when we encounter a failure. Our automated system moves affected workloads to other resources… and within minutes, everyone is up and running again. It is impressive — by the time we're paged … everything is back and healthy." – Colin McGrath, Head of Infrastructure, Baseten

MLB delivers real-time data to millions of fans with edge caching

Who: Major League Baseball is the world’s premier professional baseball league, overseeing 30 teams across North America and serving as the sport's governing body for everything from game rules to the massive data infrastructure that powers modern baseball analytics.

What they did: MLB switched from an outdated data system that frequently crashed to Memorystore for Valkey, which keeps all their live game data flowing smoothly to millions of fans. MLB can now deliver real-time stats, scores, and player information instantly to apps, stadium screens, and TV broadcasts.

Why it matters: MLB now handles nearly 10 billion requests daily and 15,000 API requests per second during peak games, ensuring that when a pitcher throws a 100-mph fastball or a runner steals second base, fans see the stats and updates instantly across every platform. In a sport where games can change on a single pitch, speed isn't just nice to have — it's essential for keeping millions of fans engaged and connected to the live action.

Learn from us: "With Memorystore for Valkey, we're in a position to move faster, build smarter, and deliver better experiences for everyone who depends on our data — from fans in the stands to broadcasters, analysts, and club staff." – Rahul Joshi, Principal Software Engineer, Major League Baseball

Kakao scales AI models with strategic JAX and Cloud TPU adoption

Who: Kakao operates KakaoTalk, South Korea's dominant messaging platform serving 49 million people – 93% of the country's population.

What they did: Facing critical limitations with their existing GPU-based infrastructure reaching power and budget capacity constraints, Kakao made a strategic shift to Google Cloud TPUs using the JAX framework. They worked with Google Cloud to adapt training tools for their specific needs, including customizing how they blend different data sources and process information to work seamlessly with their existing systems.

Why it matters: This enabled development of Kakao’s proprietary Kanana model family, with several Kanana models — including Kanana-MoE — recently released as open source on Hugging Face Hub. After switching to TPUs, Kakao observed an immediate and throughput increase of 2.7x across their models, along with improved cost-performance efficiency.

Learn from us: "We had two options: expand our GPU infrastructure and maintain our existing codebase, or adopt Cloud TPUs, which offered cost-performance advantages while requiring adoption of a new toolchain. We chose Cloud TPUs, viewing the short-term investment as worthwhile for long-term cost-performance benefits." – Minho Ryu & Nayeon Kim, Language Model Research Engineers, Kakao

The global harms of restrictive cloud licensing, one year later

Thu, 25 Sep 2025 05:00:00 +0000

A year ago today, Google Cloud filed a formal complaint with the European Commission about Microsoft’s anti-competitive cloud licensing practices — specifically those that impose financial penalties on businesses that use Windows Server software on Azure’s biggest competitors.

Despite regulatory scrutiny, it’s clear that Microsoft intends to keep its restrictive licensing policies in place for most cloud customers. In fact, it’s getting worse.

As part of a recent earnings call, Microsoft disclosed that its efforts to force software customers to use Azure are “not anywhere close to the finish line,” and represented one of three pillars “driving [its] growth.” As we approach the end of September, Microsoft is imposing another wave of licensing changes to force more customers to Azure by preventing managed service providers from hosting certain workloads on Azure’s competitors.

Regulators have taken notice. As part of a comprehensive investigation, the U.K.’s Competition and Markets Authority (CMA) recently found that restrictive licensing harms cloud customers, competition, economic growth, and innovation. At the same time, a growing number of regulators around the world are also scrutinizing Microsoft's anti-competitive conduct — proving that fair competition is an issue that transcends politics and borders.

While some progress has been made, restrictive licensing continues to be a global problem, locking in cloud customers, harming economic growth, and stifling innovation.

Economic, security, and innovation harms

Restrictive cloud licensing has caused an enormous amount of harm to the global economy over the last year. This includes direct penalties that Microsoft forces businesses to pay, and downstream harms to economic growth, cybersecurity, and innovation. Ending restrictive licensing could help supercharge economies around the world.

Microsoft still imposes a 400% price markup on customers who choose to move legacy workloads to competitors’ clouds. This penalty forces customers onto Azure by making it more expensive to use a competitor. A mere 5% increase in cloud pricing due to lack of competition costs U.K. cloud customers £500 million annually, according to the CMA. A separate study in the EU found restrictive licensing amounted to a billion-Euro tax on businesses.

In the United States, the lack of competition due to Microsoft’s licensing tactics amounts to $750 million in overspending by government agencies every year.

Cybersecurity and reliability also suffer, as Microsoft drives customers into an insecure monoculture that becomes a single point of failure. Attacks on Microsoft’s insecure software have spread across governments and critical industries.

With AI technologies disrupting the business market in dramatic ways, ending Microsoft’s anti-competitive licensing is more important than ever as customers move to the cloud to access AI at scale. Customers, not Microsoft, should decide what cloud — and therefore what AI tools — work best for their business.

The ongoing risk of inaction

Perhaps most telling of all, the CMA found that since some of the most restrictive licensing terms went into place over the last few years, Microsoft Azure has gained customers at two or even three times the rate as competitors. Less choice and weaker competition is exactly the type of "existential challenge” to Europe’s competitiveness that the Draghi report warned of.

Ending restrictive licensing could help governments “unlock up to €1.2 trillion in additional EU GDP by 2030” and “generate up to €450 billion per year in fiscal savings and productivity gains,” according to a recent study by the European Centre for International Political Economy. Now is the time for regulators and policymakers globally to act to drive forward digital transformation and innovation.

In the year since our complaint to the European Commission, our message is as clear as ever: Restrictive cloud licensing practices harm businesses and undermine European competitiveness. To drive the next century of technology innovation and growth, regulators must act now to end these anti-competitive licensing practices that harm businesses.

Cool stuff customers built, July edition: Data agents, deep financial research, hospital fall detection & more

Tue, 29 Jul 2025 16:00:00 +0000

For our latest edition, we explore Box’s AI agents extracting insights with cross-platform agent integration; Schroders uses multiple connected agents to build a complex investment research system; Hypros’ IoT device can monitor patient distress in hospitals without individual monitoring; a Formula E exhibition of whether regenerative braking can power an EV supercar for an entire lap; a unified data and AI platform at LVMH that can serve 75 distinct luxury brands; Alpian deploys AI to become the most advanced cloud-native private bank in Switzerland; a gen-AI-powered tool estimates where potential home runs might land in the stands during the MLB All-Star Game & Oviva developed an AI-powered meal-logging app.

Be sure to check back in September to see how more industry leaders and exciting startups are putting Google Cloud technologies to use. And if you haven’t already, please peruse our list of 601 real-world gen AI use cases from our customers.

aside_block: <ListValue: [StructValue([('title', 'Try Google Cloud for free'), ('body', <wagtail.rich_text.RichText object at 0x7fdc866f7d30>), ('btn_text', 'Get started for free'), ('href', 'https://console.cloud.google.com/freetrial?redirectPath=/welcome'), ('image', None)])]>

Box’s next-gen AI agents extract insights across data domains

Who: Box is one of the original information sharing and collaboration platforms of the digital era. They’ve helped define how we work, and they’ve continued to evolve those practices alongside successive waves of new technology.

What they did: Thanks to the exciting advances of the generative AI era, with all the data that Box users have stored, they can now get considerably more value out of those files by using AI to search and synthesize their information in new ways. That’s why Box created Box AI Agents, to intelligently discern and structure complex unstructured data.

Why it matters: Box built its agents using Gemini 2.5 models, our most advanced generative AI, and the new Agent2Agent protocol, which enables integration between agents across dozens of platforms. Not only do the Box AI Agents deliver new capabilities to users, they also demonstrate how advanced agent connections can work at scale across platforms.

Learn from us: "The Box AI Enhanced Extract Agent gives enterprise users confidence in their AI, helping overcome any hesitations they might feel about gen AI technology and using it for business-critical tasks. … With the Box AI Enhanced Extract Agent, we wanted to transform how businesses interact with their most complex content — whether that’s scanned PDFs, images, slides, and other diverse materials — and then turn it all into structured, actionable intelligence.” -Yashoda Bhavnani, Head of AI, Box & Dr. Ali Arsanjani, Director, Applied AI Engineering, Google Cloud

Schroders’ multi-agent financial-analysis research assistant

Who: Schroders is a leading global active investment manager with roughly $975 billion in assets under management and a recognized leader in sustainable investment.

What they did: Schroders analysts are responsible for covering as many as 50 companies at a time. To maximize analysts’ impact, Schroders is enabling its analysts to shift from data collection to the higher-value strategic thinking that is critical for business scalability and client investment performance. This is why Schroders and Google Cloud collaborated to build a multi-agent research assistant prototype using Vertex AI Agent Builder.

Why it matters: Personalization and avoiding rigid processes was a core goal for supporting analysts' unique workflows. The system uses customizable system instructions — underlying prompts that can be tuned by analysts and developers. In addition, the system allows for personalized agent configuration. Analysts in the pilot have reported significant satisfaction and time savings in working with the agent.

Learn from us: “Along the way, the team also discovered several key learnings for building effective agents: Meticulously decompose tasks. Prompt engineering is key. Tool reliability is non-negotiable. Limit tool scope per agent. Managing state is complex. Leverage Agent-of-Agents protocols. User trust is earned.” – Ed Jeffery, Principal Software Engineer, Investment AI R&D, Schroders & Megha Agarwal, AI Engineer, UK/I Customer Engineering, Google Cloud

Hypros develops IoT scanners to detect hospital falls

Who: Hypros offers customized solutions and practical insights for healthcare in the digital age, offering a range of services including process analysis and unique platforms and devices.

What they did: Monitoring patients in care settings is a critical task, but patients cannot be monitored continuously and need privacy, both in the room and digitally. Hypros set out to develop an in-room IoT device powered by AI that can sense fallen or distressed patients with a two-stage AI workflow that determines when patients need help without actively watching at all times.

Why it matters: Through a combination of low-resolution sensors and a pair of AI models that can recognize distress even from obscured, anonymized sensor readings, Hypros created a device that gives caregivers confidence in its accuracy and gives patients comfort that they are not being constantly watched. This two-step process demonstrates the power of diverse AI modalities working in concert, an approach that’s becoming increasingly common for agentic AI.

Learn from us: “Instead of stockpiling sensor data, the system uses advanced AI models to interpret and connect data from multiple streams — turning simple raw readings into practical insights that guide better decisions. Real-time alerts also bring timely attention to critical situations — ensuring patients receive the swift and focused care they deserve, and staff can perform at their very best.” – Marcel Walz, CTO, Hypros & Erlandas Norkus, AI Engineer, Hypros

Formula E recharges a race car by descending a mountain

Who: Formula E is a race league famous for its boundary-pushing cars, with near instant acceleration, thanks to electronic motors. Yet EVs also have the unique ability to recharge their batteries through braking, an important tactic during races.

What they did: Leading up to the Monaco E-Prix, Formula E and Google set out to test whether a Formula E GENBETA race car, starting with only 1% battery, could regenerate enough energy from braking during a descent through France’s coastal Alps to then complete a full lap of the iconic Monaco circuit. They used AI modeling to run numerous trials before attempting this feat.

Why it matters: The team started with a straightforward prompt in Google’s AI Studio, asking if the descent would work. Using Gemini 2.5 Pro’s deep learning feature, the model assessed all the factors, like terrain, weather, and vehicle specs, and determined the project was “theoretically feasible.” It’s a powerful example of the R&D power of gen AI. During the event, Firebase and BigQuery helped visualize real-time telemetry, while data from multiple sensors and Google Maps enabled continual status updates.

Learn from us: “From figuring out if our crazy Mountain Recharge idea was even possible, to giving us live insights during the descent, AI was our guide. It’s what turned an ambitious ‘what if' into a reality we could track moment by moment.” – Alex Aidan, VP of Marketing, Formula E

LVMH creates a data estate for 75 diverse maisons

Who: The world’s largest luxury conglomerate, LVMH is home to such iconic brands as Louis Vuitton, Moët & Chandon, and Hennessy as well as Dior, Tiffany and Co., Bvlgari, Sephora, Celine, and Dom Perignon. While each maintains a high degree of autonomy, they all rely on LVMH’s IT to create services for them.

What they did: For four years, LVMH has been working with Google Cloud to build a data foundation for its brands, particularly as they lacked a 360-degree view of customers across the different brands. With that foundation in place, they’ve begun layering on generative AI features, such as chat agents for client advisors in their shops.

Why it matters: The various generative AI platforms now have more than 40,000 monthly global users doing more than 1.5 million queries, such as analyzing documents and creating translations. These AI tools are also helping to further deepen personalization in customer relationships and boosting operational efficiency between teams and collaborators.

Learn from us: “If you want to really compare it to pure retail e-commerce, their solutions are very mass market, with big data and automation. Automation wouldn’t really fit for us, we’re looking for a truly differentiated approach. But where it can deepen our connections with our clients even more, that is the hallmark of LVMH service — excellent and effortless. That’s what our technology is for.” – Franck Le Moal, Chief Information Officer, LVMH

Alpian redefines private banking for the digital age

Who: The first fully cloud-native private bank in Switzerland, Alpian boasts a unique model that blends personal wealth management with digital convenience.

What they did: Working within the highly regulated world of finance, Alpian sought to deploy generative AI tools to automate processes and deliver better services. Tools like Gemini and Vertex AI have streamlined traditionally complex processes, allowing developers to interact with infrastructure through simple conversational commands.

Why it matters: The idea was ours, but given all the factors — combing through reams of player data, combining it with up-to-the-minute batting orders or traffic conditions and then coming up with a range of messages we could quickly display — it took the help of AI to get it into play.

Learn from us: “By aligning technological advancements with regulatory requirements, Alpian is creating a model for the future of banking — one where agility, security, and customer-centricity can come together seamlessly and confidently.” – David Nemeshazy, CTO, Alpian & Damien Chambon, Head of Cloud, Alpian

MLB delights fans in the stands during All-Star Game

Who: Major League Baseball is constantly innovating with new technology platforms to keep fans connect to one of the most statistically and historically rich sports.

What they did: Google Cloud teamed up with the Statcast unit of Major League Baseball to build a gen-AI-powered tool that estimated where potential home runs might land in the stands during the MLB All-Star Game. Using data like a player's at-bat history and other real-world factors, this agentic AI system gave fans attending the game some hint of whether they might snag a lucky homer.

Why it matters: Using the home run modeler to assess where the next players at-bat might hit a home run, the creative team then used Gemini 2.5 Pro to quickly create a selection of taglines. They would then select their favorite option, quickly making any tweaks to the language, before displaying it on the Jumbotron and digital displays around the park. This “human-in-the-loop” review is an increasingly common practice in AI-powered work.

Learn from us: “Watching these messages roll through town, we get a real sense of just what a team player AI can be. The idea was ours, but given all the factors — combing through reams of player data, combining it with up-to-the-minute batting orders or traffic conditions and then coming up with a range of messages we could quickly display — it took the help of AI to get it into play.” – Hussain Chinoy, Technical Solutions Manager for Gen AI, Google Cloud & Emmanuel Awa, AI Blackbelt, Google Cloud

Oviva develops meal-logging app with AI-powered advice

Who: Oviva developed an AI-powered meal-logging app that simplifies the meal-logging process and enhances the quality of feedback people receive, helping them make better dietary decisions.

What they did: Our AI algorithms analyze the logged meals in near real-time, providing people with feedback that is not just specific and personalized but also easy to understand and act upon. This feedback focuses on helping people maintain a balanced diet throughout the day, rather than overwhelming them with detailed nutritional breakdowns.

Why it matters: Oviva’s user base exhibits cyclical activity patterns, with meal logging concentrated around specific times. This behavior necessitates significant fluctuations in processing resources, sometimes requiring several orders of magnitude higher capacity. Google’s AI-optimized infrastructure offers low latencies and excellent availability that have proven to be a reliable way to achieve our goals, without dedicating engineering resources to make our offering scalable.

Learn from us: “The AI-powered meal logging feature is making a significant difference in how they approach their diets. People report feeling more confident in their food choices and more motivated to maintain healthy eating habits. The simplicity and immediacy of the feedback have also improved user retention.” – Manuel Baumann, Co-Founder & CTO, Oviva AG & Nicolas Wipfli, Customer Engineer, Google Cloud

London Summit: agentic AI leaders, training 100,000 civil servants, AI sovereignty, and more

Wed, 09 Jul 2025 08:00:00 +0000

There’s a buzz of excitement here at Tobacco Dock as we welcome our customers and partners to the Google Cloud Summit London. Together, we’re exploring the essential role Google Cloud is playing in driving AI innovation and adoption across the UK. Today is about shining a spotlight on our customers and partners, focusing on the real-world stories of how they are accelerating innovation, realising value, and reshaping entire industries with the powerful combination of AI agents and robust cloud infrastructure.

The opportunity ahead is immense. AI is poised to inject more than £400 billion into the UK economy by 2030, and this year’s summit reaffirms our long-term commitment to helping the UK realise its potential and shape its AI future.

Investing in Britain’s digital future

To lead in the AI era, a nation needs a strong digital foundation. That’s why we’re proud to announce a series of strategic commitments to the UK’s digital future.

First, we are launching a new partnership with the UK Government to help modernise public services. This collaboration marks a significant shift, exploring the use of advanced tech and AI to move beyond decades-old legacy contracts that can leave essential services vulnerable. It supports the UK Government's "blueprint for a modern digital government" by aiming to streamline services, reduce costs, and lay the digital foundations for AI success.

Equally important, we’re investing in a world-class, AI-ready workforce. Today, we are announcing a landmark proposal to provide free cloud and AI skills training for up to 100,000 UK public sector workers. This initiative is designed to accelerate the digital transformation of public services and empower the workforce with the talent to lead in the AI era.

These commitments are backed by our continued investment in critical infrastructure. We are close to reaching a major milestone with our data center in Waltham Cross, which will be fully operational by the end of the year. Delivering on our promise, this facility will provide British businesses with the high-performance, low-latency cloud they need to compete globally.

From AI vision to real-world value

Agentic AI is emerging as a major force in enterprise technology, representing a foundational shift in how work gets done. We're helping British businesses go beyond experimentation and embrace a new era of intelligent agents. With advanced models like Gemini on our Vertex AI platform, we’re giving businesses the toolkits to drive real results and realise value faster.

At the Summit, we're showcasing how leading UK companies are already leveraging these capabilities to drive impact:

Imperial War Museums is the first UK museum to use AI at scale to digitise and transcribe oral histories. Implemented by our partner Capgemini, the Gemini-engineered system will make more than 20,000 histories from 1945 to the early 2000s searchable and accessible.
LUSH is taking advantage of Vertex AI and Cloud Storage to reduce packaging waste through AI-powered product recognition at checkout in its beauty shops.
Morrisons’ new in-app Product Finder—built with BigQuery and Gemini—helps customers quickly locate products in its grocery stores. It was used 50,000 times a day during the most recent Easter period, proving its immense practical value.
Starling Bank launched "Spending Intelligence," an industry-leading AI tool powered by Gemini models. Customers can now understand their spending habits simply by asking natural language questions and getting instant analysis.
Toolstation now offers customers highly accurate product search results online and in-store, powered by Vertex AI Search for Commerce, which is boosting customer satisfaction and sales.

Extending Our Impact Through a Trusted Ecosystem

Collaboration is fundamental to progress. The achievements we celebrate today wouldn't be possible without our incredible network of partners. Our work with Capgemini is helping British-born companies like Additive Catchments, a majority non-profit-owned company, to deploy AI-powered water stewardship solutions. Leveraging Google Cloud, they provide real-time insights to improve water quality and safeguard ecosystems across the UK—a perfect example of technology for good.

This kind of innovation isn’t happening in isolation. Since 2023, more than 60% of UK generative AI startups have chosen Google Cloud due to our deep commitment to the ecosystem. From our ‘Gemini for UK’ initiative, which offers up to £280,000 in cloud credits and access to expert mentorship and training, to our recent partnership with Tech London Advocates, our aim is to help founders scale faster.

We’ve also secured spaces for top UK AI Startups on the Europe-wide Google for Startups accelerator. These companies, such as Martee ai, are on a mission to improve the face of grab-and-go food, for the benefit of people and the planet, and Dyad AI, which is helping healthcare providers improve care quality and automate administrative workflows. They will be joining 15 top AI startups from across Europe in receiving expert help from Google so they can take their startups to the next level.

Setting a Secure Foundation for a Bold Future

A big part of our mission is to be the most trusted cloud partner for businesses, exemplified through our leading security, data sovereignty, and responsible AI practices. At the summit, Lloyds Banking Group and Vodafone are sharing how they are using Google Cloud’s security tools to help protect their operations and innovate securely for millions of customers.

This deep commitment to security is why Google Cloud announced plans earlier this year to acquire Wiz. By integrating Wiz’s best-in-class, multi-cloud visibility with Mandiant’s unmatched threat intelligence, we will offer UK businesses proactive, comprehensive protection across their entire cloud estate.

For UK organizations, including the public sector, we're also building trust in generative AI by ensuring data sovereignty and compliance, so they can use this technology while keeping their data completely secure. Today we are happy to share that Google Cloud is strengthening its UK data residency commitment, empowering organizations with the choice to keep Gemini 2.5 Flash processing entirely within the UK. This expansion opens up even more use cases for businesses operating here.

This combination of world-class security and a commitment to openness is the foundation upon which UK organizations can innovate with confidence. Our leadership in open-source technologies like Kubernetes enables them to build and run applications anywhere, knowing their data is protected by world-class security. Whether it’s a bank securing its services, a retailer reimagining the customer experience, or a startup building the next big thing, our goal is to provide the tools and the trust to build boldly.

With that mission in mind, UK businesses have a real opportunity to lead on the global stage. Together, with our customers, partners, and the public sector, we’re building much more than a cloud platform; we’re helping UK organisations not only stay ahead but to move boldly into the future and shape the AI era.

Didn’t make it to London? Please browse our catalogue of upcoming events & sign up to join us at another exciting gathering of cloud and AI leaders from across industries and around the world.

Cool stuff customers built, May edition: Visual scouts, racing agents, agile ads & more

Tue, 13 May 2025 16:00:00 +0000

AI and cloud technology are reshaping every corner of every industry around the world. Without our customers, there would be no Google Cloud, as they are the ones building the future on our platform. In this monthly round-up, we dive into some of the exciting projects redefining businesses, shaping industries, and creating new categories.

For our inaugural edition, we explore Lowe’s new Visual Scout product recommendation engine powered by Vertex AI Vector Search; a responsive “Driver Agent” platform created by Formula E to bring more equity to the track; Ester AI, a conversational tool from wealth.com that can help financial planners review wills and trusts; a new operational dashboard that’s improving service for African super app Yassir; and AI-powered knowledge base health insurer SIGNAL IDUNA is using to enhance customer experience; how AlloyDB helped autonomous driving company Nuro manage millions of real-time image queries more efficiently and cost effectively; and Mars Wrigley can now measure and update ads more agilely with Cortex Framework.

Be sure to check back in June to see how more industry leaders and exciting startups are putting Google Cloud technologies to use. And if you haven’t already, please peruse our list of 601 real-world gen AI use cases from our customers.

Lowes’ Visual Scout sees sales boost

Who: One of the world’s leading hardware store chains, Lowe’s faced a common ecommerce challenge: Many of its customers come to the site or mobile app without a clear idea of what they want but believe that they will recognize the right product when they see it.

What they did: Using Vertex AI Vector Search to help build connections across products, Lowe’s created Visual Scout. It offers an interactive experience for customers to discover a variety of styles within a product group, starting with a panel of 10 items. Customers then indicate their preferences by “liking” or “disliking” items in the display, and then Visual Scout dynamically updates the panel with items that reflect customer preferences.

Why it matters: As the service updates in real time, Visual Scout provides an engaging and gamified shopping experience that encourages customer engagement and, ultimately, conversion.

Learn from us: "Both [Vector Search and Feature Store] help Visual Scout process a high volume of requests while maintaining low-latency responses. The 99th percentile response times of approximately 180 milliseconds align with our performance expectations, and ensures a smooth and responsive user experience.” – Zaid Alibadi, Senior Manager for Data Science, Lowe’s & Olga Stolpovskaia, Senior Data Scientist, Lowe's

Formula E’s Driver Agent boosts the next generation of racers

Who: Formula E is a new racing league whose radical eclectic-powered cars are meant to pave the way for the road cars of tomorrow, with the series acting as a competitive platform to test and develop the latest in electric technology.

What they did: Formula E launched the "Driver Agent," an AI tool powered by Google's Vertex AI platform and Gemini models, aimed at expanding access to race insights for more teams. The Driver Agent is designed to analyze extensive multimodal data generated during racing and provide actionable insights to drivers, helping democratize access to data-led analysis and coaching.

Why it matters: Google Cloud is actively supporting More than Equal's mission of identifying and developing elite female racing talent, and the Driver Agent helps fulfill this shared mission with Formula E. Race analysis in the Driver Agent is aimed at helping optimize braking and acceleration, generate more downforce, avoid crashes — and, chiefly, improve lap times, which testing has shown to be the case.

Learn from us: "Formula E has always been a platform for innovation… By developing and offering these cutting-edge tools, we are helping to create a future where racing talent is determined by skill, not resources, enabling a more diverse pool of drivers and especially women, rise to the very top of our sport.” – Beth Paretta, VP for Sporting, Formula E

aside_block: <ListValue: [StructValue([('title', 'Try Google Cloud for free'), ('body', <wagtail.rich_text.RichText object at 0x7fdc83b74430>), ('btn_text', 'Get started for free'), ('href', 'https://console.cloud.google.com/freetrial?redirectPath=/welcome'), ('image', None)])]>

Wealth.com reshapes legacy planning

Who: Wealth.com bills itself as “estate planning reimagined,” where a combination of best-in-class technology, AI, and human expertise are combined to elevate the wealth management industry to new levels of service and efficiency.

What they did: It could take even an experienced financial planner hours if not days to understand complex estate planning documents, like trusts, that can run to hundreds of pages. Wealth.com built its Ester AI to solve this by quickly absorbing the information in the documents and automating the most relative and low-value tasks, freeing advisors to focus on valuable work like building better plans and providing better customer relations.

Why it matters: Traditional machine learning models simply can’t handle the scale or complexity of estate planning documents. The team at wealth.com found that Gemini’s industry-leading long context window allowed Ester to achieve a level of understanding previously unattainable. In fact, Ester has identified critical information even wealth.com’s experienced legal team overlooked — an impressive example of how AI can augment human expertise.

Learn from us: “Building Ester itself was no easy task. The complexity of estate planning documents required a careful balance of automation and human oversight. The latter, in the form of our legal experts, lays a critical role in annotating datasets and validating outputs.” – Seungwoo Son, VP of Applied AI, Wealth.com

African super app Yassir delivers on data

Who: Yassir is a super app, supporting the daily lives of users in more than 45 cities across Algeria, Morocco, Tunisia, South Africa, and Senegal who rely on our ride-hailing, last-mile delivery, and financial services solutions.

What they did: The company had two separate data systems, one using Databricks for deploying and training machine learning models and another through Google Cloud and BigQuery for storing and analyzing data. This setup led to several issues, such as formatting incompatibilities and disconnected data. Yassir consolidated its data infrastructure with Google Cloud to bring all of these functions into one place, providing better access to data and more scalability, as well as new opportunities to analyze, review, and improve performance.

Why it matters: Operational dashboards give sales and marketing teams the insights they need to better target and reach merchants and consumers. They also include insights into our staffing processes, helping us to gradually reduce delivery times, complete more rides faster, and improve how we support specific markets. We also have product-level detection and monitoring that help us provide real-time dynamic pricing and identify fraudulent trips and orders.

Learn from us: “With our data unified in BigQuery and connected to our machine learning models, we can better support everything from customer growth and retention to marketplace optimization by providing insights into product usage, customer data, and more.” – Hamdi Amroun, Head of AI, Yassir & Maniganda Perumal, Data Platform Lead, Yassir

SIGNAL IDUNA supercharges customer service

Who: SIGNAL IDUNA is a leading German insurance provider that is particularly active in the private and supplementary insurance market, as well as covering home and auto.

What they did: SIGNAL IDUNA, in collaboration with Google Cloud, BCG and Deloitte, has developed an AI knowledge assistant that empowers service agents to quickly and accurately resolve complex customer inquiries.

Why it matters: This innovative solution uses Google Cloud AI, including Google’s multimodal Gemini models, to help agents find relevant documents and provide comprehensive answers 30% faster — ultimately, enhancing customer satisfaction. And with support from the AI knowledge assistant, SIGNAL IDUNA’s case closure rate increased by approximately 24 percentage points, rising from 73% to almost 98%.

Learn from us: “We’ve pioneered to unlock the power of human-AI collaboration: To redefine process efficiency by bringing together technology and subject matter experts to deliver exceptional customer experiences.” – Johannes Rath, board member for Customer, Service, and Transformation at SIGNAL IDUNA

NURO drives AI-powered insights with AlloyDB

Who: Nuro’s motto is “Autonomy for all. All roads, all rides.” The Silicon Valley-based startup is building an AI-powered Nuro Driver mobility platform, which is designed to be open to automotive and mobility companies.

What they did: Nuro needed a data platform that could handle complex data processes and support continuous AI model improvement. By migrating to AlloyDB for PostgreSQL, the company gained the scalability, high performance, and advanced query capabilities needed to power AI-driven insights that could manage real-world situations across millions of data points, while also reducing operating costs.

Why it matters: Since migrating to AlloyDB AI, Nuro has seen a substantial reduction in the operational costs of storing and searching embeddings. With ScaNN indexing, searches now yield more than 20,000 high-precision results in seconds, outperforming alternative indexing methods like IVF and HNSW in both quality and scalability.

Learn from us: “Our partnership with Google Cloud has also been invaluable. We have continuous access to innovations from the Google Cloud team, and we can easily meet any database requirement by leveraging their extensive suite of products. This support has accelerated our development, enabling us to focus on what matters most — advancing autonomous technology.” – Fei Meng, Head of Data Platform, Nuro

Mars Wrigley’s agile media experiments

Who: For more than a century, Mars Wrigley has made some of the world’s most popular candies and other consumer products. One way it maintains this status is through technology-driven advertising and marketing

What they did: By combining data in BigQuery and using built-in data science tools like BQML, Mars Wrigley can now better understand how specific audience targeting strategies in its media investments are driving incremental sales lift across key customer groups. Mars Wrigley then used Cortex Framework to gain instant insights through predefined and customizable analytics content as well as seamless integration with major media platforms like Google Ads, YouTube, TikTok, Meta, and more.

Why it matters: By embracing Cortex Framework, Mars Wrigley is not only gaining a clearer understanding of media impact on sales but also paving the way for a more data-driven and agile approach to marketing in the consumer packaged goods industry. This includes the ability to execute agile hypothesis testing, scalability to match media investments, and greater versatility to test media formats, content variations, shopper media, and more.

Learn from us: “Before, we were struggling to get an accurate in-flight view of our audiences’ performance. With Google Cloud Cortex Framework, we realized that the answer was within our internal data. We partnered with EPAM Systems to harness the synergy of our internal data sources, enabling us to run timely experimentation based on actual sales lift.” – Lía Inoa Pimentel, Senior Global Manager, Brand Experience & Media Measurement, Mars Wrigley

What’s new with Google Cloud - 2024

Tue, 31 Dec 2024 17:00:00 +0000

Week of Dec 16 - Dec 20

Windows Server 2025 is now available on Google Compute Engine. We are excited to announce the general availability of Windows Server 2025 on Google Compute Engine. You can now run Windows Server 2025 Data Center, and Windows Server 2025 Data Center Core editions as well as Windows SQL Server 2022 on Windows Server 2025 with pay-as-you-go licenses. Customers that don’t already have a Microsoft Enterprise Agreement can use the Google Compute Engine’s provided image to take advantage of Google Cloud’s relationships with Microsoft for pay-as-you-go licenses that scale with your workload and offers premium support.
Google Agentspace is here: unlock enterprise expertise for employees with agents that bring together Gemini’s advanced reasoning, Google-quality search, and enterprise data, regardless of where it’s hosted. Google Agentspace makes your employees highly productive by helping them accomplish complex tasks that require planning, research, content generation, and actions – all with a single prompt.

Week of Dec 9 - Dec 13

Best of N: Generating High-Quality Grounded Answers with Multiple Drafts. We are excited to announce that Check Grounding API has released a new helpfulness score feature. Building on top of our existing groundedness score, we now enable users to implement Best of N to improve RAG response quality without requiring extensive model retraining!
A3 Ultra VMs powered by NVIDIA H200 Tensor Core GPUs and Hypercompute Clusters are in preview. A3 Ultra VMs offer a significant leap in performance over previous generations. Coupled with Hypercompute Cluster, which the infrastructure and workload provisioning, and ongoing operations of AI supercomputers up to tens of thousands of accelerators is seamless. This delivers a easy to manage, secure and high-performance cloud experience for AI workloads. Learn more about the offering!

Week of Nov 25 - Nov 29

The Cyber Threat Intelligence Program Design Playbook, Now Available. Mandiant Academy published a new on-demand course, Cyber Threat Intelligence (CTI) Program Design Playbook. Comprised of three 2-hour courses, this learning track explains Mandiant’s approach to design and build, efficiently operate, and enhance a CTI program. This is the inaugural track from the Academy’s updated approach to on-demand learning with succinct, operations-oriented lessons designed to provide the world’s cybersecurity professionals the answers and resources they need to succeed.

Week of Nov 11 - Nov 15

Subsea cable connectivity is coming to Tuvalu for the first time with the addition of the Tuvalu Vaka cable. Building on the Bulikula subsea cable system announced last year, this new network infrastructure is a collaboration among several partners including Australia, Japan, New Zealand, Taiwan, Tuvalu, Tuvalu Telecommunications Corporation and the United States, and will help reduce the digital divide in the Pacific.

Week of Nov 4-8

We are excited to announce the reCAPTCHA Password Leak Detection Container App, a new tool that makes it easier than ever to protect your users from account takeovers. This container app simplifies the integration of reCAPTCHA's powerful password leak detection, allowing you to instantly detect compromised credentials and proactively prompt users to change their password before their account is compromised. With pre-built libraries and a streamlined process, you can significantly reduce integration time and enhance your website's security with ease.

Week of Oct 21-25

We're excited to announce GA support for scanning: Rocky Linux, Alma, SUSE (SLES), Red Hat (UBI), Chainguard, Wolfi & Google Distroless. These operating systems are now supported in both Artifact Registry scanning, as well as On Demand Scanning.
When the Container Scanning API is enabled, any container with these new operating systems or distroless images will automatically be scanned for vulnerabilities when pushed to Artifact Registry. We've also upgraded our On Demand scan to include; NPM, Python, Ruby, Rust, .Net & PHP language packages. See all supported package types.
Term Extension Now Available for Compute Engine Committed Use Discounts: You can now extend the term length of your Compute Engine resource-based Committed Use Discounts (“CUDs”) beyond the preset 1-year and 3-year options. CUDs offer significant cost savings for predictable workloads. You can now choose a CUDs term length beyond the original commitment end date that perfectly aligns with your workload needs, from one year and one day up to 6 years. Learn more

Week of Oct 14-18

Announcing Google Cloud Marketplace private offer enhancements that enable additional payment flexibility for enterprises, including when transacting generative AI models.

Week of Oct 7-11

We are excited to announce the launch of new Google Cloud Cortex Framework data integration and analytics solution content for BigQuery and Looker with Oracle EBS data. To learn more read our announcement blog.
Google Cloud is partnering with leading AI and cybersecurity startups to accelerate their growth and innovation, through the ISV Startup Springboard program, announced this week at the Google Cloud Startup Summit. Learn more and register interest.
Privileged Access Manager (PAM) is now Generally Available. The GA release offers new capabilities in addition to recently released public preview and includes features such as Pub/Sub integration for custom alerting and monitoring, alerts on IAM grant modifications outside of PAM, and integration with VPC Service Controls to tackle data exfiltration. Learn more.

Week of Sept 23-27

We are excited to announce that registration is open for the App Dev & Infrastructure Summit on October 30 (AMER) and October 31 (EMEA). Google Technology Fellows - our luminary technical leaders - and industry experts will share strategies and learnings on how to improve efficiency, reduce costs, and speed up AI innovation for your cloud and application infrastructure at this global digital event. Register here.

Week of Sept 16-20

Starting this week, Google Cloud customers with eligible support plans can access assistance for the Cluster Toolkit through the Cloud Console. Cluster Toolkit, formerly known as Cloud HPC Toolkit, is open-source software offered by Google Cloud which simplifies the process for you to deploy HPC, AI and ML workloads on Google Cloud. The Cloud Support team will handle filed cases, ensuring that users receive timely and effective support for their Cluster Toolkit implementations. Select 'Cluster Toolkit' as the sub-category under 'Compute Engine' when creating a support ticket in your Cloud Console to get in touch about any Cluster Toolkit issues.
Backup and DR service is excited to announce the public preview of backup vaults and simplified VM backup offering. Backup vaults provide secure backups for cyber resilience through immutable and indelible backups for VMs and databases, delivering security against accidental or malicious data deletion. Simplified Compute Engine VM backup with a fully-managed experience, directly integrated into the cloud console makes backing of VMs as easy as 1-2-3. The solution also enables backup admins to empower application developers to self-protect their VMs while retaining centralized governance and oversight. Read the full blog to learn more and try out the new features.

Week of Sept 2-6

We’re excited to share that Topaz will be extended to Taiwan. Announced in 2022, the transpacific subsea cable system was the first to connect Canada and Japan. Now, with the extension of Topaz to Taiwan, we’ll provide the region with increased reliability and resilience for network operators, for Google, and for users.

Week of Aug 26-30

We are excited to announce the general availability of Instant snapshots for Google Compute Engine Persistent Disks, which provide near-instantaneous, high-frequency, point-in-time checkpoints of a disk that can be rapidly restored as needed. Read the full blog to try it out.
In response to customer and partner requests for pollen data in Japan, we are excited to announce that data for Japanese Cedar and Cypress trees-the 2 main sources of pollen allergens in Japan-have been added to our Pollen API from Google Maps Platform.

Week of Aug 19-23

We are excited to announce we’re adding support for NVIDIA L4 GPUs to Cloud Run, in preview. Developers love Cloud Run for its simplicity, fast autoscaling, scale-to-zero capabilities, and pay-per-use pricing. Those same benefits come into play for real-time inference apps serving open gen AI models. Check out this launch blog. Also watch demos from this launch event webinar Run AI on Cloud run.
We are excited to announce that Google Cloud Functions is now Cloud Run functions — event-driven programming in one unified serverless platform. This goes beyond a simple name change. We’ve unified the Cloud Functions infrastructure with Cloud Run, and developers of Cloud Functions (2nd gen) get immediate access to all new Cloud Run features, including NVIDIA GPUs. Read the launch blog and watch demos from this launch event webinar Run AI on Cloud run.

Week of Aug 5-9

Google’s Workforce Identity federation now enables Microsoft Entra ID users to access Google BigQuery from Microsoft Power BI with Single-Sign-On. No users or groups need to be provisioned in Google Cloud as Workforce identity Federation leverages a syncless federation capability using attribute based access control to authorize access to Google BigQuery using Microsoft Entra user attributes such as user group membership. You can refer to our documentation to learn more.
We are excited to announce the preview of SQL support in Bigtable to bring Google’s pioneering NoSQL database to a broader developer audience. Bigtable leverages GoogleSQL ─the same SQL dialect used by BigQuery─ making it easier to use Bigtable as low-latency analytics serving layer in combination with BigQuery’s newly announced continuous queries but does so with extensions to support its signature data model so you can use SQL without giving up on all the flexibility that comes with a NoSQL database. It also simplifies migrations from open source databases such as Apache Cassandra. With over 100 new functions from JSON processing capabilities, kNN for GenAI and HLL for real-time analytics, SQL opens the door to many new possibilities with Bigtable. Learn more in our detailed blog post.
We are excited to announce the public preview of BigQuery continuous queries, a groundbreaking new feature that empowers users to run continuously processing SQL statements that can process, analyze, and transform data as new events arrive in BigQuery, ensuring insights are always up to date. Native integration with the Google Cloud ecosystem unlocks the ability of Vertex AI and Gemini to perform machine learning inference on incoming data in real time. As well as streaming replication of continuous query results to Pub/Sub topics, Bigtable instances, or other BigQuery tables. Read the full blog and try it out!
AlloyDB’s AutoPilot capabilities- Automatic memory management, Adaptive AutoVacuum, Automatic storage tiering ,Automatic data columnarization and query rewrite- makes management super efficient and easy. AlloyDB eliminates the drudgery of maintaining a PostgreSQL database by using, behind the scenes , advanced self-tuning machine learning algorithm. In this blog we will look into a real world example of AlloyDB Adaptive AutoVacuum in work and how AlloyDB Cluster Storage Space is Released
Google Cloud Identity Platform, our consumer identity solution, now supports Passkeys. With Passkeys, developers can authenticate their app's end users securely, protecting them from account takeover attacks like phishing and leaked credentials. To join the private preview, contact your Google account team.

Week of July 15-19

Google Cloud is excited to launch the Modern SecOps Masterclass, now available on Coursera. This course equips security professionals with cutting-edge skills to modernize their Security Operations Centers (SOCs) using our Autonomic Security Operations framework and Continuous Detection, Continuous Response (CD/CR) methodology. Read the full blog and enroll now.
Learn how to potentially achieve a strong consistency in Cloud Bigtable for your next big data solution. Bigtable offers high throughput at low latency. It is ideal for storing large amounts of data in a key-value store while supporting high read and write throughput at low latency for fast access. Bigtable provides eventual consistency as well as strong consistency. This blog talks about achieving strong data consistency in a multi-cluster Bigtable instance. Read the full blog.

Week of June 24-28

Introducing Google Cloud Marketplace Channel Private Offers, enabling customers, ISV partners, and channel partners to efficiently transact private offers via reseller-initiated sales of third-party solutions listed on the Google Cloud Marketplace. This differentiated program also empowers channel partners to manage the customer relationship from billing, collections to revenue recognition. Read the full blog.
A blog on benchmark study (collaborated with Yahoo) by comparing the cost and performance of Apache Flink and Google Cloud Dataflow for two specific streaming data processing use cases. The goal of the study was to determine the most cost-effective platform for these use cases by establishing a fair comparison methodology and controlling variables such as throughput and workload. The results indicate that, with some optimization on Dataflow can perform on-par with Apache Flink. Read the full blog.
A Blog on Secure Gateways: Mutual TLS for Ingress Gateway Secure Gateways: Mutual TLS for Ingress Gateway," discusses the implementation of mutual TLS (mTLS) for enhanced security in ingress gateways. It explains how mTLS ensures both client and server authentication through certificates, going beyond the traditional server-only verification. The article explores the setup process and the benefits of using mTLS, emphasizing its role in establishing secure communication channels in modern cloud architectures. Read the full blog.
A Blog on Wildcard certificates with Ingress Gateway "Wildcard certificates with Ingress Gateway" provides a guide on how to use wildcard certificates to secure multiple services behind a single Istio Ingress Gateway. This simplifies certificate management and improves the user experience by allowing seamless connections across different services within the same domain. The article demonstrates the configuration process step-by-step and explains how wildcard certificates are matched to incoming requests. Read the full blog

Week of June 17-21

Learn how to leverage BigQuery vector search to analyze your logs and asset metadata stored in BigQuery. Using vector search, you can find semantically similar logs which can be helpful in several use cases such as outlier detection, triage and investigation. This how-to blog walks you through the setup from processing logs, generating vector embeddings, to analyzing vector search results. It includes sample SQL queries which can be adapted for your own logs and use case. Read the full blog.
Nuvem, first announced last year, is a transatlantic subsea cable system that will connect Portugal, Bermuda, and the United States. We are now working with the Regional Government of Azores to enable extending the system to the Azores as well. Named after the Portuguese word for “cloud,” Nuvem will improve network resiliency across the Atlantic, helping meet growing demand for digital services and further establishing its landing locations as digital hubs.

Week of June 10-14

General Availability of A3 Mega, a new instance type in the A3 VM family. A3 Mega is powered by the NVIDIA H100 Tensor Core GPU, delivers a 2.4x improvement in large scale training performance over multiple A3 instances.
- 2x the GPU-to-GPU networking bandwidth over A3 Instances.
- Enhanced GPUDirect-TCPXO networking offloads GPUDirect memory access from the CPU, providing direct access through through the NIC (Network Interface Card) to GPU memory, based on Titanium TOPs, which improves performance of multi-node distributed training workloads.
Simplify your Network: The Cloud Networking Product Management and Engineering team will be traveling across US cities in June/July and Sept. Learn how Cross-Cloud Network can transform your infrastructure. The workshop will address Cross-Cloud Networking for hybrid and multicloud enterprises with distributed applications, internet-facing content and applications, security, and AI-assisted network operations with Gemini Cloud Assist. Join us at one of the following Google office locations and meet the experts who will share the latest innovations, use cases, and demos. Register here.
Learn how you can leverage the cloud deployment archetypes (zonal, regional, multi-regional, global, hybrid, & multicloud) to architect cloud topologies that meet your workload’s requirements for reliability, cost, performance, & operational simplicity. Read the full blog.

Week of May 20-24

Maximize performance and optimize spend with Compute Engine’s latest General Purpose VMs, N4 and C4. N4's flexible configurations and price-performance gains help optimize costs, while C4 provides top-tier performance for demanding applications. With N4 and C4, you get tailored solutions for all your general-purpose workloads, so you can lower the total cost of running your business without compromising on performance or workload-specific requirements. Learn more here.

Week of Apr 22 - April 26

Simplify your connectivity to Google by using a Verified Peering Provider to connect to Google, instead of using Direct Peering. Verified Peering Providers handle all of the complex connectivity allowing you to focus on your core business. Learn more here.

Week of Apr 15- Apr 19

New training in AI, data analytics and cybersecurity, designed to expand onramps to tech careers through colleges and employers. Learn more.

Week of Apr 1- Apr 5

Security Command Center (SCC) Enterprise is now generally available (GA). It is the industry’s first cloud risk management solution that converges cloud security and enterprise security operations into a single platform, supercharged by Mandiant expertise and AI. Learn more in our announcement blog.
Identify common container runtime attacks, analyzes suspicious code, and use natural language processing to pinpoint malicious scripts with GKE threat detection, powered by Security Command Center. Now in public preview.
Get a fully managed compliance service that automatically delivers end-to-end coverage for GKE, scanning for issues against the most important benchmarks with GKE compliance, now in public preview. Near-real-time insights are available in a centralized dashboard, with compliance reports automatically produced for you.
Streamline your GCE backup strategy! With tag-based backups in Google Backup and DR, protection is automated – new VMs with the right tags are protected immediately, saving you time and increasing reliability. Read more on the blog here. Differential privacy enforcement with privacy budgeting is now available in BigQuery data clean rooms so organizations can prevent data from being reidentified when it is shared.

Week of Mar 18- Mar 22

Google Kubernetes Engine (GKE) and NVIDIA NeMo framework are used to train large language models (LLMs). Due to the increasing demand for efficient and scalable training of LLMs, the need for GPUs at a large scale with high speed networking is rapidly growing. GKE offers a comprehensive set of features that make it suitable for enterprise-level training and inference. This blog post shows how generative AI models can be adapted to your use cases by demonstrating how to train models on Google Kubernetes Engine (GKE) using the NVIDIA NeMo framework.
Cloud Run now supports volume mounts! Mount a Cloud Storage bucket or NFS file share as a volume to easily serve static assets, access app configuration data, or access an AI/ML model. Learn more in our blog post.

Week of Mar 11- Mar 15

Datastream adds support for SQL Server sources, now in preview. With existing support for MySQL, PostgreSQL, and Oracle, support for SQL Server sources extends the reach of Datastream and empowers you to replicate data from a range of relational sources to several Google Cloud services, such as BigQuery, Cloud Storage, AlloyDB, and Spanner. Read more in the blog here.

Week of Feb 5- Feb 9

Check out this new blog and learn more about the Integrated Commerce Network (ICN) delivered by Kin + Carta and built on Google Cloud. The ICN features 3 of our premier digital commerce partners for an integrated end-to-end solution including Bloomreach, commercetools and Quantum Metric.

Week of Jan 29- Feb 2

IDC finds 318% ROI from migrating to Google Cloud IaaS: Check out the latest IDC research study to learn how organizations worldwide are benefitting by adopting Google Cloud Infrastructure as a Service.

Week of Jan 15-19

Check out the latest generative AI training available from Google Cloud : Take a look at our top ten trainings in Duet AI to help boost your productivity in 2024.

Week of Jan 1-5

The year in Google Cloud: Top news of 2023: A look back at the biggest stories of 2023 from Google Cloud, covering generative AI, DevOps, containers, data and databases, security, and more.

The Year in Google Cloud - 2024

Fri, 20 Dec 2024 17:00:00 +0000

If you’re a regular reader of this blog, you know that 2024 was a busy year for Google Cloud. From AI to Zero Trust, and everything in between, here’s a chronological recap of our top blogs of 2024, according to readership. You’ll probably see some favorites on this list, and discover a few that you missed the first time around.

January

We started the new year strong, removing data transfer fees for anyone moving data off of our platform. Translation: Anyone doing cool things on Google Cloud (like using generative AI to analyze their microservices deployment) is doing it because they want to, not because they have to. And in business news, we shared how to make the most out of your data and AI in the coming year.

February

From local GPUs, to model libraries, to distributed system design, the second month of 2024 was the first of many to come where AI topics dominated the charts. Our Transform team explored gen AI’s impact on various industries.

March

If it wasn’t already obvious, this month’s top-read blogs showed that our core audience is developers pushing the boundaries of innovation. Business leaders, meanwhile, read about best practices for securely deploying AI on Google Cloud.

April

Watch out, here comes Google Cloud Next, where we made a record 218 announcements; the top three are listed here. Readers were also keen to hear about how Citadel Securities built out a research platform on Google Cloud.

May

We don’t always get it right, but when there’s a problem, we’re committed to providing you with accurate, timely information with which to make your own assessments. We’re also committed to making you, and customers like McLaren Racing, go really, really fast when developing new AI-based applications.

June

Whether you wanted to modernize your databases, deliver higher system reliability, create really cool AI-powered apps, or learn how legendary companies tackle data management, the Google Cloud blog was your go-to source midway through the year.

July

We talk a lot about “meeting customers where they are.” Sometimes that means a disaster zone, a remote research station, or a truck cruising down the highway. Over on Transform, you read about the history of our custom Axion and TPU chips.

August

Just when you thought you knew how to run AI inference, your available graph database options, or the name of Google Cloud’s event-driven programming service, we went and changed things up. We like to keep you on your toes ;) And business readers got a first look at AI agents — more to come on this.

September

You’ve been generating (and storing) business data for years. Now, we’re making it easier for you to make sense of, and actually use, that data. Speaking of using data, the Transform team compiled a jaw-dropping list of the real-world ways customers are using gen AI in their organizations.

October

According to this month’s most-read blog, 75% of you rely on AI for at least one daily professional responsibility, including code writing, information summarization, and code explanation, and experience “moderate” to “extreme” productivity gains. So it was no big surprise that business leaders wanted to read about how to develop an AI strategy.

November

Not content to hold the existing record for most nodes in a Kubernetes cluster (15,000), we went ahead and more than quadrupled it, to the delight of AI unicorns. But whether you work for an AI unicorn, or just a plain old zebra, all Google Cloud users needs to start using multi-factor authentication next year, as well as learn how to avoid comman AI pitfalls.

December

We’re closing out the year on an AI highnote, with the availability of amazing new image and video generation models, as well as the new Trillium TPU, which Google used to train Gemini 2.0, our most capable AI model… yet. Be on the lookout for how these technologies — and many others — will reshape your industry and how you work in the coming year.

To all our loyal readers and customers, thanks for an amazing 2024, and here’s to an even more exciting and productive 2025!

Bringing the best of Google Cloud to the Public Sector

Thu, 03 Oct 2024 16:00:00 +0000

Over the past year, the pace of innovation across industries and around the world has been extraordinary. At Google, we're inspired by the public sector’s ingenuity and speed in adopting our AI and security innovations to achieve remarkable outcomes together.

Since Google Cloud Next, we've launched more powerful versions of Gemini, rolled out Gemini Flash and Imagen 3. And we're proud to showcase inspiring examples from the public sector, highlighting how organizations are leveraging generative AI to drive transformative change. From state agencies streamlining citizen services to healthcare providers improving patient outcomes and defense organizations enhancing mission readiness, public sector organizations are embracing generative AI to drive meaningful impact and achieve their missions.

Bringing the best of AI and security to the public sector

We continue to demonstrate our commitment to pushing the boundaries of AI and security. For example, at our recent Gemini at Work event, we showcased how AI agents are transforming how organizations operate — from enhancing customer experiences to streamlining workflows and strengthening security. In the public sector, these capabilities can improve citizen services, empower government employees, and drive data-driven decision-making for greater efficiency and mission impact. At our recent mWISE 2024 event, we emphasized the critical role of collaboration in cybersecurity. Our new offerings like Managed Defense for Google Security Operations and Private Collection Sharing in Google Threat Intelligence equip agency leaders with the tools and insights to stay ahead of evolving threats.

Accelerating mission and impact

AI is not just about futuristic possibilities; it's about real-world impact, today. In the public sector, we're seeing incredible examples of how AI is being used to accelerate missions and serve communities better:

Inclusivity and accessibility: The City of Dearborn, Michigan, is harnessing the power of our AI/ML tools to implement a 24/7 multilingual virtual agent. By providing translated information and support, Dearborn is ensuring that its diverse community of over 100,000 residents has equal access to essential services.
Mission-critical efficiency: The Air Force Rapid Sustainment Office is revolutionizing aircraft maintenance with Google Cloud Apigee API and Google Distributed Cloud. This powerful combination enhances readiness, optimizes resource allocation, and streamlines data storage, ultimately saving billions of dollars and ensuring our Air Force is always prepared.

We're helping empower organizations like Dearborn, Michigan and the Air Force Rapid Sustainment Office to accelerate their missions and impact.

Choosing the right partner matters

We continue to invest in our platform and portfolio for the public sector, driven by key tenets including ease of use, secure by design, and flexible for your needs. This aligns to our enterprise vision for the public sector, which is to deliver end-to-end IT services around the world as a global platform — with cloud platforms that cover every classification level and operating environment and our global network that connects them together. We deliver the AI, data analytics, and cybersecurity solutions that you want from Google in a secure and reliable way to transform your IT strategy.

We continuously strive to deliver innovative technologies that enable the public sector to achieve more. Gone are the days of a legacy approach to security that emphasized the use of government-only infrastructure, which was less secure with fewer features and limited functionality. The modernized FedRAMP memo and new framework validates Google Cloud’s approach of certifying our entire commercial cloud for public sector use, and we are on our path to achieving this. This guidance highlights an important shift in how federal leaders harness the power of commercial cloud technologies to transform government services.

Join us at the Google Public Sector Summit

On October 16th in Washington D.C., immerse yourself in the latest AI and security innovations from Google Cloud. Don’t miss this opportunity to hear from agency leaders and Google Cloud experts across a range of sessions:

Fireside Chat with Thomas Kurian, CEO of Google Cloud, and Karen Dahut, CEO of Google Public Sector.
AI and Security panel with Kevin Mandia, Strategic Advisor, Google Cloud & Google Public Sector Board Member.
Keynote on Data, Infrastructure and unlocking AI's potential in the Public Sector, led by Sachin Gupta, VP/GM, Infrastructure & Solutions Group, Google Cloud.
Fireside Chat on security's role in transformation and mission impact, with MK Palmore, Director, Office of the CISO, Google Cloud.

And so much more. Register today to attend our Public Sector Summit on October 16th in Washington D.C.

Google Cloud files complaint with European Commission regarding Microsoft’s anti-competitive licensing practices

Wed, 25 Sep 2024 12:00:00 +0000

Editors note, November 28th, 2025: “We filed our antitrust complaint with the European Commission (EC) to give voice to our customers and partners about the issue of anticompetitive cloud licensing practices. Today, we are withdrawing it in light of the recent announcement that the EC will assess problematic practices affecting the cloud sector under a separate process. We stand behind the arguments outlined in the blog below, and we continue to work with policymakers, customers, and regulators across the EU, the UK, and elsewhere to advocate for choice and openness in the cloud market." - Giorgia Abeltino, Head of Government Affairs & Public Policy, Google Cloud Europe

Cloud-based computing is one of the most important developments in the European economy over the last decade. Moving to the cloud has reduced costs, delivered services with incredible reach, and laid the foundation for entirely new European companies. But legacy licensing practices that force customers onto a single vendor threaten Europe’s ability to take full advantage of this opportunity.

For years, in the productivity software space, Microsoft has locked customers into Teams, even when they preferred other providers. Now, the company is running the same playbook to push companies to Azure, its cloud platform. Microsoft’s licensing terms restrict European customers from moving their current Microsoft workloads to competitors’ clouds – despite there being no technical barriers to doing so – or impose what Microsoft admits is a striking 400% price markup.

Microsoft is the only cloud provider to use these tactics, which have significantly harmed European companies and governments. Not only have they cost European businesses at least €1 billion a year, but also they have led to adverse downstream effects, including waste of tax funds, stifled competition, restrictions on distributors and channel partners, and heightened risk for organizations exposed to Microsoft’s “inadequate” security culture.

Like many others, we have attempted to engage directly with Microsoft. We have kicked off an industry dialogue on fair and open cloud licensing. And we have advocated on behalf of European customers and partners who fear retaliation in the form of audits or worse if they speak up. Unfortunately, instead of changing its practices, Microsoft has struck one-off deals with a small group of companies.

To give voice to the complaints we hear from customers – and from across the industry – and to seek a resolution that will benefit everyone, we are now taking the next step of filing a formal complaint with the European Commission.

How Microsoft’s anticompetitive licensing practices work

While Microsoft’s licensing practices apply to many enterprise products, Windows Server is central to the company’s strategy of locking customers into Azure. Windows Server is a must-have workhorse in many IT environments, serving as the backbone for applications, files, and services. And it has already added billions of dollars to Microsoft’s revenues. When businesses and governments originally paid for Windows Server licenses, they had the right to run them on any hardware they wished – and did so for many years on machines from HP, Dell, Lenovo, and others.

However, as cloud computing took off and promised to bring new benefits to European businesses, customers wanted to move their previously purchased licenses to other cloud providers, and in some cases to multiple clouds, to provide additional resiliency and security. Initially, Microsoft allowed them to do this. But as Azure faced more competition, Microsoft introduced new rules that severely limited customer choice.

One of the most significant restrictions occurred in 2019, when Microsoft adopted new licensing terms that imposed extreme financial penalties on businesses wanting to use Windows Server software on Azure’s closest competitors, such as Google Cloud and AWS. Microsoft’s own statements indicate that customers who want to move their workloads to these competitors would need to pay up to five times more. And for those who choose to keep running Windows Server on competitors’ cloud platforms (despite the cost difference), Microsoft introduced additional obstacles over the last few years, such as limiting security patches and creating other interoperability barriers.

Harm to European customers, vendors, and cloud markets

According to research from Professor Frédéric Jenny, a French economist and chairman of the OECD Competition Committee, EU customers face significant hidden costs due to Microsoft’s restrictive licensing that go well beyond inflated pricing. These include taxpayer waste, money diverted from investments in growth, and slower digital transformations. We have heard many of these same complaints from customers.

Restrictive licensing also stifles innovation and competition, preventing European companies from using multiple clouds, including European cloud providers. According to one recent study, after the 2019 licensing changes, Microsoft’s cloud market share suddenly skyrocketed, largely at the expense of European providers.

Security and reliability suffer too. As highlighted by the massive security outage two months ago, Microsoft’s lock-in tactics can result in a single point of failure that harms businesses, industries, and governments. Without diversity in vendors, cyber attacks become more frequent. Research from Prescient finds that anticompetitive licensing leads to higher cyber-insurance premiums, incident response costs, and cloud service costs.

Importance of fair and open licensing

Google Cloud’s approach is different. We promote fair and transparent licensing for our customers. We pioneered a multi-cloud infrastructure service and a multi-cloud data warehouse, enabling workloads to run across multiple clouds. And we were the first company to provide digital sovereignty solutions for European governments and to waive exit fees for customers wishing to switch cloud providers.

Our point is a simple one: Restrictive cloud licensing practices hurt companies and impede European competitiveness. We look forward to continuing this discussion on how to keep the cloud market fair and open for European businesses and governments.

What’s new with Google Cloud - 2023

Sun, 31 Dec 2023 17:00:00 +0000

Want to know the latest from Google Cloud? Find it here in one handy location. Check back regularly for our newest updates, announcements, resources, events, learning opportunities, and more.

Tip: Not sure where to find what you’re looking for on the Google Cloud blog? Start here: Google Cloud blog 101: Full list of topics, links, and resources.

Week of Dec 10 - Dec 15

Announcing Launch of Cross Cloud Materialized Views: To help customers on their cross-cloud analytics journey, today we are thrilled to announce the public preview of BigQuery Omni cross-cloud materialized views (aka cross-cloud MVs). Cross-cloud MVs allow customers to very easily create a summary materialized view on GCP from base data assets available on another cloud. Cross-cloud MVs are automatically and incrementally maintained as base tables change, meaning only a minimal data transfer is necessary to keep the materialized view on GCP in sync. The result is an industry-first capability that empowers customers to perform frictionless, efficient, and cost-effective cross-cloud analytics

Week of Nov 27 - Dec 1

Google Cloud Global Cloud Service Provider of the Year. Google Cloud is thrilled to be recognized as Palo Alto Networks 2023 Global Cloud Service Provider of the Year and Global Cortex Partner of the Year. Google Cloud and Palo Alto Networks are dedicated to working together to support customer cloud journeys with an array of jointly engineered and integrated security solutions that enable digital innovation with ease. Read the Palo Alto Networks blog.
GKE Enterprise edition free trial: We have announced the general availability of GKE Enterprise, the premium edition of Google Kubernetes Engine (GKE) recently. With GKE Enterprise, companies can increase velocity across multiple teams, easily and securely run their most important business-critical apps and the latest AI/ML workloads safely at scale with a fully integrated and managed solution from Google Cloud. Start the 90-day free trial today with the GKE Enterprise edition by going to the GKE console and clicking on the “Learn about GKE Enterprise” button.
In our new blog post on Cost Management in BigQuery, you'll learn how to use budgets and custom quota to help you stay on top of your spending and prevent surprises on your cloud bill. The interactive tutorials linked in the article will help you set them up for your own Google Cloud projects in no time!
Leverage the transformative power of generative AI to elevate your customer service. Discover how you can optimize ROI, enhance customer satisfaction, and revolutionize your contact center operations with Google’s latest conversational AI offerings in this new blog.

Week of Nov 13 - Nov 17

In the first of our new Sketchnote series on Cloud FinOps, Erik and Pathik dive into what Cloud FinOps is, and how it can help your organization optimize its cloud budget.

Week of Oct 30 - Nov 3

Join Google Cloud’s product management leadership for a Data Analytics Innovation Roadmap session on November 13th. In this session, we will go through recent innovations, strategy and plans for BigQuery, Streaming Analytics, Data Lakes, Data Integration, and GenAI. This session will give you insight into Google’s feature development and will help your team plan your data analytics strategy.
Hear from Google Cloud experts on modernizing software delivery with generative AI, running AI/ML workloads on GKE, the future of AI-infused apps, and more at Digital Transform: the future of AI-powered apps, November 15th.
Vertex AI Search: Read about exciting new generative AI features coming to Vertex AI Search our platform to create search based applications for your business. Vertex AI Search provides customers with a tunable Retrieval Augmented Generation (RAG) system for information discovery. Learn more in this blog.
Vector similarity search: If you are looking to build an an e ecommerce recommendations engine or ad serving or other DIY application based on ANN aka vector similarity search dive into our vector search capability which is a part of the Vertex AI Search platform. We’ve expanded features and made it easier then ever for developers to get started building their apps.
Cloud Deploy - Deploy hooks (GA) allow users to specify and execute pre- and post- deploy actions using Cloud Deploy. This allows customers to run infrastructure deployment, database schema updates, and other activities immediately before a deploy job, and cleanup operations as part of a post (successful) deploy job. Learn More
Cloud Deploy - Cloud Deploy now uses Skaffold 2.8 as the default Skaffold version for all target types. Learn More
Artifact Registry - Artifact Registry remote repositories are now generally available (GA). Remote repositories store artifacts from external sources such as Docker Hub or PyPI. A remote repository acts as a proxy for the external source so that you have more control over your external dependencies. Learn More
Artifact Registry - Artifact Registry virtual repositories are now generally available (GA). Virtual repositories act as a single access point to download, install, or deploy artifacts in the same format from one or more upstream repositories. Learn More

Week of Oct 2 - Oct 6

ABAP SDK for Google Cloud now supports 40+ more APIs, an additional authentication mechanism and enhanced developer productivity for SAP ABAP developers. Learn more in this blog post.

Week of Sep 25 - Sep 29

Our newly published Storage decision tree helps you research and select the storage services in Google Cloud that best match your specific workload needs and the accompanying blog provides an overview of the services offered for block storage, object storage, NFS and Multi-Writer file storage, SMB storage, and storage for data lakes and data warehouses.

Week of Sep 18- Sep 22

Meet the inaugural cohort of the Google for Startups Accelerator: AI First program featuring groundbreaking businesses from eight countries across Europe and Israel using AI and ML to solve complex problems. Learn how Google Cloud empowers these startups and check out the selected ventures here.
BigQuery is introducing new SQL capabilities for improved analytics flexibility, data quality and security. Some examples include schema support for Flexible column name, Authorized store proceduces, ANY_VALUE (HAVING) also known as MAX_BY and MIN_BY and many more. Check out full details here.
Cloud Logging is introducing to Preview the ability to save charts from Cloud Logging’s Log Analytics to a custom dashboard in Cloud Monitoring. Viewing, copying and sharing the dashboards are supported in Preview. For more information, see Save a chart to a custom dashboard.
Cloud Logging now supports customizable dashboards in its Logs Dashboard. Now you, can add your own charts to see what’s most valuable to you on the Logs Dashboard. Learn more here.
Cloud Logging launches several usability features for effective troubleshooting. Learn more in this blog post.
Search your logs by service name with the new option in Cloud Logging. Now you can use the Log fields to select by service which makes it easier to quickly find your Kubernetes container logs. Check out the details here.
Community Security Analytics (CSA) can now be deployed via Dataform to help you analyze your Google Cloud security logs. Dataform simplifies deploying and operating CSA on BigQuery, with significant performance gains and cost savings. Learn more why and how to deploy CSA with Dataform in this blog post.
Dataplex data profiling and AutoDQ are powerful new features that can help organizations to improve their data quality and build more accurate and reliable insights and models. These features and now Generally Available. Read more in this blog post.

Week of Sep 4 - Sep 8

Introducing Looker’s Machine Learning Accelerator. This easy to install extension allows business users to train, evaluate, and predict with machine learning models right in the Looker interface.
Learn about how Freestar has built a super low latency, globally distributed application powered by Memorystore and the Envoy proxy. This reference walks users through the finer details of architecture and configuration, that they can easily replicate for their own needs.

Week of Aug 28 - Sep 1

You can access comprehensive and up-to-date environmental information to develop sustainability solutions and help people adapt to the impacts of climate change through Google Maps Platform’s environment APIs. The Air Quality, and Solar APIs are generally available today. Get started or learn more in this blog post.
Google Cloud’s Global Partner Ecosystems & Channels team launched the Industry Value Networks (IVN) initiative at Google Cloud NEXT ’23. IVNs combine expertise and offerings from systems integrators (SIs), independent software vendors (ISVs) and content partners to create comprehensive, differentiated, repeatable, and high-value solutions that accelerate time-to-value and reduce risk for customers. To learn more about the IVN initiative, please see this blog post

Week of Aug 21 - Aug 25

You can now easily export data from Earth Engine into BigQuery with our new connector. This feature allows for improved workflows and new analyses that combine geospatial raster and tabular data. This is the first step in toward deeper interoperability between the two platforms, supporting innovations in geospatial sustainability analytics. Learn more in this blog post or join our session at Cloud Next.

Week of Aug 14 - Aug 18

You can now view your log query results as a chart in the Log Analytics page in Cloud Logging. With this new capability available in Preview, users can write a SQL filter and then use the charting configuration to build a chart. For more information, see Chart query results with Log Analytics.

Week of Aug 7 - Aug 11

You can now use Network Analyzer and Recommender API to query the IP address utilization of your GCP subnets, to identify subnets that might be full or oversized. Learn more in a dedicated blog post here.
Memorystore has introduced version support for Redis 7.0. Learn more about the included features and upgrade your instance today!

Week of July 31 - Aug 4

Attack Path Simulation is now generally available in Security Command Center Premium. This new threat prevention capability automatically analyzes a customer’s Google Cloud environment to discover attack pathways and generate attack exposure scores to prioritize security findings. Learn more. Get started now.

Week of July 24-28

Cloud Deploy has updated the UI with the ability to Create a Pipeline along with a Release. The feature is now GA. Read more
Our newly published Data & Analytics decision tree helps you select the services on Google Cloud that best match your data workloads needs, and the accompanying blog provides an overview of the services offered for data ingestion, processing, storage, governance, and orchestration.
Customer expectations from the ecommerce platforms are at all time high and they now demand a seamless shopping experience across platforms, channels and devices. Establishing a secure and user-friendly login platform can make it easier for users to self-identify and help retailers gain valuable insights into customer’s buying habits. Learn more about how they can better manage customer identities to support an engaging ecommerce user experience using Google Cloud Identity Platform.
Our latest Cloud Economics post just dropped, exploring how customers can benchmark their IT spending against peers to optimize investments. Comparing metrics like tech spend as a percentage of revenue and OpEx uncovers opportunities to increase efficiency and business impact. This data-driven approach is especially powerful for customers undergoing transformation.

Week of July 17-21

Cloud Deploy now supports deploy parameters. With deploy parameters you can pass parameters for your release, and those values are provided to the manifest or manifests before those manifests are applied to their respective target. A typical use for this would be to apply different values to manifests for different targets in a parallel deployment. Read more
Cloud Deploy is now listed among other Google Cloud services which can be configured to meet Data Residency Requirements. Read more
Log Analytics in Cloud Logging now supports most regions. Users can now upgrade buckets to use Log Analytics in Singapore, Montréal, London, Tel Aviv and Mumbai. Read more for the full list of support regions.

Week of July 10-14

Cloud CDN now supports private origin authentication in GA. This capability improves security by allowing only trusted connections to access the content on your private origins and preventing users from directly accessing it.
Workload Manager - Guided Deployment Automation is now available in Public Preview, with initial support for SAP solutions. Learn how to configure and deploy SAP workloads directly from a guided user interface, leveraging end-to-end automation built on Terraform and Ansible.
Artifact Registry - Artifact registry now supports clean up policies now in Preview. Cleanup policies help you manage artifacts by automatically deleting artifacts that you no longer need, while keeping artifacts that you want to store. Read more

Week of July 3-7

Cloud Run jobs now supports long-running jobs. A single Cloud Run jobs task can now run for up to 24 hours. Read More.
How Google Cloud NAT helped strengthen Macy’s security. Read more

Week of June 26-30

Cloud Deploy parallel deployment is now generally available. You can deploy to a target that's configured to represent multiple targets, and your application is deployed to those targets concurrently. Read More.
Cloud Deploy canary deployment strategy is now generally available. A canary deployment is a progressive rollout of an application that splits traffic between an already-deployed version and a new version. Read More

Week of June 19-23

Google Cloud’s Managed Service for Prometheus now supports Prometheus exemplars. Exemplars provide cross-signals correlation between your metrics and your traces so you can more easily pinpoint root cause issues surfaced in your monitoring operations.
Managing logs across your organization is now easier with the general availability of user-managed service accounts. You can now choose your own service account when sending logs to a log bucket in a different project.
Data Engineering and Analytics Day - Join Google Cloud experts on June 29th to learn about the latest data engineering trends and innovations, participate in hands-on labs, and learn best practices of Google Cloud’s data analytics tools. You will gain a deeper understanding of how to centralize, govern, secure, streamline, analyze, and use data for advanced use cases like ML processing and generative AI.

Week of June 5-9

TMI: Shifting Down, Not Left- The first post in our new modernization series, The Modernization Imperative. Here, Richard Seroter talks about the strategy of ‘shifting down’ and relying on managed services to relieve burdens on developers.
Cloud Econ 101: The first in a new series on optimizing cloud tools to achieve greater return on your cloud investments. Join us biweekly as we explore ways to streamline workloads, and explore successful cases of aligning technology goals to drive business value.
The Public Preview: of Frontend Mutual TLS Support on Global External HTTPS Load Balancing is now available. Now you can use Global External HTTPS Load Balancing to offload Mutual TLS authentication for your workloads. This includes client mTLS for Apigee X Northbound Traffic using Global HTTPS Load Balancer.
FinOps from the field: How to build a FinOps Roadmap - In a world where cloud services have become increasingly complex, how do you take advantage of the features, but without the nasty bill shock at the end? Learn how to build your own FinOps roadmap step by step, with helpful tips and tricks from FinOps workshops Google has completed with customers.
We are now offering up to $1M of financial protection to help cover the costs of undetected cryptomining attacks. This is a new program only for Security Command Center Premium customers. Security Command Center makes Google Cloud a safe place for your applications and data. Read about this new program in our blog.
Global External HTTP(S) Load Balancer and Cloud CDN’s advanced traffic management using flexible pattern matching is now GA. This allows you to use wildcards anywhere in your path matcher. You can use this to customize origin routing for different types of traffic, request and response behaviors, and caching policies. In addition, you can now use results from your pattern matching to rewrite the path that is sent to the origin.
Security Command Center (SCC) Premium, our built-in security and risk management solution for Google Cloud, is now generally available for self-service activation for full customer organizations. Customers can get started with SCC in just a few clicks in the Google Cloud console. There is no commitment requirement, and pricing is based on a flexible pay-as-you-go model.
Dataform is Generally Available. Dataform offers an end-to-end experience to develop, version control, and deploy SQL pipelines in BigQuery. Using a single web interface, data engineers and data analysts of all skill levels can build production-grade SQL pipelines in BigQuery while following software engineering best practices such as version control with Git, CI/CD, and code lifecycle management. Learn more.

Week of May 29 - June 2

Google Cloud Deploy. The price of an active delivery pipeline is reduced. Also, single-target delivery pipelines no longer incur a charge. Underlying service charges continue to apply. See Pricing Page for more details.

Week of May 22-26

Security Command Center (SCC) Premium pricing for project-level activation is now 25% lower for customers who use SCC to secure Compute Engine, GKE-Autopilot, App Engine and Cloud SQL. Please see our updated rate card. Also, we have expanded the number of finding types available for project-level Premium activations to help make your environment more secure. Learn more.
Vertex AI Embeddings for Text: Grounding LLMs made easy: Many people are now starting to think about how to bring Gen AI and large language models (LLMs) to production services. You may be wondering "How to integrate LLMs or AI chatbots with existing IT systems, databases and business data?", "We have thousands of products. How can I let LLM memorize them all precisely?", or "How to handle the hallucination issues in AI chatbots to build a reliable service?". Here is a quick solution: grounding with embeddings and vector search. What is grounding? What are embedding and vector search? In this post, we will learn these crucial concepts to build reliable Gen AI services for enterprise use with live demos and source code.

Week of May 15-19

Introducing the date/time selector in Log Analytics in Cloud Logging. You can now easily customize the date and time range of your queries in the Log Analytics page by using the same date/time-range selector used in Logs Explorer, Metrics Explorer and other Cloud Ops products. There are several time range options, such as preset times, custom start and end times, and relative time ranges. For more information, see Filter by time in the Log Analytics docs.
Cloud Workstations is now GA. We are thrilled to announce the general availability of Cloud Workstations with a list of new enhanced features, providing fully managed integrated development environments (IDEs) on Google Cloud. Cloud Workstations enables faster developer onboarding and increased developer productivity while helping support your compliance requirements with an enhanced security posture. Learn More

Week of May 8 - 14

Introducing BigQuery differential privacy, SQL building blocks that analysts and data scientists can use to anonymize their data. We are also partnering with Tumult Labs to help Google Cloud customers with their differential privacy implementations.
Scalable electronic trading on Google Cloud: A business case with BidFX: Working with Google Cloud, BidFX has been able to develop and deploy a new product called Liquidity Provision Analytics (“LPA”), launching to production within roughly six months, to solve the transaction cost analysis challenge in an innovative way. LPA will be offering features such as skew detection for liquidity providers, execution time optimization, pricing comparison, top of book analysis and feedback to counterparties. Read more here.
AWS EC2 VMs discovery and assessment - mFit can discover EC2 VMs inventory in your AWS region and collect guest level information from multiple VMs to provide technical fit assessment for modernization. See demo video.
Generate assessment report in Microsoft Excel file - mFit can generate detailed assessment report in Microsoft Excel (XLSX) format which can handle large amounts of VMs in a single report (few 1000’s) which an HTML report might not be able to handle.
Regulatory Reporting Platform: Regulatory reporting remains a challenge for financial services firms. We share our point of view on the main challenges and opportunities in our latest blog, accompanied by an infographic and a customer case study from ANZ Bank. We also wrote a white paper for anyone looking for a deeper dive into our Regulatory Reporting Platform.
Google is partnering with regional carriers Chunghwa Telecom, Innove (subsidiary of Globe Group) and AT&T to deliver the TPU (Taiwan-Philippines-U.S.) cable system — connecting Taiwan, Philippines, Guam, and California — to support growing demand in the APAC region. We are committed to providing Google Cloud customers with a resilient, high-performing global network. NEC is the supplier, and the system is expected to be ready for service in 2025.

Week of May 1 - 5

Microservices observability is now generally available for C++, Go and Java. This release includes a number of new features and improvements, making it easier than ever to monitor and troubleshoot your microservices applications. Learn more on our user guide.
Google Cloud Deploy Google Cloud Deploy now supports Skaffold 2.3 as the default Skaffold version for all target types. Release Notes.
Cloud Build You can now configure Cloud Build to continue executing a build even if specified steps fail. This feature is generally available. Learn more here

Week of April 24-28

General Availability: Custom Modules for Security Health Analytics is now generally available. Author custom detective controls in Security Command Center using the new custom module capability.
Next generation Confidential VM is now available in Private Preview with a Confidential Computing technology called AMD Secure Encrypted Virtualization-Secure Nested Paging (AMD SEV-SNP) on general purpose N2D machines. Confidential VMs with AMD SEV-SNP enabled builds upon memory encryption and adds new hardware-based security protections such as strong memory integrity, encrypted register state (thanks to AMD SEV-Encrypted State, SEV-ES), and hardware-rooted remote attestation. Sign up here!
Selecting Tier_1 networking for your Compute Engine VM can give you the bandwidth you need for demanding workloads. Check out this blog on Increasing bandwidth to Compute Engine VMs with TIER_1 networking.

Week of April 17-21

Use Terraform to manage Log Analytics in Cloud Logging You can now configure Log Analytics on Cloud Logging buckets and BigQuery linked datasets by using the following Terraform modules:
- Google_logging_project_bucket_config
- google_logging_linked_dataset

Week of April 10-14

Assured Open Source Software is generally available for Java and Python ecosystems. Assured OSS is offered at no charge and provides an opportunity for any organization that utilizes open source software to take advantage of Google’s expertise in securing open source dependencies.
BigQuery change data capture (CDC) is now in public preview!
BigQuery CDC provides a fully-managed method of processing and applying streamed UPSERT and DELETE operations directly into BigQuery tables in real time through the BigQuery Storage Write API. This further enables the real-time replication of more classically transactional systems into BigQuery, which empowers cross functional analytics between OLTP and OLAP systems. Learn more here.

Week of April 3-7

New Visualization tools for Compute Engine Fleets The Observability tab in the Compute Engine console VM List page has reached General Availability. The new Observability tab is an easy way to monitor and troubleshoot the health of your fleet of VMs
Datastream for BigQuery is Generally Available! Datastream for BigQuery is generally available, offering a unique, truly seamless and easy-to-use experience that enables near-real time insights in BigQuery with just a few steps. Using BigQuery’s newly developed change data capture (CDC) and Storage Write API’s UPSERT functionality, Datastream efficiently replicates updates directly from source systems into BigQuery tables in real-time. You no longer have to waste valuable resources building and managing complex data pipelines, self-managed staging tables, tricky DML merge logic, or manual conversion from database-specific data types into BigQuery data types. Just configure your source database, connection type, and destination in BigQuery and you’re all set. Datastream for BigQuery will backfill historical data and continuously replicate new changes as they happen.
Now available! Build an analytics lakehouse on Google Cloud whitepaper. The analytics lakehouse combines the benefits of data lakes and data warehouses without the overhead of each. In this paper, we discuss the end-to-end architecture which enable organizations to extract data in real-time regardless of which cloud or datastore the data reside in, use the data in aggregate for greater insight and artificial intelligence (AI) - all with governance and unified access across teams. Download now.
Now Available! Google Cloud Deploy now supports canary release as a deployment strategy. This feature is supported in Preview. Learn more
General Availability : Cloud Run services as backends to Internal HTTP(S) Load Balancers and Regional External HTTP(S) Load Balancers. Internal load balancers allow you to establish private connectivity between Cloud Run services and other services and clients on Google Cloud, on-premises, or on other clouds. In addition you get custom domains, tools to migrate traffic from legacy services, Identity-aware proxy support, and more. Regional external load balancer, as the name suggests, is designed to reside in a single region and connect with workloads only in the same region, thus helps you meet your regionalization requirements. Learn more.

Week of March 27-31

Last chance: Register to attend Google Data Cloud & AI Summit
Join us on Wednesday, March 29, at 9 AM PDT/12 PM EDT to discover how you can use data and AI to reveal opportunities to transform your business and make your data work smarter. Find out how organizations are using Google Cloud data and AI solutions to transform customer experiences, boost revenue, and reduce costs. Register today for this no cost digital event.
New BigQuery editions: flexibility and predictability for your data cloud
At the Data Cloud & AI Summit, we announced BigQuery pricing editions—Standard, Enterprise and Enterprise Plus—that allow you to choose the right price-performance for individual workloads. Along with editions, we also announced autoscaling capabilities that ensure you only pay for the compute capacity you use, and a new compressed storage billing model that is designed to reduce your storage costs. Learn more about latest BigQuery innovations and register for the upcoming BigQuery roadmap session on April 5, 2023.
Introducing Looker Modeler: A single source of truth for BI metrics
At the Data Cloud & AI Summit, we introduced a standalone metrics layer we call Looker Modeler, available in preview in Q2. With Looker Modeler, organizations can benefit from consistent governed metrics that define data relationships and progress against business priorities, and consume them in BI tools such as Connected Sheets, Looker Studio, Looker Studio Pro, Microsoft Power BI, Tableau, and ThoughtSpot.
Cloud Workstations is now available in more regions. Cloud Workstations is now available in asia-south1 (India), us-east4 (Virginia, North America), europe-west6 (Switzerland), and europe-west9 (France). The full list of regions is here.
Bucket based log based metrics—now generally available—allow you to track, visualize and alert on important logs in your cloud environment from many different projects or across the entire organization based on what logs are stored in a log bucket.
NEW Customer Blog! Faced with strong data growth, Squarespace made the decision to move away from on-premises Hadoop to a cloud-managed solution for its data platform. Learn how they reduced the number of escalations by 87% with the analytics lakehouse on Google Cloud. Read now

Week of March 20-24

Chronicle Security Operations Feature Roundup
Bringing a modern and unified security operations experience to our customers is and has been a top priority with the Google Chronicle team. We’re happy to show continuing innovation and even more valuable functionality. In our latest release roundup we’ll highlight a host of new capabilities focused on delivering improved context, collaboration, and speed to handle alerts faster and more effectively. Learn how our newest capabilities enable security teams to do more with less here.
Announcing Google’s Data Cloud & AI Summit, March 29th!
Can your data work smarter? How can you use AI to unlock new opportunities? Join us on Wednesday, March 29, to gain expert insights, new solutions, and strategies to reveal opportunities hiding in your company’s data. Find out how organizations are using Google Cloud data and AI solutions to transform customer experiences, boost revenue, and reduce costs. Register today for this no cost digital event.
Artifact Registry Feature Preview - Artifact Registry now supports immutable tags for Docker repositories. If you enable this setting, an image tag always points to the same image digest, including the default latest tag. This feature is in Preview. Learn more

Week of March 13 - 17

Building the most open and innovative AI ecosystem
In addition to the news this week on AI products, Google Cloud has also announced new partnerships, programs, and resources. This includes bringing bringing the best of Google’s infrastructure, AI products, and foundation models to partners at every layer of the AI stack: chipmakers, companies building foundation models and AI platforms, technology partners enabling companies to develop and deploy machine learning (ML) models, app-builders solving customer use-cases with generative AI, and global services and consulting firms that help enterprise customers implement all of this technology at scale. Learn more.
From Microbrows to Microservices
Ulta Beauty is building their digital store of the future, but to maintain control over their new modernized application they turned to Anthos and GKE - Google Cloud’s managed container services, to provide an eCommerce experience as beautiful as their guests. Read our blog to see how a newly-minted Cloud Architect learnt Kubernetes and Google Cloud to provide the best possible architecture for his developers. Learn more.
To prepare for the busiest shopping season of the year, Black Friday and Cyber Monday, Lowe’s relies heavily on Google’s agile SRE Framework to ensure business and technical alignment, manage bots, and create an always-available shopping experience. Read more.
Now generally available, understand and trust your data with Dataplex data lineage - a fully managed Dataplex capability that helps you understand how data is sourced and transformed within the organization. Dataplex data lineage automatically tracks data movement across BigQuery, BigLake, Cloud Data Fusion (Preview), and Cloud Composer (Preview), eliminating operational hassles around manual curation of lineage metadata. Learn more here.
Rapidly expand the reach of Spanner databases with read-only replicas and zero-downtime moves. Configurable read-only replicas let you add read-only replicas to any Spanner instance to deliver low latency reads to clients in any geography. Alongside Spanner’s zero-downtime instance move service, you have the freedom to move your production Spanner instances from any configuration to another on the fly, with zero downtime, whether it’s regional, multi-regional, or a custom configuration with configurable read-only replicas. Learn more here.

Week of March 6 - 10

Automatically blocking project SSH keys in Dataflow is now GA. This service option allows Dataflow users to prevent their Dataflow worker VMs from accepting SSH keys that are stored in project metadata, and results in improved security. Getting started is easy: enable the block-project-ssh-keys service option while submitting your Dataflow job.
Celebrate International Women’s Day Learn about the leaders driving impact at Google Cloud and creating pathways for other women in their industries. Read more.
Google Cloud Deploy now supports Parallel Deployment to GKE and Cloud Run workloads. This feature is in Preview. Read more.
Sumitovant doubles medical research output in one year using Looker
Sumitovant is a leading biopharma research company that has doubled their research output in one year alone. By leveraging modern cloud data technologies, Sumitovant supports their globally distributed workforce of scientists to develop next generation therapies using Google Cloud’s Looker for trusted self-service data research. To learn more about Looker check out https://cloud.google.com/looker

Week of Feb 27 - March 3

Accelerate Queries on your BigLake Tables with Cached Metadata (Preview!)
Make your queries on BigLake Tables go faster by enabling metadata caching. Your queries will avoid expensive LIST operation for discovering files in the table and experience faster file and hive partition pruning. Follow the documentation here.
Google Cloud Deploy support for deployment verification is now GA! Read more or Try the Demo
Add geospatial intelligence to your Retail use cases by leveraging the CARTO platform on top of your data in BigQuery
Location data will add a new dimension to your Retail use cases, like site selection, geomarketing, and logistics and supply chain optimization. Read more about the solution and various customer implementations in the CARTO for Retail Reference Guide, and see a demonstration in this blog.

Week of Feb 20 - Feb 24

Start your digital transformation by embarking on a hybrid cloud journey with Anthos. Anthos helps you modernize your application and infrastructure in place and build a unified Kubernetes fabric between your on prem environments and the Google cloud. The newly published Anthos hybrid cloud architecture reference design guide provides opinionated guidance to deploy Anthos in a hybrid environment to address some common challenges that you might encounter. Check out the architecture reference design guide here to accelerate your journey to hybrid cloud and containerization.
Logs for Network Load Balancing and logs for Internal TCP/UDP Load Balancing are now GA!
Logs are aggregated per-connection and exported in near real-time, providing useful information, such as 5-tuples of the connection, received bytes, and sent bytes, for troubleshooting and monitoring the pass-through Google Cloud Load Balancers. Further, customers can include additional optional fields, such as annotations for client-side and server-side GCE and GKE resources, to obtain richer telemetry.

Week of Feb 13 - Feb 17,

Announcing Google’s Data Cloud & AI Summit, March 29th!
Can your data work smarter? How can you use AI to unlock new opportunities? Register for Google Data Cloud & AI Summit, a digital event for data and IT leaders, data professionals, developers, and more to explore the latest breakthroughs. Join us on Wednesday, March 29, to gain expert insights, new solutions, and strategies to reveal opportunities hiding in your company’s data. Find out how organizations are using Google Cloud data and AI solutions to transform customer experiences, boost revenue, and reduce costs. Register today for this no cost digital event.
Leverege uses BigQuery as a key component of its data and analytics pipeline to deliver innovative IoT solutions at scale. As part of the Built with BigQuery program, this blog post goes into detail about Leverege IoT Stack that runs on Google Cloud to power business-critical enterprise IoT solutions at scale.
Download white paper Three Actions Enterprise IT Leaders Can Take to Improve Software Supply Chain Security to learn how and why high-profile software supply chain attacks like SolarWinds and Log4j happened, the key lessons learned from these attacks, as well as actions you can take today to prevent similar attacks from happening to your organization.
Running SAP workloads on Google Cloud? Upgrade to our newly released Agent for SAP to gain increased visibility into your infrastructure and application performance. The new agent consolidates several of our existing agents for SAP workloads, which means less time spent on installation and updates, and more time for making data-driven decisions. In addition, there is new optional functionality that powers exciting products like Workload Manager, a way to automatically scan your SAP workloads against best-practices. Learn how to install or upgrade the agent here.
Deploy PyTorch models on Vertex AI in a few clicks with prebuilt PyTorch serving containers - which means less code, no need to write Dockerfiles, and faster time to production.
Confidential GKE Nodes on Compute-Optimized C2D VMs are now GA. Confidential GKE Nodes help to increase the security of your GKE clusters by leveraging hardware to ensure your data is encrypted in memory, helping to defend against accidental data leakage, malicious administrators and “curious neighbors”. Getting started is easy, as your existing GKE workloads can run confidentially with no code changes required.

Week of Feb 3 - Feb 10

Immersive Stream for XR leverages Google Cloud GPUs to host, render, and stream high-quality photorealistic experiences to millions of mobile devices around the world, and is now generally available. Read more here.
Reliable and consistent data presents an invaluable opportunity for organizations to innovate, make critical business decisions, and create differentiated customer experiences. But poor data quality can lead to inefficient processes and possible financial losses. Today we announce new Dataplex features: automatic data quality (AutoDQ) and data profiling, available in public preview. AutoDQ offers automated rule recommendations, built-in reporting, and serveless execution to construct high-quality data. Data profiling delivers richer insight into the data by identifying its common statistical characteristics. Learn more.
Cloud Workstations now supports Customer Managed Encryption Keys (CMEK), which provides user encryption control over Cloud Workstation Persistent Disks. Read more
Google Cloud Deploy now supports Cloud Run targets in General Availability. Read more
Learn how to use NetApp Cloud Volumes Service as datastores for Google Cloud VMware Engine for expanding storage capacity. Read more

Week of Jan 30 - Feb 3

Oden Technologies uses BigQuery to provide real-time visibility, efficiency recommendations and resiliency in the face of network disruptions in manufacturing systems. As part of the Built with BigQuery program, this blog post describes the use cases, challenges, solution and solution architecture in great detail.
Lytics is a next generation composable CDP that enables companies to deploy a scalable CDP around their existing data warehouse/lakes. As part of the Built with BigQuery program for ISVs, Lytics leverages Analytics Hub to launch secure data sharing and enrichment solution for media and advertisers. This blog post goes over Lytics Conductor on Google Cloud and its architecture in great detail.
Now available in public preview, Dataplex business glossary offers users a cloud-native way to maintain and manage business terms and definitions for data governance, establishing consistent business language, improving trust in data, and enabling self-serve use of data. Learn more here.
Security Command Center (SCC), Google Cloud’s native security and risk management solution, is now available via self-service to protect individual projects from cyber attacks. It’s never been easier to secure your Google Cloud resources with SCC. Read our blog to learn more. To get started today, go to Security Command Center in the Google Cloud console for your projects.
Global External HTTP(S) Load Balancer and Cloud CDN now support advanced traffic management using flexible pattern matching in public preview. This allows you to use wildcards anywhere in your path matcher. You can use this to customize origin routing for different types of traffic, request and response behaviors, and caching policies. In addition, you can now use results from your pattern matching to rewrite the path that is sent to the origin.
Run large pods on GKE Autopilot with the Balanced compute class. When you need computing resources on the larger end of the spectrum, we’re excited that the Balanced compute class, which supports Pod resource sizes up to 222vCPU and 851GiB, is now GA!
Manage table and column-level access permissions using attribute-based policies in Dataplex. Dataplex attribute store provides a unified place where you can create and organize a Data Class hierarchy to classify your distributed data and assign behaviors such as Table-ACLs and Column-ACLs to the classified data classes. Dataplex will propagate IAM-Roles to tables, across multiple Google Cloud projects, according to the attribute(s) assigned to them and a single, merged policy tag to columns according to the attribute(s) attached to them. Read more.

Week of Jan 23 - Jan 27

Starting with Anthos version 1.14, Google supports each Anthos minor version for 12 months after the initial release of the minor version, or until the release of the third subsequent minor version, whichever is longer. We plan to have Anthos minor release three times a year around the months of April, August, and December in 2023, with a monthly patch release (for example, z in version x.y.z) for supported minor versions. For more information, read here.
Anthos Policy Controller enables the enforcement of fully programmable policies for your clusters across the environments. We are thrilled to announce the launch of our new built-in Policy Controller Dashboard, a powerful tool that makes it easy to manage and monitor the policy guardrails applied to your Fleet of clusters. New policy bundles are available to help audit your cluster resources against kubernetes standards, industry standards, or Google recommended best practices. The easiest way to get started with Anthos Policy Controller is to just install Policy controller and try applying a policy bundle to audit your fleet of clusters against a standard such as CIS benchmark.
Dataproc is an important service in any data lake modernization effort. Many customers begin their journey to the cloud by migrating their Hadoop workloads to Dataproc and continue to modernize their solutions by incorporating the full suite of Google Cloud’s data offerings. Check out this guide that demonstrates how you can optimize Dataproc job stability, performance, and cost-effectiveness.
Eventarc adds support for 85+ new direct events from the following Google services in Preview: API Gateway, Apigee Registry, BeyondCorp, Certificate Manager, Cloud Data Fusion, Cloud Functions, Cloud Memorystore for Memcached, Database Migration, Datastream, Eventarc, Workflows. This brings the total pre-integrated events offered in Eventarc to over 4000 events from 140+ Google services and third-party SaaS vendors.
mFit 1.14.0 release adds support for JBoss and Apache workloads by including fit analysis and framework analytics for these workload types in the assessment report. See the release notes for important bug fixes and enhancements.
Google Cloud Deploy Google Cloud Deploy now supports Skaffold version 2.0. Release notes
Cloud Workstations - Labels can now be applied to Cloud Workstations resources. Release notes
Cloud Build - Cloud Build repositories (2nd gen) lets you easily create and manage repository connections, not only through Cloud Console but also through gcloud and the Cloud Build API. Release notes

Week of Jan 16 - Jan 20

Cloud CDN now supports private origin authentication for Amazon Simple Storage Service (Amazon S3) buckets and compatible object stores in Preview. This capability improves security by allowing only trusted connections to access the content on your private origins and preventing users from directly accessing it.

Week of Jan 9 - Jan 13

Revionics partnered with Google Cloud to build a data-driven pricing platform for speed, scale and automation with BigQuery, Looker and more. As part of the Built with BigQuery program, this blog post describes the use cases, problems solved, solution architecture and key outcomes of hosting Revionics product, Platform Built for Change on Google Cloud.
Pub/Sub Lite now offers export subscriptions to Pub/Sub. This new subscription type writes Lite messages directly to Pub/Sub - no code development or Dataflow jobs needed. Great for connecting disparate data pipelines and migration from Lite to Pub/Sub. See here for documentation.
GPU Pods on GKE Autopilot are now generally available. Customers can now run ML training, inference, video encoding and all other workloads that need a GPU, with the convenience of GKE Autopilot’s fully-managed Kubernetes environment.
Kubernetes v1.26 is now generally available on GKE. GKE customers can now take advantage of the many new features in this exciting release. This release continues Google Cloud’s goal of making Kubernetes releases available to Google customers within 30 days of the Kubernetes OSS release.
Comprehensive guide for designing reliable infrastructure for your workloads in Google Cloud. The guide combines industry-leading reliability best practices with the knowledge and deep expertise of reliability engineers across Google. Understand the platform-level reliability capabilities of Google Cloud, the building blocks of reliability in Google Cloud and how these building blocks affect the availability of your cloud resources. Review guidelines for assessing the reliability requirements of your cloud workloads. Compare architectural options for deploying distributed and redundant resources across Google Cloud locations, and learn how to manage traffic and load for distributed deployments. Read the full blog here.

Shared fate: Protecting customers with generative AI indemnification

Thu, 12 Oct 2023 16:00:00 +0000

To our customers:

At Google Cloud, we put your interests first. This means that when you choose to work with us, we become partners on a journey of shared innovation, shared support, and shared fate. We are committed to helping you evolve as technology advances, drawing on our depth of experience to ensure you can use the latest and best technology, while keeping you safe and protected. When it comes to the rapidly developing world of generative AI, this is imperative.

Earlier this year, we embedded Duet AI — an always-on AI collaborator — across our products, from Google Workspace to Google Cloud Platform, and made major advancements to Vertex AI that allow customers to safely, securely, and responsibly experiment and build with generative AI foundation models. We’ve been thrilled to see the innovative use cases you’ve developed from across many industries. We put a lot of thought into how we can instill trust and confidence into these AI offerings, and today we’re pleased to share how we’re addressing one key area of interest for our customers: intellectual property indemnity as it pertains to generative AI.

We’ll explore this complex topic in detail below, but to put it plainly for you, our customers: if you are challenged on copyright grounds, we will assume responsibility for the potential legal risks involved. To do this we will employ a two-pronged, industry-first approach designed to give you more peace of mind when using our generative AI products. The first prong relates to Google’s use of training data, while the second specifically covers generated output of foundation models.

If you are challenged on copyright grounds, we will assume responsibility for the potential legal risks involved.

Taken together, these indemnities provide comprehensive coverage for our customers who may be justifiably concerned about the risks associated with this exciting new frontier of generative AI products. While these indemnities provide powerful protections, we are also committed to maintaining an ongoing dialogue with our customers about other specific use cases that may need coverage.

Let’s look at each of the indemnities in greater detail.

Indemnity 1: Training data
The indemnity for training data used by Google for generative AI models in all our services is actually not a new protection. We have always stood behind all of our services, including generative AI services, by offering a third-party intellectual property indemnity as standard for all customers. However, we’ve heard from many of you that while your company appreciates our general services indemnity, you would like explicit clarification with regards to the training data behind the Google models that those services leverage. We are happy to deliver this reassurance.

Specifically, our training data indemnity covers any allegations that Google’s use of training data to create any of our generative models utilized by a generative AI service, infringes a third party’s intellectual property right.

What does this training data indemnity mean for our customers?
We hope this gives you confidence that your company is protected against third parties claiming copyright infringement as a result of Google’s use of training data. Put simply, regardless of the training data underlying all our services, Google indemnifies you.

Indemnity 2: Generated output indemnity
The generated output indemnity provides you with a second layer of protection, as the generated output is created by our customers in response to prompts or other inputs that they provide to our services. With this second layer of protection, our indemnity obligations now also apply to allegations that generated output infringes a third party’s intellectual property rights.

The generated output indemnity will apply to Duet AI in Google Workspace and to a range of Google Cloud services. As a part of today’s announcement, products covered include:

Duet AI in Workspace, including generated text in Google Docs and Gmail and generated images in Google Slides and Google Meet
Duet AI in Google Cloud including Duet AI for assisted application development
Vertex AI Search
Vertex AI Conversation
Vertex AI Text Embedding API / Multimodal Embeddings
Visual Captioning / Visual Q&A on Vertex AI
Codey APIs

An important note here: you as a customer also have a part to play. For example, this indemnity only applies if you didn’t try to intentionally create or use generated output to infringe the rights of others, and similarly, are using existing and emerging tools, for example to cite sources to help use generated output responsibly.

What does this generated output indemnity mean for our customers?
The generated output indemnity means that you can use content generated with a range of our products knowing Google will indemnify you for third-party IP claims, including copyright — assuming your company is following responsible AI practices like the ones described above.

What do both indemnities together mean for our customers?
It means that you can expect Google Cloud to cover claims, like copyright infringement, made against your company, regardless of whether they stem from the generated output or Google's use of training data to create our generative AI models. By offering two-pronged generative AI indemnity protections, we are providing balanced, practical coverage for relevant types of potential claims. By offering these indemnities on our public service terms page (see below), customers will automatically receive the benefit of these terms without needing to amend their existing agreement.

This is just the first step, and as we continue working together on our shared generative AI journey, we will continue to support you in making sure you can use our services safely, securely and confidently. With protections like these, we hope to give you the assurance you need to get the best out of generative AI for your business.

You can read the exact terms of services here for Google Cloud and here for Workspace.

“The time is now.” Why this Kenyan Googler is betting on Africa’s tech opportunity

Fri, 12 May 2023 16:00:00 +0000

Editor’s note: Jack Ngare is a Technical Director in Google Cloud’s Office of the CTO based in Nairobi, Kenya. A native of Kenya, he worked in telecommunications abroad for 12 years before returning home to work for a large African financial institution and a U.S. technology company. He joined Google Cloud last year with a mission to digitize and modernize Cloud’s global top customers, while simultaneously growing Africa's entrepreneurial technology culture.

What is the opportunity you see before you?

Working at Google Cloud, I’m able to bring people some of the world's best software and hardware engineering. I also see the possibility of taking the capabilities that Google Cloud offers leading banks, retailers, telecommunications companies, and others in the developed world, and putting them in place in Africa. Not only would this create efficiency and end waste in a dramatic fashion, but it would also be an opportunity for Google Cloud to help advance Africa's potential and inspire people with the creativity and drive within the organization.

African technology development is a two-way exchange. Google Cloud customers I have worked with across the globe have similar challenges and opportunities, including identifying how to improve efficiency, how to optimize data pipelines, and how to apply AI in productive, cost-effective ways. Common challenges are best addressed from diverse perspectives. In the past 30 years, we've seen how customers in China, India, and Africa, unhampered by maintaining legacy infrastructures, leapfrogged development in mobile and fiber optic technologies.

What do you think are the biggest misconceptions about Africa?

One of the most common misconceptions is thinking of Africa as one place. Sub-Saharan Africa has nearly 50 countries, with more than a billion people spread over millions of square miles. There are several different cultures, economies, customers, and opportunities.

Africa shouldn't be considered a place with nothing but needs. The region has a lot to give. There's a young population that is very tech savvy. Many people are doing gig work in areas like coding, design, social media, and AI for large global companies. They understand those things very well, and are keen to do more.

Is it hard to know where to start?

In some ways, that is the hardest thing. There’s so much potential, and we need to show how Google Cloud can be a strong partner across all industries and business sizes — 70% of African businesses are small and medium-sized enterprises.

Outside of my day job, I continue to help bring technology to Africa in several ways. I participate in creating a curriculum for kids here in grades K-12 to learn how to code, I work on getting companies to sponsor schools that need to be wired to high speed Internet, and I speak at universities.

Jack and his daughter with the senior class at Alliance Girls High school in Kenya, where Jack had taught some coding classes

What would you say is your biggest motivation?

My biggest motivation is urgency. Opportunity doesn't hang around forever waiting for you. It wants to be understood and engaged with. This is an extraordinary time. On the one hand, the entrepreneurial drive was always here in Africa, but it had a hard time attaching itself to the larger world, or even connecting to good networks! The cloud, and good connectivity, can change that.

Take for example, Google’s recently commissioned report from Africa Practice, which is about the impact of its Equiano subsea cable. It’s estimated that it could cut data prices by up to a fifth, and help create 1.6 million jobs as a result of increased connectivity. Equiano will connect Europe with Togo, Nigeria, Namibia, and South Africa (and even, away from Africa). It's a big step.

At the same time, we have to move fast, we have to move with knowledge. Two years ago, Google made a $1 billion commitment to develop business in Africa, and in October we gave an update: Our first data center in the region was built, support is in place for entrepreneurs, and Artificial Intelligence is being used to map buildings. However, history shows that it's possible to spend $1 billion and make little impact. You have to take action and you must follow-up.

What makes you confident?

I'm a citizen of Kenya, an African who was fortunate enough to get the right breaks in education and the right opportunities. It has brought me so far. While I’m confident in myself, I’m even more confident that there could be 100 or 1,000 people like me who can succeed more than I have. I'm confident that we can give them that chance with Google Cloud, and if we get it right, the results will astonish the world. The time is now.

Alicia Abella has a PhD and 29 patents to her name — now she’s helping telcos transform and creating opportunities for others to join tech

Mon, 27 Mar 2023 16:00:00 +0000

Editor’s note: Alicia Abella is the Managing Director for Telecommunications Industry Solutions at Google Cloud. The work involves bringing complex, advanced technology to businesses across diverse markets and cultures — from startups in Brazil to North America's largest telecommunications companies. The daughter of immigrants from Cuba, she has a PhD, 29 patents, and extensive experience running teams and working with customers.

Did you always see yourself bringing new inventions into the world?

No, not at all. I grew up in Queens, New York — the only child of Cuban immigrants. My parents worked hard and saved money so I could get an education. I was first exposed to programming when I was a junior in high school. Personal computers were just becoming popular, and I thought operating them and fixing them could be a promising career.

While I was attending New York University, I got an internship at Bell Labs, which is the research arm of AT&T. Being around legends in their field who were working on the hardest breakthroughs in computing and communications impacted me greatly. Shortly after, I went to graduate school and worked on Natural Language Processing, Image Recognition, and other software problems. A lot of the Artificial Intelligence work you see today is what we were working on back then.

I stayed at Bell Labs for over 25 years, working my way up and becoming the first woman from AT&T Labs - Research to be promoted to Vice President. During my time there, I obtained 29 patents, received one of the two highest technical achievements, delivered on trailblazing business imperatives, and worked with great people.

Alicia and her parents at her PhD graduation from Columbia University

How is being at Google Cloud different?

I'd start with what is the same. Google Cloud has innovation, big ideas, difficult research, and people willing to take on really complicated problems. Both Bell Labs and Google Cloud have high engagement with business customers and consumers, but my role at Google Cloud is more client facing. In terms of differences, Google Cloud has many products that billions of people use everyday — so many that we lose count of how much AI and infrastructure goes into making these products pervasive.

At Google Cloud, I work with a diverse range of telecommunications companies that choose cloud for cost-efficiency reasons. The companies partner with us to bring differentiated experiences to customers and generate new revenue opportunities. Many work with us to deploy 5G edge computing solutions and network functions that bring low latency, high bandwidth applications to customers everywhere.

Was it hard moving from the lab to business?

There is a kind of tension you need to understand. It can take decades for a technology to mature, while businesses have many near-term goals. Sometimes you're waiting for the computing to become quick enough, or all the parts of the puzzle to reach maturity, before a product or service is great. Sometimes it's waiting for society to accept the new technology — for example, AT&T demonstrated a desktop video phone in 1970, but it wasn’t until Apple made FaceTime available in 2012 that the technology took off. That was an example of computers getting better and society changing.

There's also the practice of moving between technology and business. I am fortunate to have the ability to translate hard technical concepts into potential uses with real business value. I'm a good listener and have deep customer empathy, which allows me to connect dots — bringing business meeting takeaways to our engineers and discussing what needs to be built.

What do you wish our industry communicated better?

I wish people understood how complex and difficult it is to develop new technology. There's a lot of pressure to earn investments back quickly, but it takes quite a long time to get the big breakthroughs. I wish everyone in the process — from customers and managers to shareholders and the public — understood the need to find that balance.

While there's some truth in the idea of the lone genius and the indispensable founder in tech, people should understand the importance of teamwork. My best moments have been working on small focused teams, where the vision was clear and the passion was high. My first patent was very exciting, and it came as a result of working on a team. I still have it on my wall.

You've also been closely involved with helping women and minorities in the field.

As both a woman and a member of the Hispanic community, these are areas I wish we'd see more progress. The percentage of women earning Computer Science degrees peaked in the mid-80s. The year I got my PhD, I heard I was one of only two Hispanic women PhDs in Engineering. I’ve served on President Obama's Commission for Educational Excellence for Hispanics. I've also served on a nonprofit to promote women in STEM, and try to speak in any forum where I can inspire people. I try to serve as a role model, and meet with individual families about their kids' futures.

Just as with new technological breakthroughs, this too will take time and effort, but I am positive progress can be achieved.

Alicia with Supreme Court Justice Sonia Sotomayor at her White House Commission swearing in

Google is a Leader in the 2023 Gartner® Magic Quadrant™ for Enterprise Conversational AI Platforms

Thu, 09 Mar 2023 20:00:00 +0000

We’re excited to share that Gartner has recognized Google as a Leader in the 2023 Gartner® Magic Quadrant™ for Enterprise Conversational AI Platforms, authored by Bern Elliot and Gabriele Rigon.

We believe this recognition is a testament to Google Cloud’s robust investments and commitment to innovation in AI, coupled with a deep understanding of enterprise customer needs. Enterprises are increasingly investing in AI-driven solutions that balance addressing customer expectations with operational efficiency. At a time when the demand for quality, performant, and trustworthy conversational AI has never been higher, we’re thrilled to continue to deliver best-in-class technologies, purpose-built to solve our customers’ most critical use cases.

In 2022, Google Cloud delivered cutting-edge conversational AI technologies with many launches to our Conversational AI API portfolio. Together, these enabled developers to leverage Google's technologies to power their applications with our end-to-end Contact Center AI (CCAI) suite, designed to solve the needs of Customer Experience (CX) and contact center leaders.

Google Cloud’s Conversational AI APIs include pre-trained models for Speech to Text, Text to Speech and Natural Language Understanding. This conversational AI core leverages Google Research’s technology for speech, understanding and interaction, enabling and orchestrating high-quality conversational experiences at scale.

With Contact Center AI, organizations see improved customer satisfaction, higher agent productivity and reduced costs through increased agent efficiency. By focusing on user needs, Google Cloud provides comprehensive and integrated solutions that are ready for the enterprise. CCAI encompasses a comprehensive set of offerings to address the needs of the contact center.

In 2022, we launched Contact Center AI Platform, our AI-first, mobile-first, user-first contact center as a service (CCaaS), providing AI-powered experiences, CRM-centered design and deployment flexibility in a single platform without the need for multiple providers. Contact Center AI Platform auto-scales on the backend, with capacity for up to 100k concurrent users on a single tenant. It also offers multi-provider voice resiliency with global low-latency routing for best possible call quality and is optimized for enhanced customer/business data security, reduced downtime, and increased agent productivity. Segra, one of the largest independent fiber infrastructure bandwidth companies in the Eastern U.S., is leveraging CCAI Platform to reimagine their customer experience through predictive flows for common experiences and greatly expanding their channels for customer interaction.

CCAI also includes Dialogflow for building virtual agents, enabling businesses to meet their customers across multiple channels. It offers robust, flexible self-service voice and chat interactions that are just as natural as a live agent. Dialogflow enables both a great customer experience and a cost-effective way to scale services.

Our Agent Assist service gives businesses the ability to transition a call from a virtual agent to a human agent while maintaining context. It efficiently guides the agent to an accurate response, while providing real-time suggestions, more accurate responses and informed recommendations.

To improve contact center operations, CCAI Insights analyzes all customer conversations to provide leaders with real-time, actionable data points on customer queries, agent performance, and sentiment trends. Its topic modeling capabilities enable deeper understanding of key investment areas and greater classification accuracy.

To ensure our enterprise customers deploying CCAI realize value faster, Google Cloud offers CCAI through three defined transformation stages with out-of-the-box packages. The first stage starts with efficiency basics in the first week that include transcription and summarization. The second stage covers automation basics within six months using Agent Assist and Insights. The final stage is full automation within a year with industry use cases and pre-built components. All of this leads to higher agent efficiency, improved customer satisfaction and increased containment.

As we look forward to the rest of 2023 and beyond, elevating the customer experience through user-first design, AI-first capabilities and accelerating time-to-value will be our north star. We plan to announce exciting new capabilities over the next few months to enable that vision to become a reality for many more organizations.

We are honored to be a Leader in the 2023 Gartner® Magic Quadrant™ for Enterprise Conversational AI Platforms, and look forward to continuing to innovate and partner with customers on their digital transformation journeys.

Download the complimentary copy of the report: 2023 Gartner® Magic Quadrant™ for Enterprise Conversational AI Platforms.

Learn more about how organizations are transforming their business with Google Cloud solutions with Contact Center AI.

^{GARTNER is a registered trademark and service mark of Gartner and Magic Quadrant is a registered trademark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved.}

^{This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Google.}

^{Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.}

“I wouldn’t have believed you” How Brazilian Googler José Neto built his own path to tech with relentless learning and hustle

Thu, 09 Mar 2023 17:00:00 +0000

Editor’s Note: José Neto works in Google Cloud's São Paulo office, assisting customers in both hybrid/on-prem cloud computing systems, and modernizing computer applications for the cloud. It's appropriate work; a native of Salvador, Brazil, he's spent decades harmonizing the past and the future, dealing with radical change, and staying comfortable amid uncertainty as he moves forward.

What do you think defines how you work?

It's the way I look at experience. When I work with a customer, I'm interested in helping them fix a problem or build a new service—it's very personal for me.

I love working towards results. I always ask what the impact on people will be if we fix the problems. I can tell when people want to create a better experience for a customer, and it always makes me more eager to collaborate with them.

What is it about having an experience, and why is that idea so personal for you?

I believe a positive, new experience is also an experience of hope.

Education—the process of learning—is an experience that I've never grown tired of. I grew up so poor that we didn't have food every day. When I was 13, I moved to my grandmother's house, which gave me the opportunity to attend better schools and pursue education at a greater capacity. My grandmother put me on a path of relentless learning in many different ways.

Like what?

For example, if I wanted pocket money, she'd have me read a book and then she’d quiz me on it before she paid me. When I was 18, one of her friends gave me a job at a computer store where the employees had a lot more experience with the machines than I did, which meant they could take care of twice as many customers as I could. Because we worked on commission, I learned that I needed to hunt down the business so I could eat. Luckily, I was curious, so I learned more about the computers than the others knew, and eventually I was fixing things they missed, such as viruses that reinfected customers' machines. That helped my reputation and put me on the path to getting a better job.

That's still a long way from Enterprise cloud computing.

It was the start. I eventually got a job with an IT company where I learned about the Linux operating system, email servers, and Web servers. When I was 27, I moved to Angola and worked to build Internet phone calling for an education company. While I was there, I learned about mission-critical systems, and worked for oil and gas companies. Eventually, a bank in Rio de Janeiro hired me to work on its systems, and a few years later I was moved to São Paulo—which is where I learned about cloud computing. After a couple of years at another big cloud company, I ended up at Google Cloud.

That's a lot of work!

It's a lot of experience. I haven’t even touched on what else was going on in my life at the time. I went to Angola not only because I wanted to marry my girlfriend and needed to save money, but I was interested in seeing Angola, because it's a Portuguese-speaking place like Brazil. Because Black people are the dominant community in Angola, I learned a lot. There are many more experiences in my story that contribute to who I am today and how much I’m still learning.

José Neto living in Angola

Do you think much about how far your life has taken you?

Like everybody else, I am just living my life, seeking new experiences and opportunities. If you told 18 year-old me where I’d be right now in my life, I wouldn't have believed you. At that point in my life, I was hunting every day to eat. I wouldn't have believed that I have enough in life to not worry about eating for a year. I couldn't have imagined the technology I'd be working with, or that I'd be educating myself not just with books, but by talking to people at Google Cloud who built big parts of cloud computing.

By the way, what books did your grandmother have you read? Science? Math?

Shakespeare! Oscar Wilde, "The Picture of Dorian Gray." Dostoyevsky's "Crime and Punishment." Raskolnikov is such a great character! Talk about a personal transformation. I still love "Wuthering Heights."

We weren't expecting that answer.

Those books didn't prepare me for computers, but they did help me understand other people, and what they may be going through. Good stories grow your empathy. Empathy makes you better with customers, experience, and life.