SAP on Google Cloud

How SAP Concur automates expense reporting with agentic AI

Fri, 10 Apr 2026 16:00:00 +0000

For decades, expense automation relied on a simple premise: If the machine can read the text, it can do the work. But anyone who has ever tried to scan a crumpled, smudged, or sun-bleached receipt from their pocket knows that reading isn't enough. When key data is missing, such as a city name or a clear date, the machine halts and the burden falls back onto the user for manual entry.

To close this gap, where traditional Optical Character Recognition (OCR) fails, SAP Concur’s engineering team set out to break new ground. While much of the industry was still focused on the design of conversational interfaces, SAP Concur foresaw a bigger shift. They recognized early on that the next leap in efficiency wouldn't come from better scanning, but from intelligent reasoning.

The result is an agentic AI upgrade for ExpenseIt, moving automation beyond simply reading text to solving messy logic puzzles, significantly reducing the need for manual intervention. Now, travelers can simply snap photos of their receipts as they receive them, upload digital scans, or forward receipts as emails, and ExpenseIt instantly transforms them into accurate expense entries with no date entry or itemization required.

Bringing this next-generation system called for a partner who could push the boundaries of innovation while matching the ambition to execute at startup speeds. SAP Concur fused its visionary roadmap with Google Cloud’s full-stack AI power, partnering with the only provider that co-designs every layer, from custom silicon and data platforms to world-class models and agents. Together, the teams engineered a true breakthrough in cost management — an AI agent that not only captures the receipt but intuitively understands the business traveler’s reality.

Speed, scale, and ingenuity

Standard expense automation is great at seeing what is on receipts but can’t see what is not there. SAP Concur saw the emergence of AI agents as an opportunity to create systems that could reason, decide, and act.

Suppose you upload a lunch receipt from “The Main St. Café,” which doesn’t include the address. In the past, this missing information would completely derail the automation and require you to manually enter this data to continue.

Agentic capabilities enable analyzing contextual clues, such as a vendor’s name, expense types, and trip itinerary data, to fill in the gaps. SAP Concur wanted to create an AI agent that could think like a human assistant: "I see 'Main St. Café.' I also see this transaction coincides with a business trip, where the user has a flight to Dallas and a hotel in Greenville, Texas. Therefore, this vendor is probably the restaurant located near the hotel in Paris, Texas — not Paris, France."

To solve this challenge, the teams approached the problem with a dynamic, startup-style mindset. Instead of a lengthy development cycle, the collaboration was defined by rapid prototyping and bold problem-solving.

Utilizing Google’s Gemini models, they built the Receipt Analysis Agent, underpinned by a cognitive architecture.

Here’s how it works:

Ingestion: The user snaps a photo in the SAP Concur mobile app, uploads a digital scan, or forwards a digital receipt as an email.
Deterministic core: SAP’s foundational technology, refined over decades of processing global expenses, applies finely tuned logic to lift the visible text on receipts with high precision.
Intelligent rRouting layer: If the scanned receipt data is clear, there’s no need to trigger additional actions. If the data is ambiguous (e.g., "Missing location"), the routing logic dynamically directs the task to the Receipt Analysis Agent.
Contextual reasoning: Built with Gemini models, the AI agent doesn’t just guess — it uses tools and grounding to infer missing information. ExpenseIt feeds the partial receipt data to the agent, alongside grounding data like the user’s travel itinerary and business calendar.
ReAct (Reason and Act framework): The Receipt Analysis Agent connects the dots, validating the vendor against the location history, and then completes the expense entry.

ExpenseIt with agentic AI (Receipt Analysis Agent)

Based on the example above, ExpenseIt identifies the receipt image as missing the location, and the intelligent routing layer triggers the Receipt Analysis Agent. Using Gemini, the agent will then identify what’s missing, analyze surrounding contextual clues and user-specific data, and make decisions based on information like travel bookings and calendar events.

Key design patterns for successful AI agents

The Receipt Analysis Agent was designed based on the core principles from Agentic Design Patterns, a hands-on guide written by senior Google engineer Antonio Gulli. This critical guidance helped SAP Concur successfully transform ExpenseIt into a system that can reason on data both inside and outside of receipts to accurately create expense entries.

First, the teams implemented the Routing Pattern to avoid running every receipt through the AI agent, helping to optimize for both cost and intelligence. A routing architecture classifies incoming tasks: Receipts with a high OCR confidence score are routed to the standard deterministic path, while those with low scores (e.g., “Missing location) are dynamically routed to the Receipt Analysis Agent.

Next, the Reflection Pattern is applied to solve issues like the Paris Paradox, ensuring the agent doesn’t just generate an answer like a basic chatbot. This pattern involves an internal generator-critic loop, where the model generates a hypothesis (“I think this is Paris, France”) and then acts a critic, checking it against established facts (“The itinerary says Dallas, Texas. This hypothesis is likely false.”).

Finally, the agent follows the Tool Use Pattern, providing explicit API access to grounding sources like trip itineraries from Concur Travel. This approach allows the agent to fetch the truth rather than hallucinating it, turning the system from a text generator to a factual researcher.

Architecting for ambiguity: Google Cloud’s ecosystem advantage

This project highlights a pivotal shift in intelligent system design. By combining a deterministic core with an agentic reasoning layer, SAP Concur demonstrated that AI’s highest value often isn't in processing the data we have, but in reasoning to find the data we are missing. A defining moment in this engineering journey was the shift in how the model was utilized. The teams moved beyond treating Gemini as a generative interface and instead deployed it as a logic engine.

Why did SAP Concur choose to build this future with Google Cloud? Because an agent is only as good as its understanding of the world — and no one understands the digital world like Google.

While this current release relies on the reasoning power of Gemini, the partnership opens the door to a future of multimodal, full-stack intelligence that’s unique in the market, including:

Real-world grounding: Imagine an agent that cross-references a receipt with Google Maps data to ensure the business actually exists at that location.
Frictionless flow: Future integrations could use Google Wallet to match transaction timestamps instantly, or Gmail to surface hotel folio receipts automatically.
Edge intelligence: With mobile advancements like Gemini Nano and the service system Android AICore, sensitive processing could eventually happen right on devices, giving users speed and privacy without the data ever leaving their phone.

SAP Concur has the deep domain expertise that powers the world’s financial transactions. Google Cloud brings the full AI stack from the custom-designed chips (TPUs) optimized for training, to the mobile OS in the user’s pocket.

Ready to build your next-generation agent?

You don't need to reinvent the wheel to build a reasoning engine like ExpenseIt. The architectural patterns discussed here — Routing, Reflection, and Tool Use — are codified directly in the Google Agent Development Kit (ADK). The ADK provides the frameworks and best practices to help you move from "prompt engineering" to "system engineering," serving as a blueprint for building agents that are reliable, scalable, and ready for the enterprise.

Unlocking a new era for SAP on Google Cloud

Tue, 16 Sep 2025 09:00:00 +0000

The world of enterprise technology is at an inflection point. Businesses are no longer just looking to modernize their infrastructure; they're seeking to infuse intelligence and automation into every aspect of their operations. At Google Cloud, we believe the future lies in a unified, intelligent, and flexible enterprise landscape. That's why we're so excited about our latest innovations and partnerships with SAP, all designed to help customers unlock the true potential of their data and applications.

A unified data foundation: SAP Business Data Cloud and Google BigQuery

Data is the lifeblood of every modern business, and having a fragmented data landscape is a primary obstacle to innovation. We're proud to announce that SAP Business Data Cloud is now launched on Google Cloud, a significant step forward in our shared mission with SAP to help businesses get more value from their enterprise data.

This integration builds on our existing partnership around SAP Datasphere and BigQuery, and it creates a frictionless experience for customers. It enables you to:

Unify Your Data Landscape: Access data directly from BigQuery within SAP Business Data Cloud (integrated through Datasphere) and vice versa, creating a single, comprehensive view of your business.
Enable Bi-directional Data Flow: Use efficient, built-in data replication to ensure data consistency across your SAP and Google Cloud environments.
Accelerate Insights with AI: Leverage Google Cloud's powerful Vertex AI capabilities and analytics tools, all fueled by rich, real-time data from your SAP systems.

Late August, SAP launched SAP Business Data Cloud on three Google Cloud regions, in Asia Pacific, Europe, and USA, with more to follow. In addition, SAP BW Private Cloud Edition (PCE), which is offered through SAP BDC, is supported in more than 40 Google Cloud regions, helping our customers meet critical data residency and compliance requirements.

Simplifying procurement with the Google Cloud Marketplace

We're also making it easier than ever to acquire and manage your SAP solutions. SAP Business Technology Platform (SAP BTP) is now available on the Google Cloud Marketplace. This is a game-changer for businesses looking to accelerate their innovation journey.

With SAP BTP on the Marketplace, we are enabling customers to:

Simplify Procurement and Billing: Get a single, unified billing experience for both your Google Cloud infrastructure and SAP BTP services. No more managing separate contracts and invoices—just one simplified process.
Leverage Existing Google Cloud Commitments: One of the most significant advantages is the ability to use your existing Google Cloud spend commitments for SAP BTP services. This helps you maximize your investment and streamline your financial operations, providing more value from your cloud budget.

To get started, simply navigate to the SAP BTP listing on the Google Cloud Marketplace and request a private offer.

AI Agents: A New Frontier for Business Automation

The world of business process automation is being revolutionized by AI agents, and SAP customers are uniquely positioned to take advantage. At Google Cloud, we are seeing a groundswell of adoption as customers leverage the power of our innovative agentic technologies to drive a clean core strategy and innovate at the speed of business.

This is enabled by a powerful combination of technologies, including:

Agentspace: This new Enterprise Search and AI Assistant platform on Google Cloud is the central hub where your custom-built AI agents live and collaborate. Google Agentspace provides the tools to design, test, and orchestrate complex workflows, allowing you to turn domain knowledge into automated solutions.
Google Agent Development Kit (ADK): For more complex use cases, the ADK provides a robust framework to build and deploy production-ready agents that interact with your SAP systems.
Agent-to-Agent (A2A) Protocol and Model Context Protocol (MCP): These open standards are the key to multi-agent collaboration. The A2A protocol allows your custom-built Google Cloud agents to work directly with SAP’s own AI copilot, SAP Joule. MCP gives your agents a secure "language" to access real-time, authoritative data from your SAP systems via the ABAP SDK for Google Cloud, making them more reliable, capable, and actionable.

These protocols, in combination with the power of Gemini, enable agents to understand natural language queries, make decisions, and autonomously execute multi-step business tasks.

Customers like Smyths Toys are taking advantage of Google's AI ecosystem to accelerate innovation by using AI agents to transform their customer service operations. Their agent-based real-time resolution system has automated responses for over 23% of customer queries – relying on an SAP backend with a multi-agent frontend built on Google Kubernetes Engine (GKE) and Google BigQuery. Beyond this, Smyths Toys marketing team is also utilizing Google's AI solutions, including Imagen and Veo models, to tap into the full breadth of Google Cloud's capabilities.

Expanding our portfolio of memory-optimized machine instances for SAP HANA

Earlier this year, we announced the general availability of our new M4 memory-optimized machine series based on Intel’s latest 5th generation Xeon processors (code-named Emerald Rapids) which offer significant price and price-performance improvements compared to our prior generation M2 and M3 families.

In August, we released three additional M4-hypermem shapes providing memory sizes of 248, 496, and 992 GB that are certified for SAP HANA and backed by Compute Engine’s Memory Optimized 99.95% Single Instance SLA.

M4 is now available in three ratios of memory to vCPU and offers HANA certified sizes ranging from 248 GB to 6 TB. This increased level of shape granularity can help you lower TCO and improve price-performance by picking an instance type that best fits your workload requirements. Combined with our existing VM families, Google Cloud now offers 26 unique memory-optimized instances certified for SAP HANA ranging from 248 GB to 32 TB.

Ready to transform your SAP systems?

From a unified data foundation to simplified procurement and powerful AI agents, the innovations we've shared today help you get the most from your SAP systems. By leveraging the full potential of Google Cloud’s AI capabilities, you can transform your SAP experience, drive greater efficiency, and unlock new avenues for innovation. Explore these new capabilities and discover how Google Cloud can help you build a more intelligent, agile, and future-ready enterprise.

System-centric monitoring and observability for SAP workloads running on Google Cloud

Thu, 31 Jul 2025 16:00:00 +0000

Managing complex SAP landscapes can feel like navigating a maze. You’re juggling application performance, database health, infrastructure stability, and more, all while striving to ensure seamless business applications. Today, we’re excited to announce new observability and monitoring functionality in Workload Manager to provide SAP customers with purpose-built tools that bridge gaps in data and provide a unified view of SAP environments across all layers of their cloud environments.

Workload Manager is not intended to replace your existing SAP monitoring tools, but rather complement them by providing a broader view of your SAP systems and enabling you to more easily correlate application-level insights with infrastructure performance and events.

Expanding visibility in complex SAP environments

Traditional SAP monitoring excels at providing detailed information at the application and database level. Metrics about transaction performance, user activity, and application logs are readily available. However, understanding the relationship between this application data and the underlying infrastructure can sometimes require additional effort. For example, a slowdown in transaction processing might be due to a database issue, a network bottleneck, or even a problem with the underlying virtual machine. While existing tools provide valuable insights, correlating application performance with infrastructure health can be a time-consuming process or may require toggling between different monitoring platforms and manual efforts.

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Creating a system-centric, unified view with Workload Manager

After enabling the necessary functionality in Google Cloud’s Agent for SAP, you can navigate to the main Observability dashboard to see an overview of your SAP systems and the overall health status of each system and sub-layer. The health status is calculated using a variety of metrics from SAP Netweaver instances, SAP HANA databases, pacemaker clusters, and the availability of the underlying infrastructure hosting them.

Clicking on a system will take you to the system Overview page, where you can visualize the components of the system and see the current health status for each instance included. The Health Insights table will summarize any health issues that are currently detected, and the Maintenance Events table displays any upcoming maintenance for supported machine types.

The “Applications” and “Databases” tabs behave similarly, and help you correlate key performance indicators from your SAP applications with metrics from your VMs, storage, network, and other Google Cloud services such as the following:

Availability: GCE Instance Availability, SAP NetWeaver and SAP HANA instance status, SAP NetWeaver and SAP HANA process status and Pacemaker Cluster nodes and resource status.
Performance: GCE Instance CPU and memory utilization, operating system processes by CPU and memory and information about swap I/O operations on the operating system.
Storage: SAP related file systems usage, disk space utilization and usage, disk throughput and disk IOPS.
Networking: Information about network traffic and network packages.
Netweaver: CPU and memory utilization by SAP NetWeaver process, response time by processes in the SAP NetWeaver instance, SAP NetWeaver sessions and RFC connections by type, SAP NetWeaver process utilization per work process type and information for each SAP NetWeaver process type for each respective queue in the system.
HANA: SAP HANA System Replication status, SAP HANA System Replication latency, memory usage in the SAP HANA Database by type, information about idle and running connections in the SAP HANA database and top schemas by record count in the SAP HANA database.
Backups: Information related to Backint backups including Backup/Recovery success rate, Backup/Recovery average MBps for all operations and historical data about both Backup/Recovery status and throughput.

New Event Annotations built specifically for SAP allow you to surface system events directly on monitoring dashboards to help empower you to quickly identify the root cause or see the impact of events on your system’s performance and health. These events are also now available outside of Workload Manager in Cloud Monitoring dashboards.

SAP Availability:

Pacemaker cluster:

Pacemaker cluster node status
Pacemaker cluster resource status

SAP HANA Database:

SAP HANA instance status
SAP HANA service status

SAP NetWeaver:

SAP NetWeaver instance status
SAP NetWeaver service status

SAP Operations:

SAP HANA System Replication status
SAP HANA Backup status

SAP HANA Data backups
SAP HANA Log backups

For example, in the following screenshot we can see how a SAP HANA database failover impacted the database availability and see the series of events as the Pacemaker cluster moved the database operations to the secondary node.

Other key features and benefits:

Comprehensive metrics: The solution collects a wide range of metrics from your SAP applications and Google Cloud infrastructure, but if you are looking for more, you can create your own custom queries and add the metrics to your custom dashboards inside Workload Manager Observability.
Customizable dashboards: Modify the dashboards to create alternative views to help visualize what matters most to your business and allow for faster identification of critical issues
Alerting and notifications: The dashboards are natively integrated with Cloud Monitoring and Alerting. You can set up alerts for specific metrics and receive notifications when thresholds are breached
Automated system discovery: The Agent for SAP automatically identifies and reconciles your SAP instances and resources when enabled, saving you valuable time and avoiding manual tagging or labeling

Getting started

Ready to experience the benefits of a single-pane-of-glass for SAP observability on Google Cloud? You can view detailed documentation and instructions on how to get started and the supported architectures here. The observability service in Workload Manager is available at no additional cost, but the underlying metrics and logs are subject to costs associated with Cloud Monitoring and Cloud Logging. You can view an estimated cost for the required features that must be enabled here.

If you would like assistance onboarding or would like a demo or more information, please contact your account representative or Google Cloud support and we will be in touch.

Looking ahead

We are committed to continuously improving SAP observability on Google Cloud and plan on adding new features and more correlation capabilities and insightful visualizations.

Unlock 66% better price-performance with new M4 VMs for memory-intensive workloads

Mon, 09 Jun 2025 16:00:00 +0000

Today, we're excited to announce the general availability of the memory-optimized machine series: Compute Engine M4, our most performant memory-optimized VM with under 6TB of memory.

The M4 family is designed for workloads like SAP HANA, SQL Server, and in-memory analytics that benefit from higher memory-to-core ratio. The M4 is based on Intel’s latest 5th generation Xeon processors (code-named Emerald Rapids), with instances scaling up to 224 vCPUs and 6TB of DDR5 memory. M4 offers two ratios of memory to vCPU, allowing you to choose to upgrade your memory-optimized infrastructure. They are offered in predefined shapes with a 13.3:1 and 26.6:1 memory/core ratio, for instance shapes ranging from 372GB to 6TB, with complete SAP HANA certification in all shapes and sizes.

M4 VMs are also engineered and fine-tuned to deliver consistent performance, with up to 66% better price-performance compared to our previous memory-optimized M3¹. The M4 outperforms the M3 with up to 2.25x² more SAPs, a substantial improvement in overall performance. Additionally, M4 delivers up to 2.44x better price performance compared to the M2³. To support customers' most business-critical workloads, M4 offers enterprise-grade reliability and granular controls for scheduled maintenance, and is backed by Compute Engine’s Memory Optimized 99.95% Single Instance SLA — important for business-critical in-memory database workloads such as SAP.

“We are excited to announce our collaboration with Google Cloud to bring the power of the 5th Gen Intel Xeon processors to the first memory-optimized (M4) instance type among leading hyperscalers. This launch represents a significant milestone in delivering cutting-edge performance, scalability, and efficiency to cloud users for large-scale databases such as SAP Hana and memory-intensive workloads. The new M4 instance delivers advanced capabilities for today and future workloads, empowering businesses to innovate and grow in the digital era.” - Rakesh Mehrotra, VP & GM DCAI Strategy & Product Management, Intel

A full portfolio of memory-optimized machine instances

M4 is just the latest in a long line of Compute Engine’s memory-optimized VM family. We introduced the M1 in 2018 for SAP HANA. M2 followed in 2019, supporting larger workloads. In 2023, we introduced M3, with improved performance and new features. X4 launched in 2024, supporting the largest in-memory databases, with up to 32TB of memory, making Google Cloud the first hyperscaler with an SAP-certified instance of that size.

“For years, SAP and Google Cloud have had a powerful partnership, helping businesses transform with RISE with SAP on Google Cloud. Now, fueled by the enhanced performance, high reliability, and cost efficiency of M4 machines, we're accelerating our mission to deliver even greater value to our shared customers.” - Lalit Patil, CTO for RISE with SAP, Enterprise Cloud Services, SAP SE

Today, both customers and internal Google teams are adopting the M4 to take advantage of increased performance, new shapes, and Compute Engine’s newest innovations.

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Powered by Titanium

M4 is underpinned by Google’s Titanium offload technology, enabling ultra low-latency with up to 200 Gb/s of networking bandwidth. By offloading storage and networking to the Titanium adapter, host resources are preserved for running your workloads. Titanium also provides M4 with enhanced lifecycle management, reliability, and security. With Titanium’s hitless upgrades and live migration capabilities, most infrastructure maintenance can be performed with minimal to no disruption, helping to ensure predictable performance. Additionally, Titanium’s custom-built security hardware root-of-trust further strengthens the security of customer workloads.

Next-level storage with Hyperdisk

M4 VMs come with the latest Hyperdisk storage technology, now available in both Hyperdisk Balanced and Hyperdisk Extreme options. With up to 320K IOPS per instance, Hyperdisk Balanced delivers a blend of performance and cost-efficiency for a wide range of workloads, handling typical transactional throughput and moderate query volumes effectively. Hyperdisk Extreme pushes the boundaries of storage performance, up to 500K IOPS and up to 10,000 MiB/s of throughput per M4 instance for the most demanding applications such as SAP HANA’s in-memory database operations, which require low-latency access to large datasets. You can attach up to 64 Hyperdisk volumes per M4 VM, with up to 512 TiB of total capacity, with a mix of Balanced and Extreme volumes.

Hyperdisk’s benefits go beyond raw performance. It allows you to dynamically tune IOPS and bandwidth in real time, so your workloads consistently have the resources they need. Hyperdisk storage pools, available for Hyperdisk Balanced volumes, support capacity pooling and flexible allocation of storage resources, optimizing both utilization and cost-efficiency. As a result, Hyperdisk delivers not only high performance and flexibility but also a significant reduction in total cost of ownership (TCO) compared to traditional storage solutions. The combination of Hyperdisk's advanced features and Titanium's storage acceleration offloads storage processing from the CPU, frees up compute resources, and enhances overall M4 performance.

SAP certifications

Building on existing SAP certifications on Google Cloud—including X4 for SAP ASE and C4 for SAP Adaptive Server - M4 machines are certified for SAP HANA and SAP NetWeaver-based Application workloads. For transactional and analytical applications deployed on the SAP HANA database, please reference the certified and supported SAP HANA Hardware directory.

For SAP applications, including SAP NetWeaver-based applications deployed on non-SAP HANA databases (SAP ASE, DB2, SQL Server), such as SAP Business Suite and SAP Business Warehouse (BW), SAP certifications are available for the following machine shapes: 372GB, 744GB, 1,488GB, 2,976GB and 5,952GB. You can find more information on supported SAP applications in SAP Note 2456432.

Get started today

Whether you're running advanced analytics, complex algorithms, or real-time insights for critical workloads on databases like SAP HANA and SQL Server in the cloud, M4 VMs provide the performance, features, and stability to meet your business needs. With high-performance infrastructure designed to handle massive datasets, M4 VMs offer robust memory and compute capabilities that can meet the needs of your most demanding workloads.

M4 instances are currently available in us-east4, europe-west4, europe-west3, us-central1 and will be coming to additional regions. Like other instances of the M machine family, you can purchase them on-demand or committed use discounts (CUDs). For more, see the M4’s predefined compute resource pricing or start using M4 in your next project today.

_{1. M3-megamem-64 compared to M4-megamem-56. Performance based on the estimated SPECrate®2017_int_base performance benchmark score
2. M4-megamem-224 comparing to M3-megamem-128
3. M4-ultramem-224 comparing to M2-ultramem-208}

SAP & Google Cloud: Enabling faster value and smarter innovation for business excellence

Tue, 20 May 2025 14:45:00 +0000

SAP and Google Cloud are deepening their collaboration across data analytics, AI, security, and more to deliver what customers need most: faster paths to business value, lower risk on complex projects, and smart, enterprise-ready innovation that’s built to serve real workloads — not hypothetical use cases.

At SAP Sapphire 2025, we are excited to highlight multiple updates that will simplify how customers access SAP data with BigQuery, power new AI agents and capabilities with Gemini and Agentspace, and bring Google Cloud’s leading infrastructure to SAP customers’ most demanding workloads.

AI collaboration that drives business value

AI is at the core of work between SAP and Google Cloud. Today, we’re highlighting innovations that will help enterprise customers bring our leading AI technology to SAP data and systems, enabling measurable impact without rebuilding everything from scratch.

Building AI-powered applications: The Vertex AI platform provides full access to leading foundation models, an SDK for SAP's ABAP language, and Model Garden: a single place to search, discover, and interact with models from Google and Google partners with pre-integrated models. For SAP customers, these capabilities include improving business processes like invoice resolution, enabling generative AI chatbots that provide faster, more accurate customer service experiences, and generate personalized marketing content — all with data from SAP systems.
Bringing Gemini to SAP Joule: SAP continues to build and refine Joule, its native agentic intelligence layer that enables AI-powered agents to operate across SAP applications. Now, with the addition of newer Gemini models embedded into the SAP’s Generative AI Hub on SAP Business Technology Platform (BTP), those agents can leverage Google Cloud’s most advanced language models to power more intelligent, autonomous behavior. With 10 SAP BTP regions available on Google Cloud globally, customers can now utilize these capabilities to scale AI agent applications that comply with enterprise requirements for governance, data locality, and operational control.
Accessing SAP data in Agentspace: Google Agentspace unifies access to enterprise agents and applications including SAP agents, offering users a single place to streamline task automation and secure enterprise knowledge access across various systems, applications, and data formats. This empowers employees to leverage enterprise intelligence within their current tools, regardless of its location, including in popular partner CRM, IT, and data platforms. Accessing SAP data in Agentspace improves access to AI agents, structured and unstructured data, and contextual recommendations, all within the employee's existing environment.
Enabling Agent2Agent interoperability: SAP supports and is contributing to Google Cloud’s Agent2Agent (A2A) interoperability protocol, which enables AI agents across platforms to securely exchange information, share context, and work together to achieve business outcomes. For example, an SAP orchestrator can utilize A2A to trigger a Vertex AI agent using BigQuery with full context, replacing manual, brittle integrations with autonomous, standards-based collaboration.
AI-powered SAP operations with Gemini: As customer adoption of RISE with SAP continues to grow, SAP and Google Cloud are partnering on AI co-innovations to deliver faster, more intelligent SAP operations at scale. As part of this effort, we have co-developed specialized AI agents with SAP, powered by the latest Gemini models, to prevent outages, optimize performance, and accelerate troubleshooting.

As an example, AMD is leveraging Google's AI capabilities to improve user experiences with SAP. The company developed several gen AI chatbots that allow finance, HR, and customer service teams to use natural language to find the information they need from SAP systems. One customer operations chatbot pulls data related to order scheduling and deliveries to help answer customers' questions quickly, while a finance chatbot built with Vertex AI and Cortex Framework helps accelerate cash-flow forecasting.

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Unlock and enrich the value of enterprise data

Enterprise data is only truly valuable when it’s connected, current, and actionable. Customers can leverage the speed of BigQuery, enhanced by Cortex Framework, to accomplish this. Cortex provides prebuilt models for key systems (like SAP, Google Ads, and other enterprise data sources), simplifying connections to disparate data and integration of real-time signals. This serves to build a reliable data model from your existing truth that’s ready for BigQuery's native ML to help you proactively act on opportunities, enhancing AI readiness, analytics, and operational agility.

Suzano, the world's largest pulp company and a Google Cloud RISE with SAP customer, uses Cortex to centralize its vast operational data, which was previously difficult for its global workforce to access. The company then developed a gen AI tool that translates employees' natural language questions into SQL queries, allowing non-technical users to easily retrieve insights from their SAP data. This significantly democratized data access, led to a 90% reduction in data consultation time, and enabled faster, more informed decision-making across the organization.

SAP and Google Cloud are continuing to jointly engineer data integrations between SAP source systems and BigQuery using SAP Business Data Cloud, making SAP data instantly available for AI, analytics, and visualization — without moving workloads off SAP. Customers can build new intelligence pipelines using tools they already know and with data they already trust.

Leading infrastructure for SAP workloads

Choosing the right cloud infrastructure is critical for your SAP systems. Google Cloud now offers new SAP-optimized virtual machines (M4 and C4D families) designed to directly boost your business performance and efficiency. M4, generally available, offers the most performant memory-optimized VM Compute Engine instances, with up to 127% better performance at 36% better TCO compared to previous generations. This means you can run your core SAP workloads significantly faster while reducing costs.

Google Cloud infrastructure is designed from the ground up for exceptional reliability and security, now supporting industry-leading single instance 99.95% uptime service level agreement (SLA) to minimize disruption to your business critical operations. Plus, with our expanded large-scale X4 instances, you can operate even your most demanding S/4HANA environments under RISE confidently at enterprise scale, ensuring your IT foundation scales with your business ambitions, not against them.

Enhancing security and compliance

Google Cloud safeguards your critical SAP systems and valuable business data through a comprehensive, multi-layered approach to security, starting with secure-by-design global infrastructure and data encryption by default, to reduce risk from the get-go. This is enhanced by Google Unified Security which provides precise access controls, continuous monitoring, and centralized security management, for proactive threat visibility across your SAP landscape. For sensitive SAP workloads, especially in the public sector, Google Cloud enables compliance through the differentiated Assured Workloads control platform, which is supporting ITAR for SAP Ariba and RISE with SAP. This combination of Google Cloud solutions helps ensure compliant operations while enabling rapid detection, investigation, and neutralization of sophisticated threats, to minimize impact on the business and enhance operational resilience.

What’s next: Learn, try, build

SAP customers seek clear wins: faster time to value, simplified architectures, and improved utilization of their existing data and systems. This is precisely what SAP and Google Cloud are building together. We expect Google Cloud to deliver even greater value in 2025 and beyond with our advanced enterprise AI and planet-scale cloud infrastructure.

Visit us at SAP Sapphire to explore what’s possible with the advances we have been sharing here and elsewhere in recent weeks:

Learn how Google Cloud's approach to enterprise AI translates into real-world value for our SAP customers. See hands-on demos of AI-assisted SAP workflows using Google Agentspace.
Get details on the A2A protocol and agentic integration scenarios.
See how RISE with SAP on Google Cloud infrastructure is engineered for scale, security and reliability — and proven in the field.
Discover how Google’s security solutions are protecting SAP’s customers’ most valued data and operations.

Google Cloud and SAP: Powering AI with enterprise data

Wed, 18 Dec 2024 17:00:00 +0000

As the 2027 end of support for SAP Business Suite 7 approaches, SAP customers need to decide where to deploy as they upgrade to cloud-based S/4HANA and RISE with SAP. This represents a great opportunity to get more value out of your enterprise data, and take advantage of the longstanding partnership between Google Cloud and SAP. RISE with SAP on Google Cloud lets you accelerate innovation and reduce costs through a secure, reliable, and scalable high-performance infrastructure. By deploying SAP on Google Cloud, you can accelerate your ERP transformation with a unique, unified data experience that offers leading integration, analytics accelerators, and AI innovations to bring clarity from data to decisions.

Two data powerhouses unite

Key to the Google Cloud-SAP partnership is the integration between BigQuery, a fully managed, AI-ready data analytics platform that helps you maximize value from your data, and SAP Datasphere. BigQuery is designed to be multi-engine, multi-format, and multi-cloud. This integration lets you access your most critical data in real time without duplication thanks to co-engineered data replication and federation technologies. This joint capability can unify data from SAP software systems, such as SAP S/4HANA and SAP HANA Cloud, providing organizations with a comprehensive view of their most important data on Google Cloud and letting you:

Simplify data landscapes. Federate queries across SAP Datasphere and BigQuery to blend data from SAP and non-SAP software. This minimizes common data silos from sources that span marketing, sales, purchasing, finance, supply chain, manufacturing and more.
Improve decision-making. Gain a more holistic view of your data and leverage powerful analytics to drive better decision-making. Now, you can plan with a single, comprehensive view of your businesses by connecting SAP data to powerful data and analytics tools such as Vertex AI to analyze financial and business outcomes while improving the accuracy of models.
Add rich context to your analytics. BigQuery makes it easy to bring in Google and third-party data sources such as Trends, Weather, Maps, world events and Enterprise application data with Google Cloud Cortex Framework’s pre-built accelerators.
Use SAP Business Technology Platform (SAP BTP) globally on Google Cloud. SAP is advancing its multi-cloud offerings by expanding regional support of SAP BTP and SAP HANA Cloud on Google Cloud, which includes support for SAP Analytics Cloud and SAP Datasphere. SAP and Google Cloud intend to launch SAP BTP in five new regions, building to a total of eight regions supported by 2025.

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Transform your business with AI

Google Cloud has powerful, easy-to-use tools to help you incorporate your SAP data into predictive and generative AI initiatives. Vertex AI provides a single, integrated development platform where you can build sophisticated predictive and generative AI agents and experiences faster — without any manual ETL.

Innovate freely with Model Garden, a curated collection of over 150 machine learning models. Google is the only cloud provider to offer widely used first-party, third-party, and open-source models, so you can easily discover and choose foundation models based on modality, size, performance, latency, and cost.
Leverage Google’s most powerful model yet. Gemini is Google’s most capable and general family of LLMs, offering four models each built for its own set of use cases. Google Cloud recently announced multiple Gemini updates that enable SAP users to bring more gen AI capabilities to SAP workloads and access Google Cloud’s large language models through SAP GenAI Hub.
Get more from your models by augmenting and grounding them with SAP data. Leverage Vertex AI Model Builder’s managed tooling for extensions, function calling, and grounding. Customize Gemini models in an efficient, lower-cost way with supervised tuning.
Easily deploy, manage, and monitor agents with Vertex AI Agent Builder, which lets you quickly create a range of generative AI agents grounded with Google Search and your SAP data with the convenience of a no-code agent builder console.

Run SAP today on tomorrow’s infrastructure

Google Cloud helps SAP customers build quickly, securely, and cost effectively with the next generation of infrastructure designed to meet specific workload and industry needs. Google Cloud infrastructure is optimized for AI, cloud-first, enterprise workloads with an emphasis on security, scalability, and data sovereignty.

Leverage superior scale-up machine types. Google Cloud is the sole provider of 32TB SAP-certified machines, simplifying architecture, deployments, and administration. More recently, Google Cloud introduced memory-optimized X4 instances, which provide the largest SAP-certified compute instances in the cloud market, supporting up to 32TB SAP HANA workloads.
Accelerate time to value. Google Cortex for SAP Framework delivers pre-built analytical and AI models based on SAP data models and with out-of-the-box integration with SAP. Cortex comes with pre-built dashboards for visualizing SAP data and enriches data with AI/ML services and external data sets such as weather, search trends, ads impressions, and more.
Increase agility and scalability. Unlike on-premises infrastructure, Google Cloud offers on-demand scalability to massive scale if needed, allowing you to easily adjust resources based on changing business needs. This agility can be crucial for responding to market fluctuations or unexpected growth.
Improve performance and efficiency. Google Cloud's infrastructure is designed for high performance and reliability. This can lead to faster processing times and reduced latency for your SAP applications, improving overall efficiency and the user experience.
A highly secure cloud. While customers are growing concerned about the recent increase in DDoS attacks, threat vulnerability, and security-born outages, Google Cloud’s customers have been appreciative of our consistency in availability. With robust security features and compliance certifications, Google Cloud can help give you peace of mind knowing your data is secure and your business meets regulatory requirements.
Meet sustainability goals. SAP and Google Cloud are exploring ways to combine SAP Datasphere with broader ESG data sets and insights powered by Google Cloud to accelerate sustainability journeys with actionable insights.

Real-world results with RISE on Google Cloud

SAP customers are already getting more out of their technology investments by migrating to Google Cloud.

Hunkemöller
Hunkemöller, a leading European lingerie brand with over 850 stores in 22 countries, aimed to enhance its customer experience and support its omnichannel growth strategy. The company migrated its SAP environment and IT infrastructure to Google Cloud using RISE with SAP. This move allowed Hunkemöller to leverage Google Cloud's data and analytics capabilities, enabling more precise customer segmentation and personalized recommendations, leading to improved customer experiences and reduced returns.

"By moving our on-premise data to the cloud and leveraging Google Cloud technologies, we can provide our customers with the best possible customer experience—digitally driven and supported by data. Developments happen at lightspeed in retail, and we want to be a market leader when it comes to digital applications and use of data for a better customer experience and operation of the business. We worked intensively with experts from Google Cloud and partners to realize the blueprint for cloud migration.” - Gordon Smit, Global IT Director, Hunkemöller

Cementos Pacasmayo
A leading producer of construction solutions in Northern Peru, Cementos Pacasmayo built a data ecosystem using the Cortex Framework, SAP, and Vertex AI on Google Cloud to provide stakeholders across all departments with fast, broad, and deep visibility into data.

“Before, three people had to work for eight hours to generate a business analysis. Now business users don't have to wait for computer scientists or data analysts. They can act autonomously to immediately gain valuable insights thanks to automation and rich, centralized information.” - Franz Zárate, Technical Tribe Lead Data & Analytics, Cementos Pacasmayo

This is just the beginning

Google Cloud and SAP continue to collaborate, with new co-innovations coming online all the time, making Google Cloud a compelling choice for your SAP modernization initiative. Together, Google Cloud and SAP have made it easy to activate your SAP data with Cloud Cortex Framework and Vertex AI. Now you can enable advanced analytics and build cutting-edge AI/ML and generative AI applications, retain end-to-end business context for enterprise AI, and improve time-to-AI enterprise realization with instant access to your SAP data, all without thousands of integration and development hours.

Learn more about SAP on Google Cloud here.

Achieve peak SAP S/4HANA performance with Compute Engine X4 machines

Mon, 16 Dec 2024 17:00:00 +0000

Enterprise workloads like SAP S/4HANA present unique challenges when migrating to a public cloud, making the choice of a cloud provider critically important. As an in-memory database for large SAP deployments, SAP HANA can have massive memory and CPU processing requirements, and that can just be the beginning of the challenges. Businesses are generating, processing, and making business decisions on more data than ever before, and they require increasingly complex data analysis, algorithms, and reporting. SAP provides the real-time operational and historical analytics and insights businesses need to make informed decisions quickly. However, this requires machines that can process and analyze large volumes of data in real time, demanding high levels of memory and compute power.

To meet these demands, we recently introduced X4 machine types. The Compute Engine X4 machine family is purpose-built to handle the demanding requirements of SAP HANA Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) workloads. These machines deliver strong performance, scalability, and reliability, empowering businesses to unlock the full potential of their SAP S/4HANA, SAP Business Suite (ECC) on SAP HANA deployments, and SAP’s Industry Solutions. X4 is also built to support OLAP workloads such as SAP BW/4HANA and SAP BW on HANA.

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Uncompromising performance in a scalable solution

As businesses grow, whether organically or via acquisitions, they often risk hitting CPU and memory limitations of their SAP HANA system. This forces them to upgrade to larger scale-up machines earlier or using multiple machines in a scale-out configuration. Scaling out is a complex custom process that requires application data redesign and approvals from SAP, as well as being costly from an operational and resource perspective. In addition, the planned downtime required for these migration operations can be unacceptable for organizations that rely on SAP for mission-critical operations.

X4 solves these challenges by allowing businesses to grow further in scale-up mode before hitting performance bottlenecks. X4 is available in 16TB, 24TB, and 32TB memory configurations and 960, 1440, 1920 vCPU cores respectively with “standard sizing” SAP certification for both SAP HANA OLTP and OLAP capable of running the most demanding enterprise SAP HANA workloads. X4 machines also boast scale-out OLTP certifications for up to four nodes the size of the servers, for a total of 128 terabytes for S/4HANA use cases — larger than any other cloud provider’s. The X4 16TB machines achieved an SAP Benchmark IaaS SAPS result that is over 8% higher than the closest IaaS cloud’s. (Source: SAP note 2456432 - Logon required).

As the only cloud IaaS provider offering a 32TB SAP-certified machine, Google Cloud helps ensure that your SAP HANA environment grows seamlessly with your business needs while providing a cost-effective and simple cloud-native experience. Here’s how:

Industry-leading compute and storage: The Google Cloud X4 machine family gains its power and scale through a combination of powerful hardware and software optimizations. Integration with Google Cloud Hyperdisk provides high performance, scalability, and resilient block storage. Hyperdisk provides dedicated, dynamically tunable read/write operations per second (IOPS) and throughput with each volume up to 5GB per second, delivering substantially higher performance compared to the previous generation of Persistent Disk. This level of performance is crucial for applications that require rapid data access, like databases, real-time analytics, and reduces SAP HANA rehydration times. Additionally, X4 machines run on one of the world’s largest privately managed networks, offering low-latency performance.
High availability and reliability: Minimizing downtime for mission-critical SAP applications is a top priority for customers. X4 machines have an industry-leading 99.95% Compute Engine Memory-Optimized Single Instance SLA. Paired with Hyperdisk, X4 enables rapid SAP HANA rehydration capabilities (<45 min full rehydration for 32TB) that minimize application business process downtime, so your mission-critical SAP applications stay up and running.
Performance-boosting innovation: Titanium is a hardware- and software-based technology designed to significantly enhance workload performance, efficiency, and security while also simplifying management by automating many infrastructure-level tasks. Titanium shifts networking and storage functions away from the machine’s CPU to specialized hardware, allowing the machine’s CPU to focus on running SAP HANA applications. Titanium’s tight integration with Google Cloud's Hyperdisk block storage service allows for best-in-class storage I/O performance (up to 400k IOPS per instance), surpassing what's typically possible with traditional architectures.
Enhanced security and compliance: X4 machines inherit Google Cloud's robust security features, including encryption of data in transit and at rest as well as compliance with industry standards and regulations with support for Google Cloud’s Assured Workloads. Titanium enhances security feature performance by offloading security-sensitive tasks like encryption and key management to dedicated hardware with enhanced protections. This helps improve the security posture of workloads, reduces the risk of vulnerabilities, and enables customers to meet their compliance and regulatory requirements.
Simplified cloud-native experience: X4 machines offer the benefits of a cloud-native architecture for SAP S/4 HANA, integrating seamlessly with Google Cloud's ecosystem and providing access to a wide range of cloud services. Compute Engine also offers a seamless migration experience for X4. You can easily migrate your SAP instance from M2 servers (up to 12 terabytes) to X4. The migration process from other servers or on-prem environments to X4 is the same as the standard process for migrating to any other Google Cloud server.
A choice of service model: When migrating to Google Cloud, SAP customers have two choices. You can choose a direct (BYOL) deployment model, or you can take advantage of RISE with SAP, which brings solutions and expertise from SAP and technology ecosystem partners into one single-contract subscription offering.

“In the past few years, our SAP HANA systems have seen significant data growth with an increasing need for higher performance. With the 24TB X4 machines and Hyperdisk storage, we have been able to raise the ceiling for our future data growth and are also looking to see improvements in our performance. Added to this, Google’s X4 machines are cloud native, giving us opportunities to automate system management and operations.” - Shawn Lund, US Chief Technology Officer, Deloitte

Google Cloud's X4 machines represent a significant advancement in SAP HANA infrastructure, offering high performance, scalability, and cost-efficiency. By integrating with Google Cloud's powerful ecosystem and providing a cloud-native experience, X4 machines empower businesses to unlock the full potential of their SAP S/4HANA deployments and drive digital transformation.

Learn more about X4 machines and RISE with SAP on Google Cloud. View SAP Datasphere for Google BigQuery on Google Cloud Marketplace.

Get cost-effective protection for SAP HANA with Backup and DR Service

Fri, 06 Dec 2024 17:00:00 +0000

Like many businesses, your SAP HANA database is the heart of your SAP business applications, a repository of mission-critical data that drives your operations. But what happens when disaster strikes?

Protecting a SAP HANA system involves choices. Common methods include HANA System Replication (HSR) for high availability and Backint for backups. But while having a disaster recovery (DR) strategy is crucial, it doesn't need to be overly complex or expensive. While HSR offers rapid recovery, it requires a significant investment. For many SAP deployments, a cold DR strategy strikes the perfect balance between cost-effectiveness and recovery time objectives (RTOs).

What is cold DR? Think of it as your backup plan's backup plan. It minimizes costs by maintaining a non-running environment that's only activated when disaster strikes. This traditionally means longer RTOs compared to hot or warm DR, but significantly lower costs, and while often deemed sufficient, any improvement on RTO and lower cost is what businesses are often in search of.

Backint, when paired with storage (e.g. Persistent Disk and Cloud Storage) enables data transfer to a secondary location, and can be an effective cold DR solution. However, using Backint for DR can mean longer restore times and high storage costs, especially for large databases. Google Cloud is delivering a solution addressing both the cost-effectiveness of cold DR and the rapid recovery of a full DR solution: Backup and DR Service with Persistent Disk (PD) snapshot integration. This innovative approach leverages the power of incremental forever backups and HANA Savepoints to protect your SAP HANA environment.

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Rethinking SAP disaster recovery in Google Cloud

Backup and DR is an enterprise backup and recovery solution that integrates directly with cloud-based workloads that run in Google Compute Engine. Backup and DR provides backup and recovery capabilities for virtual machines (VMs), file systems, multiple SAP databases (HANA, ASE, MaxDB, IQ) as well as Oracle, Microsoft SQL Server, and Db2. You can elect to create backup plans to configure the time of backup, how long to retain backups, where to store the backups (regional/multi-regional) and in what tier of storage, along with specifying database log backup intervals to help ensure a low recovery point objective (RPO).

A recent Backup and DR feature offers Persistent Disk (PD) snapshot integration for SAP HANA databases. This is a significant advancement because these PD snapshots are integrated with SAP HANA Savepoints to help ensure database consistency. When the database is scheduled to be backed up, the Backup and DR agent running in the SAP HANA node instructs the database to trigger a Savepoint image, where all changed data is written to storage in the form of pages. Another benefit of this integration is that the data copy process occurs on the storage side. You no longer copy the backup data through the same network interfaces that the database or operating system are using. This results in production workloads retaining the compute and networking resources, even during an active backup

Once completed, Backup and DR services trigger the PD snapshots from the Google Cloud storage APIs, so that the image is captured on disk, and logs can also be truncated if desired. All of these snapshots are “incremental forever” and database-consistent backups. Alternatively, you can use logs to recover to a point in time (from the HANA PD snapshot image).

Integration with SAP HANA Savepoints is critical to this process. Savepoints are SAP HANA API calls whose primary use is to help speed up recovery restart times, to provide a low RTO. They achieve this because when the system is starting up, logs don’t need to be processed from the beginning, but only from the last Savepoint position. Savepoints are coordinated across all processes (called SAP HANA services) and instances of the database to ensure transaction consistency.

The HANA Savepoint Backup sequence using PD snapshots can be summarized as:

Tell agent to initiate HANA Savepoint
Initiate PD snapshot, wait for ‘Uploading’ state (seconds)
Tell agent to close HANA Savepoint
Wait for PD snapshot ‘Ready’ state (minutes)
Expire any logs on disk that have passed expiration time
Catalog backup for reporting, auditing

In addition, you can configure log backups to occur regularly, independent of Savepoint snapshots. These logs are stored on a separate disk and also backed up via PD snapshots, allowing for point-in-time recovery.

Operating system backups

What about the operating system backups? Good news: Backup and DR lets you take PD snapshots for the bootable OS and selectively any other disk attached directly to your Compute Engine VMs. These backup images can be also stored in the same regional or multi-regional location for cold DR purposes.

You can then restore HANA databases to a local VM or your disaster recovery (DR) region. This flexibility allows you to use your DR region for a variety of purposes, such as development and testing, or maintaining a true cold DR region for cost efficiency.

Backup and DR helps simplify DR setup by allowing you to pre-configure networks, firewall rules, and other dependencies. It can then quickly provision a backup appliance in your DR region and restore your entire environment, including VMs, databases, and logs.

This approach gives you the freedom to choose the best DR strategy for your needs: hot, warm, or cold, each with its own cost, RPO, and RTO implications.

One of the key advantages of using Backup and DR with PD snapshots is the significant cost savings it offers compared to traditional DR methods. By eliminating the need for full backups and leveraging incremental forever snapshots, customers can reduce their storage costs by up to 50%, in our testing. Additionally, we found that using a cold DR region with Backup and DR can reduce storage consumption by 30% or more compared to using a traditional backup to file methodology.

Why this matters

Using Google Cloud’s Backup and DR to protect your SAP HANA environment brings a lot of benefits:

Better backup performance (throughput) - storage layer handles data transfer rather than an agent on the HANA server
Reduced TCO through elimination of regular full backups
Reduced I/O on the SAP HANA server by avoiding database reads and the writes during the backup window that can be very long by comparison to a regular Backint full backup event.
Operational simplicity with an onboarding wizard, and no need to manage additional storage provisioning on the source host
Faster recovery times (local or DR) as PD Snapshots recover natively to the VM storage subsystem (not copied over customer networks). Recovery to a point-in-time is possible with logs from the HANA PD Snapshot. You can even take more frequent Savepoints by scheduling these every few hours, to further reduce the log recovery time for restores
Data resiliency - HANA PD Snapshots are stored in regional or multi-regional locations
Low Cost DR - Since Backup images for VMs and Databases are already replicated to your DR region (via regional or multi-regional PD snapshots), recovery is just a matter of bringing up your VM, then choosing your recovery point-in-time for the SAP HANA Database and waiting for a short period of time

When to choose Persistent Disk Asynchronous Replication

While Backup and DR offers a comprehensive solution for many, some customers may have specific needs or preferences that require a different approach. For example, if your SAP application lacks built-in replication, or you need to replicate your data at the disk level, Persistent Disk Asynchronous Replication is a valuable alternative. This approach allows you to spin up new VMs in your DR region using replicated disks, speeding up the recovery process.

PD Async’s infrastructure-level replication is application agnostic, making it ideal for applications without built-in replication. It's also cost-effective, as you only pay for the storage used by the replicated data. Plus, it offers flexibility, allowing you to customize the replication frequency to balance cost and RPOs.

If you are interested in setting up PD Async, and would like to configure this within Terraform, please take a look at one of our colleagues who created this Terraform example for how to test in a failover and failback scenario for a number of Compute Engine VMs.

Take control of your SAP disaster recovery

By leveraging Google Cloud’s Backup and DR and PD Async, you can build a robust and cost-effective cold DR solution for your SAP deployments on Google Cloud that minimizes costs without compromising on data protection, providing peace of mind in the face of unexpected disruptions.

Learn more about running SAP on Google Cloud and discover how Google Cloud Consulting can help you learn, build, operate and succeed in your cloud journey.

How The Home Depot is innovating with Google Cloud using the ABAP SDK

Fri, 18 Oct 2024 16:00:00 +0000

The Home Depot, the world's largest home-improvement retailer, has been on a transformation journey on Google Cloud since 2017. We've harnessed the power of Google Cloud to enhance our customer experience, optimize critical SAP applications, and build an efficient and integrated supply chain.

Our supply chain, fueled by a data platform on Google Cloud, is a well-oiled machine. Inventory movement across our vast network of stores, online platforms, and replenishment systems is synced in near real-time, thanks to the streaming capabilities of our data platform. This aggregated inventory data is then integrated with our SAP ERP application for financial accounting.

Traditionally, we relied on middleware platforms and third-party add-ons to integrate SAP applications with our data platform. While effective, this approach added complexity and cost to our operations. We needed a solution that would streamline the integration process, reduce costs, and accelerate development. The ABAP SDK for Google Cloud was the answer.

As seasoned ABAP developers at The Home Depot, we've been managing our SAP applications for over two decades. The ABAP SDK empowers us to leverage the capabilities of Google Cloud directly within our preferred programming language, ABAP. By handling the complexities of connectivity, authentication, data serialization, and error handling, the SDK allows us to focus on crafting business logic. This has enabled us to rapidly build and deploy a range of impactful use cases, from concept to go-live in just a few weeks. Let's explore a few use cases:

#1. Boosting financial accounting accuracy with near real-time inventory data

Historically, inventory movement in our physical and online stores was reflected in our ERP system only as aggregated financial transactions. This limited our ability to delve into the details. Now, with the ABAP SDK, we can pull thousands of inventory transactions directly from Google Cloud Pub/Sub into SAP. This provides near real-time inventory visibility, granular transaction details, and improved accuracy in financial postings.

#2. Safeguarding sensitive financial data in integrations

We use third-party systems to manage financial transactions in stores. Data from these systems are ingested into SAP daily. To protect this sensitive data, we create asymmetric keys in Google Cloud Key Management (KMS) and share the public key with these systems. The third-party systems encrypt files using the public key before sending them to SAP, where we decrypt them using Google Cloud KMS with ABAP SDK. This architecture significantly enhances the security of our financial integrations.

#3. Cutting costs and improving performance in data sharing

We have file-based integrations between SAP and various non-SAP systems, including our customer portals. These integrations handle both structured and unstructured data of varying sizes and volumes. Using the ABAP SDK, we leverage Google Cloud Storage as a landing zone for these files, providing a scalable, reliable, and cost-effective file-sharing solution.

At The Home Depot, we've taken the ABAP SDK even further by adding monitoring and error handling using the SAP Application Interface Framework. This allows us to proactively monitor the health of our interfaces, respond to issues promptly, and ensure the overall efficiency of our integrations.

Getting started with the ABAP SDK for Google Cloud is easy. You can install the On-premise or any cloud edition in your SAP application for in-place integrations or the BTP edition in your BTP ABAP environment for side-by-side integrations. Google Cloud also offers code samples and sample solutions to help you hit the ground running.

With the ABAP SDK supporting over 75 Google APIs, we've only scratched the surface of what's possible. We're constantly exploring new use cases to drive efficiencies across our integration landscape. We'd love to hear how you're using the ABAP SDK for Google Cloud to innovate and transform your business.

Google Cloud expands services in Saudi Arabia, delivering enhanced data sovereignty and AI capabilities

Mon, 19 Aug 2024 16:00:00 +0000

Building on the launch of the Google Cloud region in the Kingdom of Saudi Arabia (KSA) in November 2023, we are excited to announce new data sovereignty, security, and AI capabilities for the Dammam region. These new offerings can help support the digital transformation journeys of organizations operating in Saudi Arabia that need to meet certain regulatory requirements, including multinational enterprises operating in the Kingdom.

Sovereign Controls by CNTXT

Google Cloud is committed to working with local, trusted partners to help our customers meet digital sovereignty requirements. In Saudi Arabia, Google Cloud has partnered with CNTXT to offer Sovereign Controls by CNTXT which is now generally available. This offering, provided through Assured Workloads, is built on Google Cloud's Class C-certified infrastructure and adds additional CNTXT-operated controls to help organizations meet more stringent data sovereignty requirements. With this offering, CNTXT augments Google Cloud by offering a managed External Key Management (EKM) with Key Access Justifications (KAJ) service as well as localized support.

EKM with KAJ encrypts customer data at rest with keys stored outside Google Cloud’s infrastructure. It requires detailed justifications each time access to keys is required, offering customers the ability to deny access for any reason, including extraterritorial data requests. In this offering, CNTXT operates the external key manager in partnership with Saudi Information Technology Company (SITE) and Fortanix and configures and enforces key access policies on behalf of customers. With localized support, CNTXT ensures that support personnel for Google Cloud are Saudi-based.

CNTXT online portal

CNTXT has launched a new portal designed to streamline the procurement process for customers in the region, allowing a broad range of users to harness the power of Google Cloud’s advanced technologies. From the portal, users can easily:

Browse and purchase Google Cloud services: The portal provides a comprehensive overview of Google Cloud services available in Saudi Arabia, along with pricing information and easy-to-follow purchase options.
Manage their accounts: Users can view their account details, billing information, and service usage data, all in one place.
Get support: The portal offers access to a variety of support resources, including documentation, FAQs, and a contact form for direct assistance.

You can access the portal here.

"We’re excited to work with Google Cloud to help customers in Saudi Arabia drive their digital transformation with strong security and regulatory assurance,” said CNTXT CEO Abdullah Jarwan. “Together with Google Cloud, we are bringing unparalleled sovereign capabilities to the Google Cloud Dammam region that will benefit our public and private sector customers. This partnership and services embody our commitment to fostering technological innovation and supporting the Kingdom’s Vision 2030 by empowering individuals and small businesses with the tools they need to succeed in a digital economy.”

Google Cloud Sovereign Controls for KSA

For organizations that do not need the additional assurance of a local partner, Google Cloud's Sovereign Controls for KSA is a new control package, transacted directly with Google, that can help non-Saudi domiciled organizations deploy cloud-based applications and services in the region while adhering to local regulations and industry standards. It allows organizations to easily configure core controls such as data residency at-rest, in use and in-transit for Google Cloud services, provides monitoring of the controlled environment for compliance violations, enables administrative access transparency and approval, and optionally supports customer-managed encryption.

“Google Cloud Sovereign Controls for KSA will allow our regional customers to use the full power of the Snowflake Data Cloud to solve unique business problems while meeting local regulatory requirements." - Kunal Kapoor, Director Product Management, Snowflake

Vertex AI expansion

Google Cloud has also expanded the availability of its Vertex AI platform in Saudi Arabia, with core offerings that went live in the Dammam cloud region in May 2024. Vertex AI lets businesses harness the power of machine learning and AI to drive innovation, optimize operations, and enhance customer experiences.

Take the next step

With the introduction of these new services and capabilities, Google Cloud reaffirms its commitment to supporting the digital transformation goals of Saudi Arabia. By providing a comprehensive suite of cloud solutions tailored to the unique needs of the Kingdom, Google Cloud is empowering organizations to innovate, grow, and thrive in the digital age.

Now GA: Compute Engine C3 bare-metal and X4 instances

Thu, 01 Aug 2024 12:00:00 +0000

Enterprise workloads present unique challenges when migrating to a public cloud. Whether it’s a 32TB in-memory database, a private cloud built on a commercial hypervisor, or an application that can’t run in a virtual machine, these business-critical workloads are a high-priority for technology leaders to migrate to the cloud.

To help ease and accelerate migrating these workloads, we're excited to announce that Compute Engine’s X4 and C3 bare-metal machine types are now generally available. These machine types address unique compute needs within the general-purpose and memory-optimized families:

The new X4 instance series includes three new instance types to address extra-large in-memory databases such as SAP HANA.
Three new C3 bare-metal shapes cater to a variety of applications, such as commercial and custom hypervisors, that require direct access to CPU and memory resources.

Underpinning X4 and C3 is Titanium, Google Cloud’s system of purpose-built custom silicon and multiple tiers of scale-out offloads. By freeing up the CPU, Titanium provides performance, reliability, and security improvements for a variety of workloads. In fact, Titanium is the foundation to all third-generation and newer Compute Engine machine types.

“Intel and Google recognize the unique needs of enterprises migrating to the cloud. Through our collaboration on X4 and C3 Bare-metal instances powered by 4th Gen Intel Xeon processors, we're providing businesses with unique instances and performance enhancements along with the flexibility and power they need to seamlessly transition even their most complex workloads, unlocking the full potential of the cloud.” - Suzi Jewett, General Manager - Intel Xeon Products, Intel Corporation

Now GA: X4 for extra-large memory-intensive workloads

Powered by 4th Generation Intel Xeon Scalable processors, X4 offers industry-leading compute and block storage performance, with up to 1,920 vCPUs and 32TB of DDR5 memory. X4 instances are ideal for extra-large, memory-intensive workloads such as relational in-memory databases and graph in-memory databases, and are offered in three configurations:

Machine Type	Cores (Hyper threaded)	Memory (GB)	Storage	Standard Networking
x4-megamem-960-metal	960	16,384	Hyperdisk	100Gbps
x4-megamem-1440-metal	1440	24,576	Hyperdisk	100Gbps
x4-megamem-1920-metal	1920	32,768	Hyperdisk	100Gbps

Uncompromising performance and availability for all memory sizes

As an application’s in-memory database grows, database administrators and architects need to be able to scale their workloads without sacrificing performance. X4 offers a 17:1 Memory / Core ratio for all three of its instance shapes to help ensure performance scales with size In fact, X4 has achieved the highest SAPS benchmark certification results of any hyperscaler for Intel servers. This instance shape’s design is one reason why X4 is the only 32TB hyperscaler instance certified by SAP and the only hyperscaler instance certified for 24TB and 32TB OLTP and OLAP with SAP ‘Standard Sizing’ — no other cloud providers hold these certifications.

With support for Hyperdisk Extreme, X4 supports up to 10,000 MBps of throughput and 400K IOPS. In the unfortunate event of a node failure or restart, this block storage performance enables sub-one-hour memory rehydration time, meeting recovery time objectives (RTOs) for databases as large as 32TB. In addition, X4 is backed by Compute Engine’s Memory-optimized 99.95% single-instance SLA.

"In the past few years, our SAP HANA systems have seen significant data growth with an increasing need for higher performance. With the 24TB X4 machines and Hyperdisk storage, we have been able to raise the ceiling for our future data growth and are also looking to see improvements in our performance. Added to this, Google’s X4 machines are cloud native, giving us opportunities to automate system management and operations." - Shawn Lund, US Chief Technology Officer, Deloitte

A maintenance experience built for business-critical workloads

When designing the X4 maintenance experience, we consulted with enterprise customers to learn what they need to run their business-critical workloads in the cloud. We came back with three key takeaways:

Maintenance events should be rare.
Customers want control over maintenance execution.
Customers need ample upfront notice of upcoming maintenance events.

We designed the X4 instances’ maintenance experience with these takeaways as guiding principles. For one, by leveraging Titanium offloads, we achieved a drastic reduction in the number of infrastructure maintenance events that we initiate. And when a maintenance event is necessary, we give you a minimum of 60 days notice, and let you trigger that maintenance event at any time within that period.

Together, X4’s performance and reliability characteristics have impressed some of our most demanding customers and partners.

“SAP Enterprise Cloud Services has been evaluating and exploring the integration of X4 and C3 Metal systems for RISE with SAP, and has been impressed with its reliability, performance, and ease of management.” - Lalit Patil, CTO for RISE with SAP, Enterprise Cloud Services, SAP SE

Now GA: C3 bare-metal machine types

Bare-metal machine types are ideal for customers with workloads that require direct access to the machine’s CPU and memory resources, e.g., hypervisors or container platforms; aren’t supported in virtual machines; or have special performance monitoring or licensing requirements.

In particular, customers in financial services, as well as SaaS/PaaS security, dev/test and private cloud platform sectors, often need bare-metal machine types to meet their performance goals.

“We’re excited for the launch of Google Cloud's new bare metal machine types. Nutanix looks forward to collaborating with Google to help organizations capitalize on the benefits of cloud while achieving a universal hybrid multicloud operating model for their legacy and AI-enabled modern apps.” - Tarkan Maner, Chief Commercial Officer, Nutanix

C3 bare-metal instances are based on the 4th Generation Intel Xeon Scalable processors — the same raw server platform that powers C3 virtual machines (VMs). On Google Cloud, these instances exclusively provide access to Intel integrated CPU features such as Intel Quick Assist (QAT), Intel Data Streaming Accelerator (DSA), and Intel In-Memory Analytics Accelerator (IAA). They offer many of the same attributes as the largest C3 VMs, for example the same Hyperdisk storage options, and the same standard and Tier 1 bandwidth. Finally, C3 bare-metal instances have the same controlled maintenance experience as the rest of the C3 machine family. These instances are offered in three configurations:

Machine Type	Cores (Hyperthreaded)	Memory (GB)	Storage	Standard Networking	Tier 1 Networking
c3-highcpu-192-metal	192	512	Hyperdisk	100Gbps	200Gbps
c3-standard-192-metal	192	768	Hyperdisk	100Gbps	200Gbps
c3-highmem-192-metal	192	1536	Hyperdisk	100Gbps	200Gbps

A continued focus workload-optimized infrastructure

X4 and C3 bare-metal instance types are the culmination of several years of investment in the Compute Engine architecture, with the Titanium offload system at its core. Unlike the similarly named Bare Metal Solution, X4 and C3 bare-metal machine types are not limited to specific workloads or use cases; they are fully integrated, native Compute Engine instances that run on Google Cloud’s server fleet in Google Cloud data centers, and can be consumed just like any other Compute Engine VM. You can expect more bare metal shapes in future machine families, as we continue to support your infrastructure modernization efforts.

To get access to X4 instances, please contact your account team or submit an inquiry to your Google Cloud Sales Specialist.

C3 bare-metal machine types are currently available in us-central1, us-east5, us-east1, europe-west1, europe-west4 and will be coming to additional regions with C3 VMs. Like other members of the C3 machine family, you can purchase them on-demand, with committed use discounts (CUDs) or Flex CUDs. For more, see the C3’s predefined compute resource pricing.

Safeguard your SAP environments with Workload Manager’s evaluation service

Fri, 12 Jul 2024 16:00:00 +0000

As businesses embrace the cloud for their SAP workloads, compliance with best practices is critical. In this blog post, we dive into Google Cloud’s Workload Manager and show how it can help safeguard your SAP systems by providing automated, rule-based analysis to proactively identify potential misconfigurations and deviations from best practices.

The role of best practices in maintaining SAP system integrity

Configuring and maintaining large-scale deployments in the cloud can be challenging, especially when infrastructure, operating system, and application settings are all involved. Complex configurations, evolving best practices, and the potential for human error that comes with manual effort can negatively impact your SAP systems and ultimately your business.

Historically, detecting and addressing misconfigurations only happens in response to a situation, and often involves time-consuming manual checks. Workload Manager provides an evaluation service for SAP that can dramatically improve how you manage your SAP systems on Google Cloud, allowing you to:

Reduce preventable mistakes: Many issues and outages could have been avoided or mitigated by following best practices. Run scans to proactively identify potential issues before they might escalate into major problems.
Safeguard go-lives: Ensure new deployments are validated and configured according to best practices to help increase go-live success rates and resolve issues that may be difficult to change later.
Detect drift: Run scans on a recurring basis to identify any inconsistencies or misconfigurations over time.
Reduce operational overhead: Automate the validation process to help save time otherwise spent performing tedious manual checks.

Workload Manager evaluation service: an overview

Workload Manager’s evaluation service is an intelligent rule-based validation service that can automatically assess your SAP systems against an extensive set of best practices from Google Cloud, SAP, and operating system vendors.

The SAP rule catalog is frequently updated as best practices evolve and new learnings are added. The included rules go beyond simple configuration checks, delving into critical aspects of your sap environment in the following categories:

SAP General: Rules that apply to all types SAP workloads, such as VM configuration settings and requirements for support
SAP High Availability: Checks that help optimize reliability and availability by analyzing cluster configurations, failover mechanisms, and system architectures
SAP Netweaver & HANA: Logic that automatically identifies the role of each resource and then validates it against role-specific requirements like certified machine sizes, disk types, and more
SAP HANA Insights: Intelligent insights and optimizations for compression, maintenance activities, performance checks, memory allocations, and more
SAP HANA Security Best Practices: Rules that help evaluate the security posture of HANA, including access control, encryption settings, known vulnerabilities, and more

After running a scan, an evaluation report provides a summary of the results, allowing you to drill deeper into each rule to identify which individual resources passed and failed. Each rule includes a description of the issue, its severity, and a recommendation including links to the relevant documentation to help with remediation. You can also choose to be alerted through notification channels such as email or Pub/Sub based on triggers such as when a new issue is identified.

Getting started with the Workload Manager evaluation service

Set up Google Cloud’s agent for SAP on each VM in scope

Google Cloud’s agent for SAP is a consolidated agent that performs a variety of functionality related to running SAP workloads on Google Cloud. The agent is required to be installed and running on all VMs that run SAP workloads on Google Cloud (SAP Note 2456406 - SAP on Google Cloud Platform: Support Prerequisites).

In addition, the agent contains optional functionality, including the Workload Manager collecting information for analysis. Refer to the following checklist to verify the agent is installed and configured correctly: Set up Google Cloud’s Agent for SAP.

The evaluation report also includes an automatic check to verify that each in-scope VM has the agent installed and configured correctly. If you are unsure if you have already completed the above, run an evaluation as described below and check the results for the rule called “Check that Google Cloud’s Agent for SAP is set up correctly on all instances in the evaluation scope.”

Prerequisites and initial enablement

Before beginning, ensure that you have completed the prerequisites to start using the evaluation service within Workload Manager:

Enable the Workload Manager API
IAM Roles: Define the appropriate IAM roles to manage access to the evaluation service

Please note that Workload Manager uses a Service Agent, which may need additional IAM permissions based on the projects and configurations selected during the subsequent evaluation creation. It may be helpful for an administrator to create the first evaluation and grant any missing permissions as they are prompted for them; this step is only required one time per project.

Create an evaluation in Workload Manager

Navigate to Workload Manager > Evaluation in the console, which is nested under Compute in the left navigation pane, or can be found in the search bar at the top. Click the New Evaluation button at the top to begin.

On the Evaluation details tab, provide a name and description for the evaluation and select “SAP” from the Workload type dropdown menu.

On the Evaluation Scope tab, you can select which project(s) you wish to evaluate and use filters to refine the scope further.

On the Evaluation rules tab, you can select which rules you wish to include in the evaluation. Only rules that are relevant for each resource in scope will be evaluated, so you may select them all if you are unsure which to choose. For example, rules that are marked for SAP HANA would not be evaluated against rules in the SAP Netweaver category. Similarly, rules related to High Availability (HA) would not be evaluated for a non-HA system.

On the Scheduling tab, you can determine how frequently you wish to run this specific evaluation, or choose “Does not repeat” if you wish to run the evaluation on an ad-hoc basis. Even if you pick a recurring frequency, you can still run additional evaluations as needed which will not interfere with the scheduled scans.

On the Notifications tab, you can choose to receive alerts based on various triggers, such as when a new issue is found, which is integrated with Notification Channels like Email or Slack.

Finally, on the Review tab, you can revisit any selections made and click ‘Create’ to finish. The first evaluation you create in a project may take a few extra minutes to create. You will receive a notification once it has finished, which will take you back to the evaluation dashboard.

Run an evaluation and view your results

After creating a new evaluation, you can run it by selecting it from the evaluation dashboard and clicking ‘Run’, or by waiting for your next scheduled run if you set a recurring frequency.

Upon completion, Workload Manager generates a thorough report highlighting areas of compliance and deviations from best practices. You can then drill down into specific rules for detailed recommendations on the remediation, as well as identification of which resources passed and failed each check.

Best practices validation: Beyond the basics

For organizations running SAP on Google Cloud, Workload Manager and its new evaluation service is a powerful way to identify misconfigurations and deviations from best practices. For troubleshooting tips and answers to common questions, refer to the official documentation or reach out to Google Cloud customer support.

Ready to learn more? Learn more about running SAP on Google Cloud and discover how Google Cloud Consulting can help you learn, build, operate and succeed in your cloud journey.

In an AI era, forge a path to enduring business innovation with Google Cloud and SAP

Tue, 04 Jun 2024 12:00:00 +0000

Google Cloud and SAP believe the cloud should offer more than highly secure, high-performing, and reliable infrastructure. It should also provide a comprehensive, open, and multi-cloud platform that enables your business to get the most out of its data with analytics and generative AI. This is especially applicable for critical data stored on SAP systems, which span supply chains, finance, HR, and more.

By integrating Google Cloud’s generative AI and analytics solutions with SAP data, our partnership helps your organization unlock the full potential of its information to drive continuous innovation, tackle your toughest business challenges, and make smarter decisions.

At today’s SAP Sapphire conference, we’re excited to announce new advancements across AI and infrastructure to help SAP customers innovate and more effectively manage data, including:

An AI-powered solution to enable more resilient supply chains. The solution combines Google Cloud Cortex Framework and Gemini models with SAP Joule and Integrated Business Planning (IBP) for Supply Planning.
An integrated analytics offering with SAP Datasphere, now available on Google Cloud Marketplace.
The introduction of Google Cloud’s memory-optimized X4 instances, which provide the largest SAP certified compute instances in the cloud market, supporting up to 32TB SAP HANA workloads.
Regional expansions for RISE with SAP, SAP BTP, and SAP Datasphere, plus support for EU access for RISE.
Multiple Gemini updates that enable SAP users to bring more gen AI capabilities to SAP workloads and access Google Cloud’s large language models through SAP GenAI Hub.

Accelerating AI-powered resilient supply chains

As we continue to co-innovate with SAP, we are diving deeper into business-critical use cases that will help customers gain a competitive edge. Using our combined data and AI solutions to strengthen supply chain management and mitigate supply chain risks is a natural fit.

By integrating Cortex Framework and Gemini models with SAP’s generative AI assistant Joule and Integrated Business Planning (IBP) for Supply Planning, businesses can accelerate insights from sensed events, risks, and identify opportunities to enable faster, more intelligent supply chain responses.

With an AI-powered resilient supply chain, you can also help better predict demand and mitigate supply chain risk, with use cases that include:

Enhanced demand forecasting that integrates diverse data sources, such as marketing campaigns.
Mitigation of supply chain risks with proactive disruption detection and alerts, fueled by additional data sources such as weather, and event data.
Optimized operations with more precise planning, the ability to maintain optimal inventory levels, and opportunities for automation.

SAP Datasphere now available on Google Cloud Marketplace

The SAP Datasphere integration with BigQuery continues to deliver real-time access to your SAP and non-SAP data, including publicly available datasets within BigQuery and other integrated data like Google Ads, accelerated via Cortex Framework. SAP Datasphere’s Replication Flow now offers bidirectional replication and federation with BigQuery, enabling a petabyte-scale platform for analytics and data science, as well as a foundation for machine learning and gen AI using Vertex AI with Gemini. All of this is available “out of the box” with SAP Datasphere for Google Cloud, which is available on Google Cloud Marketplace.

Customers have already generated great results through Datasphere for Google Cloud, such as a major consumer electronics company that modernized its sales reporting process. Using Datasphere, BigQuery, and Google Dataform for sales pipeline automation, they built a real-time sales reporting dashboard to replace their existing PDF reports and modernize their entire reporting process. As a result, they have saved significant resources, increased operational speed, and created deeper business insights about business sales.

Introducing X4: Largest cloud instances with unparalleled performance, reliability, and security

As more global enterprises migrate to SAP S/4HANA on the cloud, the demand for more memory- and compute-intensive machines to handle giant workloads keeps growing. We are thrilled to introduce the X4 machine family, featuring 16TB, 24TB, and 32TB instances designed specifically for SAP HANA OLTP and OLAP workloads to operate with highest performance and reliability, X4 family leads the industry in multiple dimensions including:

First SAP HANA-certified 32TB instances
Offering 1920 vCPUs, more than double the number of vCPUs of other certified hyperscaler offerings and providing industry-leading compute and Hyperdisk block storage performance (up to 10,000 MBps throughput), which is enabled by Google Cloud’s unique Titanium off-load technology.
Backed by 99.95% Compute Engine Memory-Optimized Single Instance SLA, highest in the industry, the X4 Instance family ensures exceptional reliability for SAP workloads.

These systems further benefit from Google Cloud's infrastructure differentiators, including the largest network footprint delivering low-latency for SAP workloads and robust security measures such as built-in encryption and proactive threat detection.

"In the past few years, our SAP HANA systems have seen significant data growth with an increasing need for higher performance,” says Shawn Lund, US Chief Technology Officer, Deloitte. “With the 24TB X4 machines and Hyperdisk storage, we have been able to raise the ceiling for our future data growth and are also looking to see improvements in our performance. Added to this, Google’s X4 machines are cloud native, giving us opportunities to automate system management and operations."

Innovating for RISE with SAP customers

The new high-performance X4 Instance family is one example of how Google Cloud continues to invest in being the most reliable and scalable cloud provider for RISE with SAP workloads.

Lalit Patil, CTO of RISE with SAP, says, “SAP and Google Cloud have a deep co-innovation partnership, and we're continuously launching new, differentiated solutions to benefit RISE with SAP customers.

At SAP Sapphire, we're excited to announce two new offerings:

New X4 Systems for SAP RISE: SAP RISE now supports Google Cloud's latest 16, 24, and 32TB X4 systems. This co-engineered offering, which we have rigorously tested through customer POCs, will deliver the reliability and performance needed for even the largest and most demanding SAP workloads.
Enhanced Compliance for EU Customers: We're pleased to announce availability of EU Access for RISE on Google Cloud. This addresses the regulatory and compliance requirements of our European customers.”

A recent RISE with SAP customer on Google Cloud is Asian Paints. "We selected Google Cloud for RISE with SAP given their strong partnerships with SAP and their ability to manage large installations in the region,” says Aashish Kshetry, CIO, Asian Paints. “We look forward to deploying SAP S/4HANA on their latest infrastructure and platforms on Google Cloud to support our business innovations and sustained growth."

Other recent updates that solidify Google Cloud’s position as the ideal cloud partner for RISE with SAP customers include:

The expansion of the SAP BTP and Datasphere footprint, with new regions launching in Israel and Japan this quarter and in Saudi Arabia, Australia, and Brazil later this year.
The extension of the ABAP SDK for Google Cloud to SAP BTP. This makes Google Cloud the first hyperscaler to release a fully supported version of ABAP SDK on SAP BTP, which helps customers infuse their SAP business processes with AI, analytics, and automation via 55 Google Cloud APIs (e.g., Vertex AI, BigQuery, pub/sub and more).
Direct integration into Vertex AI through SAP’s Customer Database Platform (CDP), enabling enterprises to instill predictability into business operations, improve customer experiences, and accelerate growth.
Gemini Assist for SAP, a feature within Google Cloud Workload Manager (WLM) that enables SAP admins to operate SAP deployments through a natural-language interface.
Availability of Google Gemini LLMs in SAP GenAI Hub to support embedded generative AI features alongside SAP Joule across SAP’s product portfolio. Google Cloud models can enhance workloads including S/4, Ariba, SuccessFactors, and more. SAP customers will continue to have access to Google Cloud’s latest models as they are released, including Gemini Flash which was announced at Google I/O in May.

Enabling customer success with large workload

Cintas, a facilities services and supplier company that serves more than one million businesses worldwide, transformed its on-premises SAP estate with more than 200 servers and large uncompressed 130TB+ database with Google Cloud. After a lift-and-shift migration, including a RISE with SAP use case for one business unit, Cintas was able to reduce its uncompressed database to just 41TB, a 68% decrease in overhead. With a stable, fast cloud-native data management platform, the company is set to accelerate its AI and analytics journey with Google Cloud technologies like Google Cloud Cortex Framework.

Mumbai-based Mahindra & Mahindra Ltd. brought its multinational federation of 80 businesses together with one instance of the private edition of SAP S/4HANA Cloud with the first-ever RISE scale-out architecture. The company worked closely with Google Cloud and SAP experts to create the flexible distributed HANA database it needed for peak workload and realized 12% faster response times. Mahindra & Mahindra has also increased developer productivity by 35% and improved high-compute transactions by 15%. In one example, its new systems withstood the demand of selling more than 100,000 cars in just 30 minutes.

Learn more on-site at Sapphire

We're eager to learn about your plans and challenges, and to share how our continued co-innovations with SAP leverage our combined strengths to help you meet the future with confidence with optimized SAP environments on Google Cloud, including RISE.

We’re also looking forward to the SAP Analytics Cloud (SAC) Roadmap Session at Sapphire. SAP will announce exciting new SAC-BigQuery integration capabilities designed to help customers elevate planning and analysis with insights into non-SAP and unstructured data via SAC.

Visit us at Sapphire Orlando in booth #302 to meet with us in person, ask any questions you may have, or check out our demos on AI/ML, generative AI (Gemini), supply chain, sustainability, and more. Or visit https://cloud.google.com/solutions/sap to learn more immediately.

Accelerate SAP S/4HANA deployments with ‘Guided Deployment Automation for SAP’

Wed, 15 May 2024 16:00:00 +0000

We are excited to announce the general availability of Guided Deployment Automation for SAP on Google Cloud. This new service within Workload Manager helps accelerate deployment of SAP workloads on Google Cloud by allowing customers to specify what they are trying to deploy, and then incorporating opinionated guidance, best practices, and deployment automation directly into the console.

For customers who choose to deploy SAP S/4HANA on Google Cloud, this service provides several key benefits:

Efficiency: End-to-end automation simplifies the lengthy and error-prone deployment process and automates infrastructure provisioning, operating system configuration, high availability cluster setup, and installation of the chosen application
Reliability: Built-in checks and safeguards help ensure you are automatically following best-practices and the latest architecture guidance from both SAP and Google Cloud, without having to manually read through pages and pages of documentation
Flexibility: Choose to deploy in “one click” directly from the console, or generate and download the equivalent Terraform and Ansible to add to an existing deployment pipelines or customize further

There is no charge to use this deployment service, but customers pay for any of the underlying resources or other services created and used in the deployment, such as VM Instances and disks.

How does it work?

After picking from the list of supported SAP products and versions, the guided interface helps you customize and configure your workload, while the equivalent infrastructure as code (Terraform, Ansible) is generated based on your selections.When deploying directly from the console, a Cloud Build job is created to execute the Terraform and provision the required resources in your project. The exact resources created will vary depending upon your configuration, but the following diagram shows a high-level architecture for a Distributed High Availability deployment. The documentation contains additional information on the resources created during the deployment.

High-Level architecture for a Distributed High Availability deployment

In addition to the resources required for your SAP workload, a temporary VM instance is also deployed to handle the orchestration and execution of Ansible. Ansible is used to complete the remainder of the deployment process and performs tasks and operations such as the following:

Operating system configuration
Installation of HANA and initial backup
Configuration of OS Clusters
Enablement of HANA System Replication (HSR)
Installation of S/4HANA
Execution of initial database load
Installation of required agents (SAP Host Agent, Google Cloud’s Agent for SAP)

Getting started - Deploy a SAP S/4HANA workload

Before beginning, ensure that you have completed the prerequisites to use the deployment service within Workload Manager. There are a few additional prerequisites for deploying SAP workloads, such as uploading the required SAP installation files to Cloud Storage.

Afterwards, navigate to Workload Manager > Deployment in the console, which is nested under Compute in the left navigation pane or can be found in the search bar at the top. Click the Create SAP Deployment button at the top to begin.

Deployment Basics Tab:
The first tab collects basic information for the deployment and allows you to pick from the supported applications and architectures. The selections on this page help determine which information shows on the following tabs, and also will pre-populate some of the subsequent inputs.

Location & Networking Tab:
On this tab, specify where the system should be deployed, which includes the region and zone(s) and the network to use. If you have a Shared VPC configured, you can also choose to select the network from the Host Project.

External internet access is required during the deployment process, and you can choose to create external IP addresses if the chosen network does not already have access. Finally, you can specify whether a new DNS should automatically be created, or if you wish to select an existing one.

Database Tab:
Next you will begin configuring the HANA database layer, where you can enter the HANA SID and customize the instance number and VM names. Secret Manager is fully integrated to securely store any credentials used during the deployment process. You can select from a list of certified public operating systems, or choose your own Custom Image.

Afterwards, pick from the list of certified HANA machine shapes and choose your desired storage type. Disk volumes and sizes are automatically calculated based on the best practices for your chosen size.

Application Tab:
On the Application tab, you will repeat a similar process and enter information on the central services and application layer. You can make selections independently for each, for example, picking different machine sizes or operating systems for the ASCS compared to the application servers.

In addition to choosing from the list of certified machine shapes, you will also specify how many application servers should be deployed in each zone.

Preview Tab:
The final page summarizes your selections and also performs some additional proactive checks for things like quotas to prevent failures from occurring later in the process. You will also see a list of the required APIs and services that are needed in the deployment.

You can click Download Equivalent Terraform if you wish to generate and download the equivalent Infrastructure as Code to deploy in your existing automation pipeline or customize further, or you can click Create at the bottom of the page to start the deployment in the console.

Clicking Create will take you back to the deployment dashboard. You will receive a notification when the deployment has finished, which may take between 2-3 hours to complete. You can track the status and view real-time logs by clicking on the deployment and then the links for either the Terraform log or Ansible log on the subsequent screen.Post-deployment tasks

After the deployment has finished, you can connect to your SAP S/4HANA system using standard tooling such as HANA Studio or the SAP GUI by connecting using the information specified during the configuration process. View the documentation for additional information on connecting to your system.

Learn more

We’ve created a seven-minute overview and demo video that shows the above steps in action. You can also reference our public documentation for additional information on the service and how to start using it.

If you have any questions or would like to request functionality or discuss the roadmap, please contact your account manager or support team.

Seamless SAP Migration to Google Cloud: Accelerating Solenis's Digital Transformation Journey

Wed, 15 May 2024 16:00:00 +0000

Editor’s note: In this post, we’ll hear from specialty chemical manufacturer Solenis about how its migration journey to SAP on Google Cloud has supercharged its innovation and unlocked new value. Headquartered in Wilmington, Delaware, the company has 69 manufacturing facilities strategically located around the globe and employs a team of over 16,000 professionals in 130 countries across six continents

Migrating SAP to the cloud isn't just a trend; it's a strategic move transforming how businesses operate. Imagine cutting costs, boosting performance, and easily scaling your resources — that's the power of SAP in the cloud.

Consider the experience of Solenis, a leading global producer of specialty chemicals for water-intensive industries, which migrated its business to a modern digital platform in the public cloud to help improve its agility, scalability, and cost-efficiency. Owned by Platinum Equity, Solenis provides a broad array of sustainable solutions, including water treatment chemistries, process aids, functional additives, cleaners and disinfectants, as well as state-of-the-art monitoring and control systems. Customers use these technologies to improve operational efficiencies, enhance product quality, protect plant assets, minimize environmental impact, and create cleaner and safer environments.

In recent years, Solenis has grown by acquisition, leading to a complex and unwieldy IT environment. To address these challenges, Solenis decided to migrate its on-premises SAP workloads, which run its mission-critical business processes, to SAP on Google Cloud. Given its rapidly increasing memory requirements, Solenis opted to forego a hardware refresh and instead chose to leverage flexible cloud-based infrastructure with High Availability (HA) capabilities to support near-zero downtime.

Google Cloud Consulting worked with Solenis to prepare its migration teams, fill the skills gap, and successfully run SAP in Google Cloud. Together, Google Cloud Consulting and Solenis migrated the company’s SAP workloads, including SAP ERP, Global Trade Services, Adobe Document Service, GRC (governance, risk, and compliance), and many other bolt-on applications — all in less than five months.

Migrating SAP to Google Cloud

With guidance from Google Cloud Consulting, Solenis was able to minimize downtime during the migration by carefully planning and testing the process, including the performance. This helped to identify and resolve any potential issues before they could cause any disruptions to Solenis’ business operations.

During the migration, for instance, the Solenis team faced a number of performance and technical issues while working to migrate workloads from its SAP ERP Central Component (ECC) and SAP Global Trade Services applications to Google Cloud. During Q&A testing, Solenis discovered an issue with one of its on-premises components that would have caused significant project delays if not addressed promptly. Working with Google Cloud Consulting, the team was able to quickly pinpoint the root cause and implement a solution before it could impact the migration process.

Choosing the right approach to moving data from on-premises to Google Cloud was another critical step to ensure the project was completed with minimal downtime and optimal success. Working with Google Cloud Consulting, Solenis decided to implement a three-step approach that yielded a significant reduction in downtime.

Data was migrated from an on-premises server to Google Cloud using a Network File Share and rsync (a remote and local file synchronization tool). This approach reduced downtime by five to six hours.

The company also took advantage of Google Cloud's managed backup and disaster recovery services to ensure that its data was always protected throughout the migration.

“We are grateful to the Google Cloud team for their exceptional support and expertise during the migration of our SAP environment from on-premises to the cloud,” said Adrian Giboi, vice president of infrastructure and operations at Solenis. “This significant accomplishment was achieved with minimal interruption to our operations, which is a testament to the dedication and proficiency of the Google Cloud team.”

Accelerating innovation and unlocking new business value

The migration to Google Cloud has delivered a number of benefits to Solenis. For example, Solenis was able to transition from Oracle databases to SAP HANA, providing a solid foundation for future performance improvements. With real-time access to data, SAP HANA can help businesses make faster and more informed decisions, deliver a more personalized and responsive customer experience, and provide a platform for innovation.

In addition, the migration helped Solenis reduce the complexity and management overhead of its previous IT environment. Google Cloud also made it easier for Solenis to perform ongoing maintenance without business interruptions. With on-premises environments, planned maintenance activities often require downtime, which can disrupt or delay service, impact productivity, or even result in potential loss in business.

With Google Cloud, such instances can be significantly reduced. Features like live migration allow for seamless transfers of virtual machines between hosts without causing downtime for customers. Additionally, Google Cloud's 99.99% compute SLA , with instances in multiple zones, guarantees high availability, further minimizing the risk of unplanned outages. By leveraging Google Cloud's capabilities, Solenis can ensure uninterrupted service for their customers, avoiding the negative impacts of downtime. This leads to improved customer satisfaction, increased productivity, and a stronger business reputation.

Furthermore, Google Cloud's secure-by-design infrastructure and robust security features have helped Solenis to improve its security posture. The company has been able to achieve compliance with a number of industry regulations, such as ISO 27001.

Since moving to Google Cloud, Solenis has experienced a 10x increase in response and transition times, leading to improved efficiency and productivity. Overall, performance improved by 35% utilizing Google Cloud resources for compute, memory, and storage. The company has also been able to optimize costs and improve performance by taking advantage of Google Cloud's committed use discounts (CUDs) and its high-performance compute and storage capabilities.

“Our migration to SAP on Google Cloud is a crucial milestone in our company's digital transformation journey, significantly reducing our technical debt and lowering operational costs,” Giboi said. “It not only enhances our agility and scalability but also positions us to better leverage innovative cloud technologies for future growth. Google Cloud is a reliable partner in our journey towards a more efficient, flexible, and sustainable technological future.”

Get started

Ready to learn more? Learn more about migrating SAP to Google Cloud and discover how Google Cloud Consulting can help you learn, build, operate and succeed.

Make data your competitive edge with new solutions from Cortex Framework

Mon, 22 Apr 2024 16:00:00 +0000

In today’s AI era, data is your competitive edge.

There has never been a more exciting time in technology, with AI creating entirely new ways to solve problems, engage customers, and work more efficiently.

However, most enterprises still struggle with siloed data, which stifles innovation, keeps vital insights locked away, and can reduce the value AI has across the business.

Discover a faster, smarter way to innovate

Google Cloud Cortex Framework accelerates your ability to unify enterprise data for connected insights, and provides new opportunities for AI to transform customer experiences, boost revenue, and reduce costs which can otherwise be hidden in your company’s data and applications.

Built on an AI-ready Data Cloud foundation, Cortex Framework includes what you need to design, build, and deploy solutions for specific business problems and opportunities including endorsed reference architectures and packaged business solution deployment content. In this blog, we provide an overview of Cortex Framework, and highlight some recent enhancements.

Get a connected view of your business with one data foundation

Cortex Framework enables one data foundation for businesses by bridging and enriching private, public, and community insights for deeper analysis.

Our latest release extends Cortex Data Foundation with new data and AI solutions for enterprise data sources including Salesforce Marketing Cloud, Meta, SAP ERP, and Dun & Bradstreet. Together this data unlocks insights across the enterprise and opens up opportunities for optimization and innovation.

New intelligent marketing use cases

Drive more intelligent marketing strategies with one data foundation for your enterprise data, including integrated sources like Google Ads, Campaign Manager 360, TikTok and now — Salesforce Marketing Cloud and Meta connectivity with BigQuery via Cortex Framework, with predefined data ingestion templates, data models and sample dashboards. Together with other business data available like sales and supply chain sources in Cortex Data Foundation, you can accelerate insights and answer questions like: How does my overall campaign and audience performance relate to sales and supply chain?

New sustainability management use cases

Want more timely insights into environment, social and governance (ESG) risks and opportunities? You can now manage ESG performance and goals with new vendor ESG performance insights using Dun & Bradstreet ESG ranking data connected with your SAP ERP supplier data. Now with predefined data ingestion templates, data models and a sample dashboard focused on sustainability insights, for informed decision making. Answer questions like: “What is my raw material suppliers' ESG performance against industry peers?” “What is their ability to measure and manage GHG emissions?” and “What is their adherence and commitment to environmental compliance and corporate governance?”

New simplified finance use cases

Simplify financial insights across the business to make informed decisions about liquidity, solvency, and financial flexibility to feed into strategic growth investment opportunities — now with predefined data ingestion templates, data models and sample dashboards to help you discern new insights with balance sheet and income statement reporting on SAP ERP data.

Accelerate AI innovation with secured data access

To help organizations build out a data mesh for more optimized data discovery, access control and governance when interacting with Cortex Data Foundation, our new solution content offers a metadata framework built on BigQuery and Dataplex that:

Organizes Cortex Data Foundation pre-defined data models into business domains
Augments Cortex Data Foundation tables, views and columns with semantic context to empower search and discovery of data assets
Enables natural language to SQL capabilities by providing logical context for Cortex Data Foundation content to LLMs and gen AI applications
Annotates data access policies to enable consistent enforcement of access controls and masking of sensitive columns

With a data mesh in place, Cortex Data Foundation models can allow for more efficiency in generative AI search and discovery, as well as fine-grained access policies and governance.

Data and AI brings next-level innovation and efficiency

Will your business lead the way? Learn more about our portfolio of solutions by checking out our website.

ABAP SDK: Powering Alphabet’s AI/ML solutions on SAP S/4HANA

Thu, 01 Feb 2024 17:00:00 +0000

At SAP Sapphire last year, Alphabet, Google's parent company, revealed that it leverages SAP S/4 HANA systems on Google Cloud to manage its critical business operations, including Finance, Supply Chain, Logistics, Planning, and Allocations. This has allowed Alphabet to consolidate over 50 billion transactions and process multiple terabytes of data every month, and better support its global operations.

To scale its business operations, Alphabet leverages many Google Cloud products and services using the ABAP SDK. Created by Google Cloud’s SAP Engineering team, the ABAP SDK provides an accurate representation of Google Cloud APIs in ABAP, providing an integration point between SAP and Alphabet’s internal systems, powering AI/ML solutions that drive decisions, and enabling business process automation. The ABAP SDK provides in-built functionality for authentication, security, data serialization, etc., making it easier for Alphabet developers to integrate with Google Cloud products and services, and drastically decreasing time-to-value!

ABAP SDK: a story of engineering excellence

Since launching internally, ABAP SDK has been used for many Alphabet production use cases: to run mission-critical applications in finance, corporate asset management (IT, audio/video, real estate), supply chain (plan and procure to pay including forward/reverse logistics), business event notifications, exception alerting, business process monitoring, and data warehousing. Security and scalability were key requirements for Alphabet business users, which they were able to achieve quickly with the ABAP SDK. Alphabet also uses the ABAP SDK to run ML inference in the context of a SAP business transaction analytics, surfacing ML predictions.

Here are some great productionized use cases from Google Cloud for inspiration:

Stream information from SAP to multiple subscribers with Pub/Sub - SAP is the source of truth for many master and transaction data objects. SAP sends information to other applications to ensure data consistency across applications. Sub-second speed and highly reliable messaging is key. Alphabet uses SAP Streaming Pub/Sub messages for various use cases, including network equipment status for deriving trust management, order status tracking, stock availability, transaction posting status, order comments and changes exchanged from the commerce portal to the order processing team.
Use Pub/Sub for orchestration - To scale bulk data processing submitted via APIs at Alphabet, non-SAP enterprise applications use SAP OData to submit bulk updates to the SAP Application Interface Framework (AIF). SAP AIF asynchronous processing completion raises a Google Cloud CPS message to confirm processing results to the API client. ABAP SDK plays a crucial role in orchestrating many use cases like these including jobs, business events, and logs.
Automate translation of finance documents to multiple languages - SAP S/4 is the source of truth for statutory reporting in multiple local languages. Alphabet boundary systems send journal entry data in English, but the headers and line text of various finance documents must be maintained in the local language, as per the company’s code definition. Alphabet uses the ABAP SDK to seamlessly interact with Google Translate, helping finance documents to comply with system and legal requirements.
Integrate AI/ML models on Google Cloud for better decision making - Before Alphabet began using SAP to manage IT hardware orders worldwide, order routing across fulfillment channels was a time-consuming process. While a rules-based decision table can predict cost-effective order routes in some cases, the majority of orders required manual review, which was highly inefficient. To address this issue, the Alphabet engineering team developed a BigQuery Machine Learning model to predict routes based on historic manual decisions, and used the ABAP SDK to read the BigQuery Machine Learning predictions in real time. This continual learning model has helped to predict routes more accurately, reducing the need for manual review and automating the shipping process.
Offload attachments from expensive HANA Storage - Alphabet utilizes the ABAP SDK to streamline and simplify the management of attachments (documents) for all applications in the SAP landscape. Due to the scale of the required storage capacity, it was imperative to offload the storage of attachment documents from Hana DB in-memory to cheaper and highly secured Cloud Storage buckets. By using the ABAP SDK, we were able to seamlessly read and write attachments from SAP applications to Cloud Storage without any impact to SAP critical user journeys (CUJs). End-user access to documents is controlled strictly based on authorization given in SAP, leveraging the standard Google Cloud Security Model.

From internal to generally available

Over the years, many of our customers have asked for ways to easily integrate their SAP systems with Google Cloud services. With the launch of the ABAP SDK last year, the same ABAP SDK that has been powering Alphabet’s business operations since 2019 is now generally available for Google Cloud customers. Download the SDK for free and onboard in a few simple steps.

While our public documentation contains the latest product updates, we also invite you to collaborate and engage with us on the Google Cloud developer community forum. We also have a public repository on GitHub so that developers can clone sample programs and quickstarts into their development environment. We are excited to see and assist you in creating enterprise and business solutions using ABAP SDK.

Moving to S/4 HANA on Google Cloud brings significant benefits for Deutsche Börse Group

Thu, 01 Feb 2024 08:00:00 +0000

As an international exchange organization and innovative market infrastructure provider, Deutsche Börse Group ensures capital markets that are transparent, reliable and stable. Our business areas cover the whole financial market transaction process and value chain. Furthermore, we develop state-of-the-art IT solutions and offer our IT systems all over the world. With our large range of products, services and technologies, our Group organizes safe and efficient markets for sustainable economies. Trust, stability, and compliance are thus the cornerstones of our business.

Moreover, innovating constantly is vital to stay competitive and relevant in the light of a market that is changing rapidly. Innovation and stability, however, don’t naturally go together. To innovate involves taking risks, so every innovation we make requires a certain balancing act to ensure we maintain our customers’ trust and meet regulatory requirements.

Stuck behind an on-premises bottleneck

This balance between trust and innovation was at the heart of our journey from our legacy architecture to Google Cloud. Running on-premises, our previous SAP enterprise resource planning (ERP) software was unable to keep up with the pace of changing requirements. From adding new legal entities following mergers and acquisitions, through launching products such as swap types or securities, to simple requests to improve our workflows, the system couldn’t keep up. Just a simple launch request would take as much as nine months, and the bottleneck led to a backlog of requests in the system. As we began upgrading to the latest SAP ERP, S/4 HANA, we knew that a simultaneous migration to the cloud would greatly improve our system performance. But first, we needed to ensure we had the trust of our stakeholders and regulators.

From day one, our approach has been full transparency: to our customers, our stakeholders, and to regulators. When we first shared with our internal control teams that we were moving to the cloud, we found ourselves looking into a lot of serious faces, but the Google Cloud team understood what it meant to build trust with all parties. As we and our stakeholders worked together with Google Cloud to understand exactly what the process entailed — and its implications for the business — we succeeded in bringing all the relevant parties on board. We were one of the first globally to move our SAP workload into Google Cloud.

Leaving the on-premises mindset behind

In particular, we busted the myth that an on-premises architecture is more secure than the cloud. Most on-premises data centers don’t have any encryption, because they believe that having it in house makes it secure. In Google Cloud, however, our data is encrypted three times: at the infrastructure level, database level, and application level. Initially, we weren’t able to hold the encryption keys ourselves, but the Google Cloud team supported us to hold our own keys, adding another layer of security. By explaining all this through open and transparent conversations with stakeholders and regulators, we were able to convince them of the virtues of migration.

Now, with Google Cloud, our data is more secure than ever, with no drop in performance. However, that wasn’t the end of the journey. After migrating our systems from our on-premises infrastructure, we realized that we had underestimated the need to migrate from our on-premises mindset, too. With many of our engineers having run workloads on legacy operating systems for many years, there was an understandable level of apprehension about switching to cloud workloads after such a long time. Again, the Google Cloud team understood their concerns, and helped to train our engineers to adapt to the new systems.

Keeping up with market demands, with a powerful cloud architecture

With SAP S4/HANA now running on Google Cloud, our ability to react quickly to a changing market has improved dramatically. If we need to rapidly scale up our processing power, in response to a sudden increase in trading volumes, we are now able to do so in a matter of a few clicks. Our development cycle has shortened considerably, too. Previously, we had just one development environment, accommodating 10 to 15 developers, leading to development cycles of nine to twelve months. Now we have 60-70 developers working in multiple development environments in parallel, significantly reducing development time.

We also no longer need to worry about lengthy delays to add new hardware to our systems. With Google Cloud, we can simply add new software services at the click of a button, meaning we can onboard new services in days, rather than spending months adding new hardware. Disaster recovery times have improved, too, with automated failover, meaning our recovery time objective (RTO) is now down from two hours to less than 20 minutes, while our recovery point objective (RPO) has been cut from two hours to nearly zero.

Let the innovation begin

We are in the process of exploring ways to apply the data analytics capabilities of Google Cloud to the treasure trove of business data from our SAP platform. We have already begun to do so with our HR and IT data domains. For the first time, the HR team has fast access to integrated business data in BigQuery, enabling them to add depth and insight to processes such as management and diversity reporting. At the same time, we are investigating how we can incorporate more AI features into our workflows, and are currently piloting Document AI to save our accountant team’s time with automated invoice entries.

In many ways, our journey is just beginning. But because we were able to win over hesitant stakeholders and cautious regulators with our transparent approach, we have already been able to demonstrate the significant improvements in security and performance that Google Cloud gives us. Now, we can start to innovate further, improving efficiencies and reaction times, and ensuring we can continue offering relevant products and services to our customers. Trust, stability, compliance, and innovation. With Google Cloud, we have them all.

Kingfisher: building the future of home improvement with a powerful new data platform

Mon, 04 Dec 2023 17:00:00 +0000

In retail, the distinction between physical and digital has blurred, and the home improvement sector is no exception. At Kingfisher, our retail banners include B&Q, Castorama, Brico Dépôt, and Screwfix, and our customers expect a seamless shopping experience whether they shop with us online or in store.

From product recommendations to delivery suggestions to location-based services, the technology required to meet these changing expectations is all powered by data. And to effectively deliver for our customers, that data needs to be highly available, highly accurate, and highly optimized. It needs to be gold standard.

In November 2022, we signed a five-year strategic partnership with Google Cloud to accelerate the migration of our huge on-premises SAP workloads to the cloud. By moving away from a tightly coupled, monolithic architecture, our goal was to improve our resilience and strengthen our data platform to unleash the full potential of our data, giving us the resilience and agility we need to power our growth.

The right platform — and people — to help us do it ourselves

Data speed and quality are critical to helping us achieve our goals, with data platforms, recommendation engines, sophisticated machine learning, and the ability to quickly ingest and curate content, all key to our future plans. Partnering with Google Cloud helps us to unlock this potential, with Google Cloud Marketplace also offering a critical capability to help us simplify procurement.

One of the most important factors in our decision to partner with Google Cloud was the expertise. Google Cloud not only brings a specific set of functionality and services that are well suited to our needs, but a team of people behind those solutions who understand our industry. They know our needs and goals, and can help us work through our challenges. And as we continue to migrate our workloads and build our architecture, the Google Cloud team is fully engaged, working closely with us in a meeting of minds.

Unleashing data’s potential to meet customer expectations

This partnership has already started to deliver results. By abstracting the data away from our core platform, we are now able to use it more productively for our business needs, and we’re currently working on some use cases around supply chain visibility. One such project enables us to dynamically price products according to various live promotions, so that we can react to the market with more agility.

This is only possible because we’ve been able to separate the data from our SAP system and run it through Google Cloud solutions such as BigQuery and Cloud Storage, enabling us to provide a more personalized shopping experience. Plans are now underway to use our product and sales data to create a new, real-time order system to greatly improve stock accuracy, as well as scaling up B&Q’s online marketplace from 700,000 products to 4 million (Kingfisher’s H1 2023/23 Financial Results).

Facing the future with a solid foundation

The future of digital retail is highly compute-intensive, requiring a level of real-time data processing near equivalent to that needed to power a major stock market. Working with Google Cloud gives us the processing power to use our data to its full potential, freeing us to focus on what we do best: offering the best home improvement proposition to our customers.

The growing suite of AI solutions in Google Cloud adds another dimension to our ability to leverage data, which will be increasingly important to enhancing the customer experience. Vertex AI, for example, is already allowing us to optimize our product pages, so that customers can visualize products in different scenarios and make a more informed purchasing decision. Throughout the business, AI is improving and speeding up our internal processes, which ultimately allows us to better serve our customers.

It’s no secret the retail industry is evolving at pace. With Google Cloud, we now have the agility, the support, and the data platform to create more seamless customer experiences both in stores and online.

Automate plant maintenance using MDE with ABAP SDK for Google Cloud

Tue, 31 Oct 2023 16:00:00 +0000

Many Google Cloud customers run multiple manufacturing facilities and are constantly looking at ways to reduce costs and improve efficiency by proactively maintaining their machines and reducing production downtime.

Until now, monitoring and maintaining shop floor assets was mostly a manual, reactive, and cumbersome process. Google Cloud can help with its portfolio of artificial intelligence (AI) and machine learning (ML) capabilities. Today, sensors collect operational data from machines and stream It to Google Cloud. Once data is ingested in Google Cloud, customers can use machine learning or statistical calculations to identify patterns and predict and solve maintenance issues even before they happen. This solution pattern is known as predictive maintenance. Plant managers can now leverage technical solutions based on predictive maintenance to detect anomalies in any machine or equipment before it breaks down. Predictive maintenance also allows plant managers to schedule maintenance when it is convenient and not during actual production hours, thus saving a lot of time and cost.

Analyzing production data at scale for huge datasets is always a challenge, especially when there’s data from multiple production facilities involved with thousands of assets in production pipelines. To help solve this challenge, our Manufacturing Data Engine is designed to help manufacturers manage end-to-end shop floor business processes.

Manufacturing Data Engine

Manufacturing Data Engine (MDE) is a scalable solution that accelerates, simplifies, and enhances the ingestion, processing, contextualization, storage, and usage of manufacturing data for monitoring, analytical, and machine learning use cases. This suite of components can help manufacturers accelerate their transformation with Google Cloud’s analytics and AI capabilities.

The architecture above includes:

Manufacturing Connect, a factory connectivity product that supports edge workloads and integrates devices with Google Cloud. It has an extensive library of 250+ machine protocols that can quickly connect with nearly any manufacturing asset.
Manufacturing Data Engine, which processes, contextualizes, and stores factory data. With built-in data normalization and context-enrichment capabilities, it provides a common data model, with a factory-optimized data lakehouse for storage.
Customizable predefined analytics that provide customizable dashboards and ‘metamodels’ for business insights and self-service analytics.
AI-Driven Operations Optimization, a portfolio of AI use cases that unlock value at scale and integrate with Google Cloud tools such as Vertex AI.

SAP for manufacturing customers

SAP,a leading enterprise resource planning (ERP) software vendor, and Google Cloud have been partners for many years, helping customers transform their businesses leveraging Google’s services like BigQuery, Vertex AI, Cloud Pub/Sub, etc., across business domains. In the manufacturing space, SAP offers SAP Plant Maintenance to help industrial companies manage maintenance activities such as equipment inspection, notifications, corrective and preventive maintenance, and repairs.

ABAP SDK for Google Cloud

ABAP SDK for Google Cloud provides bi-directional, real-time integration between SAP and Google Cloud services. SAP developers can use the ABAP SDK for Google Cloud to integrate their SAP applications with Google Cloud services such as Vertex AI, Document AI, Translation AI, Pub/Sub, and more. With the ABAP SDK, customers can accelerate their digital transformation and achieve business goals faster.

Combining the best of both solutions

Manufacturing customers whose Plant Maintenance business processes are on SAP can implement predictive maintenance for their shop floor assets by combining capabilities of Google Cloud’s MDE and ABAP SDK for Google Cloud. Let’s take an example of a car manufacturer who uses sandblasting machines to clean metal parts before sending them out for a paint job and assembly. Imagine the car manufacturer wants to monitor the health of the motor in the blasting machine for any anomalies that may lead to assembly line disruptions:

MDE can receive a stream of sensor data in the form of shaft vibrations from the vibration sensors mounted on the motor, and MDE can have a machine learning model to detect any anomaly in the pattern of the vibration stream.
If an anomaly is detected by the ML model, an event is triggered in MDE and a notification with equipment information is published to a Cloud Pub/Sub topic.
An SAP automation program can run in the background at a regular interval and use ABAP SDK for Google Cloud to pull in the equipment information from Cloud Pub/Sub natively and create a Plant Maintenance Order in SAP.
An SAP business user starts working on the order. ABAP logic can be written to leverage the ABAP SDK for Google Cloud to publish the current order status to another Cloud Pub/Sub topic. This topic can then be used to source information to a BigQuery dataset.
A dashboard can be designed based on the BigQuery dataset for the plant managers which can be used to track metrics like:
- the status of the maintenance orders in real time
- visibility into delayed orders
- total delays for a month

Conclusion and value prospects

By integrating manufacturing data into enterprise software like SAP, a customer can gain unprecedented visibility into their shop floor operations and can:

Reduce downtime by planning and optimizing maintenance schedules, which can cost companies around 11% of their yearly turnover otherwise (Link)
Avoid catastrophic failures that otherwise could result in assembly line disruptions and expensive repairs
Achieve efficient cycle times in their production lines

MDE gives you the opportunity to streamline and gather your shop floor data efficiently, while ABAP SDK for Google Cloud opens up the possibilities to bring in manufacturing insights to your SAP systems. Customers can follow a similar solution pattern to utilize other Google Cloud solutions and services natively in their SAP systems and ABAP SDK for Google Cloud can enable the integration. Also, partners can convert these integration patterns into packaged solutions using the SDK.

Learn more and start your journey today with Google Cloud’s Manufacturing Data Engine and ABAP SDK for Google Cloud.