Infrastructure impact on SAP cloud services

SAP Joule for S/4HANA: Public Cloud vs. Private Cloud — What’s the Real Difference? SAP is rolling out Joule across the ERP landscape, but one question keeps coming up: “How does Joule actually differ between S/4HANA Public Cloud and S/4HANA Private Cloud?” If you work in SAP architecture, operations, or transformation programs, this comparison truly matters. Here’s a crisp, accurate breakdown — without the noise. 1️⃣ Joule in S/4HANA Public Cloud Status: Natively Integrated (Minimal Setup Required) In Public Cloud, Joule plugs into the system with almost no infrastructure work. Streamlined Setup You don’t deploy infrastructure or Cloud Connector. SAP has already wired the environment for you. What you do is simply: ↳ Enable Joule in the Fiori Launchpad ↳ Activate the standard communication scenarios (e.g., COM_0647, COM_0193) ↳ Assign appropriate business roles ↳ Validate identity settings (IAS/IPS is mostly pre-configured) Capabilities Out of the Box Once activated, Joule can provide: ↳ Navigational search ↳ Contextual insights (POs, deliveries, sales data, etc.) ↳ App guidance and help content Public Cloud = Fastest adoption path with the least technical effort. 2️⃣ Joule in S/4HANA Private Cloud (RISE Customers) Status: Full Architecture Setup Required Private Cloud gives more power and flexibility — but requires assembling several SAP components. Key Components to Configure To enable Joule, you must set up: ↳ SAP BTP subaccount ↳ Cloud Foundry environment ↳ SAP Build Work Zone, Standard Edition ↳ SAP Cloud Identity Services (IAS + IPS) ↳ SAP Cloud Connector (mandatory) ↳ Technical SU01 user with appropriate authorizations HTTP + RFC mappings ↳ Activation of required OData APIs in S/4HANA backend Compared to Public Cloud, this is a multi-layer integration project, not just a setting. Capabilities Private Cloud can do everything Public Cloud does — and more — because you can activate any required backend services. You get: ↳ Broader transactional execution (create/update documents via OData) ↳ Conversational filters ↳ Custom process extensions via BTP ↳ Ability to connect with non-SAP systems ↳ Document grounding via SAP AI Core or external vector stores Which One Should You Care About? If you’re on  S/4HANA Public Cloud Joule is the simplest AI rollout you’ll ever do. Enable → Assign roles → Done. If you’re on  S/4HANA Private Cloud (RISE) You get significantly more extensibility and integration control, but you must plan for: ↳ BTP readiness ↳ Identity architecture (IAS/IPS trust) ↳ Cloud Connector paths ↳ OData activation ↳ Cross-system authorizations The Bigger Picture Regardless of edition, Joule marks SAP’s shift toward: Conversational. Intelligent. Context-aware ERP. Companies that prepare their BTP foundation and identity strategy today will benefit the most as SAP extends Joule into agents, skills, and deeper automation layers. P.S—Unlock SAP AI Course + learning materials: https://lnkd.in/dtKFpBP7  

AI isn’t magic - it’s math + data + infrastructure. And if your SAP system is still on-prem, you’re cutting off its fuel source. I’ve spent over two decades in SAP environments. Today, I’m watching a new wave of demand hit CIOs hard: “Can we plug AI into our SAP data?” Not if your system is stuck in an old stack. At Sapphire last week, SAP pushed Joule - their AI assistant - front and center. But what they also made clear is this: to even access that capability, you need to be in the cloud. Modernization used to mean agility, cost savings, and faster provisioning. Now it means AI readiness. And most teams haven’t connected the dots yet. Here’s what I’ve learned after 25 years of SAP migrations: 1. AI requires speed and scale Legacy systems, even those virtualized, hit performance ceilings. Cloud-native SAP environments are the only way to handle the speed AI needs. 2. Your current stack might block SAP AI features If you’re still running on older infrastructure, you won’t be able to use services like Joule. SAP made that clear: cloud is the new baseline. 3. Migration without transformation is wasted effort Moving to the cloud isn’t enough. If you don’t modernize your operational processes - monitoring, integration, automation - the costs won’t go down, and the performance won’t go up. 4. AI needs context, and that starts with orchestration Without streamlined workflows and clean data pipelines, AI doesn’t just underperform - it confuses and misfires. 5. You don’t need to move everything at once, but you do need a blueprint I’ve helped organizations migrate in phases, with minimal disruption. But every successful one started with a clear assessment and roadmap. Cloud migration is no longer a tech decision. It’s a business enablement move - one that sets the stage for AI, analytics, and real-time decisions. If you want your SAP system to think like the future, you need to get it into the infrastructure of the present.

🚨 𝗦𝗧𝗢𝗣 𝗽𝗶𝗰𝗸𝗶𝗻𝗴 𝗵𝘆𝗽𝗲𝗿𝘀𝗰𝗮𝗹𝗲𝗿𝘀 𝗯𝗹𝗶𝗻𝗱𝗹𝘆 𝗶𝗻 𝗦𝗔𝗣 𝗥𝗜𝗦𝗘 (𝘛𝘩𝘪𝘴 𝘴𝘪𝘯𝘨𝘭𝘦 “𝘪𝘯𝘧𝘳𝘢” 𝘥𝘦𝘤𝘪𝘴𝘪𝘰𝘯 𝘲𝘶𝘪𝘦𝘵𝘭𝘺 𝘥𝘦𝘤𝘪𝘥𝘦𝘴 𝘸𝘩𝘦𝘵𝘩𝘦𝘳 𝘺𝘰𝘶𝘳 𝘚𝘈𝘗 𝘙𝘐𝘚𝘌 𝘱𝘳𝘰𝘨𝘳𝘢𝘮 𝘴𝘤𝘢𝘭𝘦𝘴… 𝘰𝘳 𝘴𝘭𝘰𝘸𝘭𝘺 𝘣𝘭𝘦𝘦𝘥𝘴.) 💬 𝗧𝗵𝗲 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻 𝗲𝘃𝗲𝗿𝘆𝗼𝗻𝗲 𝘁𝗵𝗶𝗻𝗸𝘀, 𝗳𝗲𝘄 𝗮𝘀𝗸 “Ravi… I’m convinced about SAP RISE. But what is this hyperscaler thing — and how do we choose the right one?” This came from my veteran infra lead. Decades of experience. Zero tolerance for buzzwords. He was right. Most SAP RISE programs don’t fail in S/4HANA. They fail before that — 𝗶𝗻 𝘁𝗵𝗶𝘀 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻. Because once you sign RISE, you don’t “switch hyperscalers.” 𝗜𝘁’𝘀 𝗮 𝗿𝗲-𝗱𝗲𝗮𝗹. ☁️ 𝗪𝗵𝗮𝘁 𝗮 𝗵𝘆𝗽𝗲𝗿𝘀𝗰𝗮𝗹𝗲𝗿 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗶𝘀 𝗶𝗻 𝗦𝗔𝗣 𝗥𝗜𝗦𝗘 • SAP owns the contract • SAP runs S/4HANA Cloud, Private Edition • Hyperscaler runs the infrastructure (IaaS) 𝗠𝗲𝗻𝘁𝗮𝗹 𝗺𝗼𝗱𝗲𝗹👇 👉 SAP = airline 👉 Hyperscaler = aircraft 👉 You cannot switch planes mid-flight This is architecture. Not procurement. 🏗️ 𝗧𝗵𝗲 𝟰 𝗦𝗔𝗣-𝗮𝗽𝗽𝗿𝗼𝘃𝗲𝗱 𝗵𝘆𝗽𝗲𝗿𝘀𝗰𝗮𝗹𝗲𝗿𝘀 (𝗿𝗲𝗮𝗹𝗶𝘁𝘆 𝗰𝗵𝗲𝗰𝗸) • 𝗔𝗪𝗦 – strongest SAP hosting maturity, global scale ⚠️ Watch: cost sprawl, governance complexity • 𝗔𝘇𝘂𝗿𝗲 – best fit for Microsoft-heavy enterprises ⚠️ Watch: region-specific service gaps • 𝗚𝗼𝗼𝗴𝗹𝗲 𝗖𝗹𝗼𝘂𝗱 – analytics & AI-first strength ⚠️ Watch: smaller SAP footprint • 𝗔𝗹𝗶𝗯𝗮𝗯𝗮 𝗖𝗹𝗼𝘂𝗱 – essential for China compliance ⚠️ Watch: limited relevance outside China/APAC 🎯 𝗛𝗼𝘄 𝘁𝗼 𝗰𝗵𝗼𝗼𝘀𝗲 𝗽𝗿𝗮𝗴𝗺𝗮𝘁𝗶𝗰𝗮𝗹𝗹𝘆 (𝘂𝘀𝗲 𝘁𝗵𝗶𝘀 𝗰𝗵𝗲𝗰𝗸𝗹𝗶𝘀𝘁) • 𝗥𝘂𝗻 𝗮 𝟯𝟲-𝗺𝗼𝗻𝘁𝗵 𝗧𝗖𝗢 In RISE, hyperscaler is bundled — 𝗰𝗼𝗻𝘀𝘂𝗺𝗽𝘁𝗶𝗼𝗻 𝗶𝘀𝗻’𝘁 𝗳𝗿𝗲𝗲. Model 3-year growth + storage/DR + network/egress. Cheap now, expensive later = 𝗱𝗲𝗳𝗲𝗿𝗿𝗲𝗱 𝗿𝗶𝘀𝗸. • 𝗠𝗮𝘁𝗰𝗵 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆 – Microsoft estate → Azure – AI/analytics roadmap → Google – Global footprint → AWS – China operations → Alibaba • 𝗟𝗲𝘁 𝗰𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲 𝗱𝗲𝗰𝗶𝗱𝗲 𝗲𝗮𝗿𝗹𝘆 – Data residency laws beat opinions • 𝗔𝗰𝗰𝗲𝗽𝘁 𝗥𝗜𝗦𝗘 𝗰𝗼𝗻𝘀𝘁𝗿𝗮𝗶𝗻𝘁𝘀 𝘂𝗽𝗳𝗿𝗼𝗻𝘁 – You don’t control infra — SAP does – Not all native cloud services are usable – Change moves at SAP speed, not cloud speed 🧨 𝗧𝗵𝗲 𝗯𝗼𝘁𝘁𝗼𝗺 𝗹𝗶𝗻𝗲 𝗛𝘆𝗽𝗲𝗿𝘀𝗰𝗮𝗹𝗲𝗿 𝘀𝗲𝗹𝗲𝗰𝘁𝗶𝗼𝗻 𝗶𝗻 𝗦𝗔𝗣 𝗥𝗜𝗦𝗘 𝗶𝘀 𝗮 𝗹𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽 𝗰𝗼𝗻𝘀𝗲𝗾𝘂𝗲𝗻𝗰𝗲. Get it right — silence. Get it wrong — post-mortems. The loudest voices in hyperscaler selection are usually the 𝗹𝗲𝗮𝘀𝘁 𝗮𝗰𝗰𝗼𝘂𝗻𝘁𝗮𝗯𝗹𝗲 in hypercare. 👉 𝘞𝘩𝘪𝘤𝘩 𝘩𝘺𝘱𝘦𝘳𝘴𝘤𝘢𝘭𝘦𝘳 𝘸𝘰𝘶𝘭𝘥 𝘺𝘰𝘶 𝘤𝘩𝘰𝘰𝘴𝘦 𝘧𝘰𝘳 𝘚𝘈𝘗 𝘙𝘐𝘚𝘌 — 𝘢𝘯𝘥 𝘸𝘩𝘢𝘵 𝘵𝘳𝘢𝘥𝘦-𝘰𝘧𝘧 𝘢𝘳𝘦 𝘺𝘰𝘶 𝘤𝘰𝘯𝘴𝘤𝘪𝘰𝘶𝘴𝘭𝘺 𝘢𝘤𝘤𝘦𝘱𝘵𝘪𝘯𝘨? #RISEwithSAP #S4HANA #CloudStrategy #Hyperscalers #EnterpriseArchitecture #SAPTransformation Wouter van Heddeghem

Your SAP AI is only as good as your Data infrastructure. No clean data → No business impact. SAP is making headlines with AI innovations like Joule, its generative AI assistant. Yet, beneath the surface, a critical issue persists: Data Infrastructure. The Real Challenge: Data Silos and Quality Many enterprises rely on SAP systems - S/4HANA, SuccessFactors, Ariba, and more. However, these systems often operate in silos, leading to: Inconsistent Data: Disparate systems result in fragmented data. Poor Data Quality: Inaccurate or incomplete data hampers AI effectiveness. Integration Issues: Difficulty in unifying data across platforms. These challenges contribute to the failure of AI initiatives, with studies indicating that up to 85% of AI projects falter due to data-related issues. Historical Parallel: The Importance of Infrastructure Just as railroads were essential for the Industrial Revolution, robust data pipelines are crucial for the AI era. Without solid infrastructure, even the most advanced AI tools can't deliver value. Two Approaches to SAP Data Strategy 1. Integrated Stack Approach:   * Utilizing SAP's Business Technology Platform (BTP) for seamless integration.   * Leveraging native tools like SAP Data Intelligence for data management. 2. Open Ecosystem Approach:   * Incorporating third-party solutions like Snowflake or Databricks.   * Ensuring interoperability between SAP and other platforms. Recommendations for Enterprises * Audit Data Systems: Identify and map all data sources within the organization. * Enhance Data Quality: Implement data cleansing and validation processes. * Invest in Integration: Adopt tools that facilitate seamless data flow across systems. * Train Teams: Ensure staff are equipped to manage and utilize integrated data effectively. While SAP's AI capabilities are impressive, their success hinges on the underlying data infrastructure. Prioritizing data integration and quality is not just a technical necessity → It's a strategic imperative.