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SAP_Expert_Lectures_t2calm1_Unit_3_Lesson_1_Video.mp4

Hello and welcome. Today's lesson is Taking Operations to the Next Level with SAP Cloud ALM. I'm Carsten Heinz, chief Product Owner for SAP Cloud ALM for Operations and SAP Focused Run. In the next minutes, I'll show you our mission, how we support large enterprise operations, and how we move step by step towards Autonomous ALM. Let's get started. Here is the agenda. First, I'll explain our mission for SAP Cloud ALM for Operations. Then we talk about Large Enterprise Readiness and what we deliver to make SAP Cloud ALM work for you in large enterprise environment. After that, I'll walk you through our path to Autonomous ALM, what it means, and how we get there in practical steps. And finally, I'll close with a few key takeaways. Our mission is simple, help you ensure business continuity with an out-of-the-box, realistic observability solution built for SAP and open beyond SAP. At the heart of SAP Cloud ALM are seven monitoring use cases that work together as one operational story. Most customers typically start with real user monitoring and integration and exception monitoring, because this provides insights that go well beyond what many teams were used to with SAP Solution Manager. And you see what users experience and where integrations break before it becomes a business incident. At the same time, we still cover the operational foundation with health monitoring and job and automation monitoring, the core you need to run as stable day-to-day. A key differentiator is business process monitoring. SAP Cloud ALM comes with pre -configured business processes, so you get visibility into the most important business KPIs out of the box without starting from scratch. And you can already extend this with custom metrics for both SAP S/4HANA and SAP BTP-based applications, as well as custom processes, including processes that can be imported from SAP Cloud ALM for implementation. This connects implementation and operation much more tightly. Also, business object flow monitoring in integration and exception monitoring shows our commitment to expanding capabilities for business key users, not only technical teams. And we are clearly doubling down on configuration and security analysis. Because enterprise customers need continuous checks, not occasional audits. That's an area where we are investing heavily, and we will reach a state beyond SAP Solution Manager and SAP Focused Run by mid-2026. Another important part of our mission is openness. With open telemetry support, SAP Cloud ALM can receive metrics, logs, and traces not only from SAP applications, but also from custom-built SAP BTP applications, and even non -SAP applications that support the open telemetry standard. And I want to emphasize something. It is especially simple to connect custom SAP BTP applications to SAP Cloud Data. This is designed to be practical, fast onboarding, no drama. Outbound, we support forwarding of raw telemetry data, and we provide an analytics API. A third key dimension is collaboration across customers, partners, and SAP. SAP Cloud ALM acts as a collaboration hub. For example, it can automatically synchronize maintenance windows and contractual uptime information from the SAP Cloud services you subscribe to. And you can add your own scheduled maintenance windows as well. Partners can also enhance SAP Cloud ALM beyond its current scope via extension APIs. That's exactly the ecosystem approach we envision. Finally, we are proud of one thing, speed of activation. For many supported products, you can enable metric collection for a cloud service per use case with a single click, so value comes in minutes, not days. But this is still not good enough. You are being asked to do more with less, so we are moving towards autonomous ALM. Within the next years, we will move away from manually defining every threshold and every rule. Instead, SAP Cloud ALM for Operations will continuously analyze incoming metrics, logs, and traces, correlate them, and proactively alert you when it detects a critical situation. And later, I'll outline how we're turning this into reality. Before we go deeper into autonomy, we need to address a very real customer question. Where to start, SAP Cloud ALM or SAP Focus Run? Our recommendation today is start with SAP Cloud ALM for Operations. Why? Because SAP Cloud ALM already provides powerful capabilities to replace SAP Solution Manager for many operation scenarios with a simpler setup and a cleaner user experience. Now, there is still a place for SAP Focused Run. SAP Focused Run is recommended when you keep a large on-premise footprint, need maximum flexibility for system monitoring and customization, cannot use a cloud solution, even sovereign cloud due to regulatory or governance constraints. Or you are a service provider operating many customer landscapes. So, think of it like this. SAP Cloud ALM and SAP Focused Run can achieve similar goals, but often with different methods. SAP Cloud ALM is optimized for fast time-to-value, standardized best practices, and cloud-native extensibility. SAP Focused Run is optimized for deep system monitoring and highly tailored on-premise operations at very large scale. Customers can also combine both, depending on their landscape and constraints. Now let's look at this transition from SAP Solution Manager, specifically through the lens of monitoring coverage. When we look at what's available in SAP Cloud ALM and SAP Focused Run, we see a key split in emphasis. Implementation functionality like design, build, test and deploy and business process monitoring is only available in SAP Cloud ALM. And at the same time, many operational monitoring use cases are well covered in both. integration and exception monitoring, performance monitoring as synthetic and real user monitoring, as well as job and automation monitoring, and configuration and security analysis. SAP Focused Run clearly has its strengths in system monitoring, especially for very large landscapes. But SAP Cloud ALM is catching up quickly, and with Agentic AI via Joule, we are taking monitoring capabilities to the next level with a much simpler user experience. That's why this transition is not only about replacing SAP Solution Manager. It's about modernizing how operations get done. So, what do we have to deliver to make SAP Cloud ALM work well for large enterprises? Let me highlight the key areas. First, updated memory mode. We've increased the baseline memory included in your enterprise support subscription to support enterprise at scale. In addition, you can estimate via our newly released memory estimator what you'll need as you connect systems and services. So, scaling becomes predictable. Essential monitoring metrics come second. This is a crucial step for customers transitioning core monitoring scenarios. We have recently shipped most requested metrics for monitoring QRFC and BGRFC. Third, Advanced Role and Access Management. Large enterprises need stronger governance and control. So it's a foundation. That's why we ship an updated role in access management until the end of Q2 2026. Fourth, configuration and security analysis. This is one area where customers still feel differences compared to SAP Solution Manager and SAP Focused Run. So we are investing heavily to make it more powerful and easier to consume, also with AI support. And fifth, mass configuration within Health Monitoring. Because onboarding must be efficient even if you have hundreds or thousands of systems, mass configuration is as well planned for the end of Q2 2026. Taken together, these capabilities make SAP Cloud ALM ready for serious enterprise operations at scale. Now, let's move to the most exciting part, how we get to Autonomous ALM step by step. We think about Autonomous ALM in three pillars, simplified setup and enhanced alerting, resolution and analytics. Let's start with where many teams are today. In traditional monitoring, you often have to select a metric, configure a threshold. And when something happens, you manually search for a solution. And if you want dashboards that fit your needs, you often have to rely on external tools. We are already improving on this. For example, dynamic thresholding in synthetic user monitoring and change point detection in real user monitoring. And we are expanding AI support across additional areas, especially in configuration and security analysis. Now, what's next? We move towards critical situation detection, meaning SAP Cloud ALM continuously analyzes signals, metrics, locks and traces, correlates them, and proactively alerts you when patterns indicate a real risk. So you don't have to pre-define every single threshold manually. The system helps decide what matters based on context. In the resolution pillar, we move from manually searching to customer resolution proposals. With Joule, you get guided recommendations tailored to your landscape, your configuration, your services, and your dependencies. And over time, where it's safe and appropriate, resolution can become increasingly automated. In the analytics pillar, we move from external dashboards to conversational creation of custom dashboards in SAP Cloud ALM. You describe what you want to see. And the system creates dashboards without requiring to master a separate analytics product. That's the path from manual configuration to intelligent detection to guided resolution to conversational analytics and ultimately towards autonomous ALM. So what are the key takeaways? First, finalize your transition to SAP Cloud ALM. SAP Cloud ALM is ready for core operation scenarios and the roadmap is accelerating. Second, make use of memory estimation and the updated memory model. So plan your onboarding with confidence, especially for larger landscapes. And third, Autonomous ALM is around the corner. What comes together now is the ability to replace SAP Solution Manager monitoring scenarios and the introduction of AI-driven experiences that fundamentally improve operational efficiency. And if you want to see this in action, join our sessions and events, where we demo what's coming next. Thank you for your time and enjoy the rest of the course.

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Taking Operations to the Next Level with SAP Cloud ALM

bookmap_Transition_from_SAP_Solution_Manager_to_SA_en-US_learning-sap-com_lsc-prod_batchid_527916.zip (BUILDER-INGRESS) - 2026-05-19T06:57:31.000Z

<div id="content"><div class="kalturaVideoLessonWrapper"><div id="1_v4u0clro" data-testid="video" class="kalturaVideoLessonContainer" aria-label=""></div></div><p tabindex="0"><strong>Video Summary:</strong></p><p tabindex="0">The video presents SAP Cloud ALM for Operations: its mission to provide an out-of-the-box, business‑centric observability platform; the seven integrated monitoring use cases (real/synthetic user monitoring, integration/exception, health/job/automation, business process monitoring, configuration &amp; security analysis); investments to make Cloud ALM enterprise-ready at scale; and the roadmap toward Autonomous ALM with AI-driven detection, guided resolution (Joule), and conversational analytics. It also explains when to start with Cloud ALM versus SAP Focused Run, and highlights openness (OpenTelemetry, BTP onboarding, APIs), collaboration features, and fast activation</p><p tabindex="0"><strong>Key Points:</strong></p><ul style="list-style-type:disc"><li tabindex="0">Built for business‑centric observability: seven integrated monitoring use cases, including preconfigured business process monitoring and KPIs so teams get actionable visibility quickly (and can extend with custom metrics and imported processes).</li><li tabindex="0">Enterprise readiness and scalability: SAP is delivering an updated memory model and estimator, essential metrics (e.g., QRFC/BGRFC), advanced role/access controls, stronger configuration &amp; security analysis, and mass configuration for onboarding large landscapes.</li><li tabindex="0">Openness and collaboration: Cloud ALM ingests OpenTelemetry data from SAP and non‑SAP apps, offers easy SAP BTP onboarding, supports outbound telemetry and an analytics API, and acts as a collaboration hub (maintenance windows, partner extensions).</li><li tabindex="0">Autonomous ALM roadmap with AI: progression from dynamic thresholds and change‑point detection to continuous critical‑situation detection, Joule‑based guided resolution (and eventual automated remediation), and conversational dashboard creation to greatly reduce manual effort.</li></ul></div>

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