Most AIOps solutions today detect and explain anomalies, but they rarely act. In critical environments like IBM Z mainframes, this gap can prevent true operational resilience. This presentation argues that effective AIOps requires a shift from passive observation to autonomous control, built on a foundation of rigorous workload modeling. Drawing on a patent-backed framework, the session will explore the progression from simple metrics to autonomous infrastructure, including workload modeling that connects business activity to system resource consumption, context-aware analysis that segments diverse workloads for more precise service-level decisions, and automated execution that enables true agentic capabilities. Attendees will learn why reliable system models are a prerequisite for self-healing infrastructure and how organizations can evolve from reactive monitoring to proactive, autonomous control.
The research is available on @ResearchGate:
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