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Alert fatigue is rarely caused by missing data. Logs, metrics, traces, and alerts are usually available, but during incidents they remain fragmented. Engineers still correlate signals manually, under pressure, relying on experience rather than shared context.
This talk describes an AIOps approach where observability data becomes the basis for operational decisions. OpenSearch is used as the central platform to collect, query, and correlate logs, metrics, and traces, providing a consistent data model and query layer across systems. By leveraging MCP capabilities, agentic AI, and tools, automation plays a central role in closing the loop from GitOps to delivery, monitoring, and problem resolution.
From this foundation, OpenSearch can be integrated with complementary tools to extend its capabilities. KeepHQ can consume data from OpenSearch to design alerting and response workflows and connect ticketing systems and external tools. HolmesGPT can operate on data retrieved from OpenSearch to assist with incident analysis and root cause investigation.
The focus is on what happens after detection: reducing noise, correlating signals, and supporting engineers during incident response.
Stefano is the CEO of two open source companies operating as benefit companies, combining business activity with social and environmental impact. He founded his first Internet Service Provider in 1995, building the entire infrastructure using open source software, and later created... Read More →
