How OpenObserve uses AI-powered alert correlation to reduce noise, connect related events, and speed up incident response while evolving toward practical AIOps.
Learn how AI-driven alert correlation groups related telemetry to cut noise and improve detection.
Understand how these capabilities reduce MTTD and MTTR in real incident workflows.
See what AIOps features OpenObserve is releasing next and how they fit into existing systems.
Teams are dealing with rising alert volume, long investigation cycles, and fragmented telemetry. This session dives into how OpenObserve uses AI-powered alert correlation to surface related events, reduce noise, and shorten incident timelines. We will walk through what is already live in the product, how organizations are using it to reduce MTTD and MTTR, and what AIOps capabilities we are releasing next. You will leave with a clear view of how AI observability is evolving inside OpenObserve and how to adopt it in your own workflows.
Shraddha Kishan is a backend developer with experience in Rust, Linux, and AI. With extensive experience at building products and features zero-to-one, he excels at driving business value through unique solutions and automation.
Manas is a passionate Dev and Cloud Advocate with a strong focus on cloud-native technologies, including observability, cloud, kubernetes, and opensource communities--building bridges between tech and community.
