Traditional automated remediation (if-this-then-that) is brittle. It fails when faced with the "unknown-unknowns" of distributed systems. When a production incident occurs, the cognitive load on the on-call engineer to parse logs, traces, and metrics is the primary bottleneck for MTTR (Mean Time to Resolution). But with the rise of Agentic AI—LLMs that don't just "chat" but actually execute tools—the dream of a truly self-healing infrastructure is finally within reach. This session moves past the marketing slides to demonstrate how to build an autonomous remediation pipeline that thinks like an SRE. We will explore the architecture of an0 Agentic Observability Loop. Unlike static scripts, an AI Agent can: Observe: Interface with AI Agents to identify the root cause. Reason: Cross-reference telemetry with recent GitHub deployments and runbooks. Act: Execute safe, scoped operations—like rolling back a canary, scaling a K8s deployment, or flushing a cache—using verified toolsets.
Jones is a seasoned developer turned architect who currently at New Relic being an observability advocate working as Senior Developer Relations Engineer and also focuses on infrastructure and development on cloud platforms like AWS and well into the Serverless ecosystem. Jones is also recognised as AWS Serverless Hero who is enabling the community with latest happenings in the Serverless space with his newsletter, blogs and podcast. Along with this, Jones also regularly shares the best of cloud + observability at multiple global forums and conferences.
