Grafana Applies SLOs and Error Budgets to AI Agent Behaviour

Craig Risi — Fri, 16 Oct 2026 12:00:00 GMT

Grafana Labs is proposing a familiar reliability engineering approach for one of the less familiar problems in modern software: how to measure whether an AI agent is actually behaving well.

By Craig Risi

Presentation: Ontology‐Driven Observability: Building the E2E Knowledge Graph at Netflix Scale

Prasanna Vijayanathan, Renzo Sanchez-Silva — Fri, 09 Oct 2026 11:00:00 GMT

Prasanna Vijayanathan and Renzo Sanchez-Silva share how Netflix tackles observability across 38M events/sec. They discuss replacing reactive monitoring with an AI-driven operational ontology and agentic workflows using Claude and graph databases. They explain how unifying MELT telemetry into queryable knowledge graphs enables automated triaging, root-cause analysis, and self-healing systems.

By Prasanna Vijayanathan, Renzo Sanchez-Silva

InfoQ - AIOps

Grafana Applies SLOs and Error Budgets to AI Agent Behaviour

Presentation: Ontology‐Driven Observability: Building the E2E Knowledge Graph at Netflix Scale