Observability
10 guides tagged “Observability”.
- How to Monitor an AI Agent in Production Monitor outcomes and actions, not just errors: completion rate, cost per run, tool failures, latency, and interventions per hundred runs.
- LLM Observability: What to Log and Trace Trace prompt version, model, tokens, tools, latency, cost, and outcome per request, with sensitive content redacted before storage.
- What Is Structured Logging? Structured logging emits machine-readable key-value events instead of free text. Learn why it matters, how to adopt it, and what AI logs get wrong.
- How to Set Up Basic Application Monitoring Set up basic app monitoring with Prometheus metrics, a health endpoint, and Grafana dashboards. A tool-agnostic tutorial with a concrete example.
- What Is Log Rotation (and Why Do Your Logs Keep Disappearing)? Log rotation archives and deletes old logs so disk never fills up. Learn how it works, why your logs vanish, and how log management services fit in.
- What Is Observability (and How Is It Different From Monitoring)? Monitoring tells you when something known is wrong; observability lets you ask new questions about unknown failures. Learn the difference with examples.
- What Are SLA, SLO, and SLI? SLIs are the measurements, SLOs are your internal targets, and SLAs are contractual promises to customers. Learn the difference with a comparison table.
- What Is SRE (Site Reliability Engineering)? Site reliability engineering applies software engineering to operations: SLOs, error budgets, and automation. Learn the core ideas and key practices.
- What Is Self-Healing Infrastructure? Self-healing infrastructure automatically detects failures and restores the desired state without human action. Learn the patterns and the risks.
- What Is AIOps? AIOps applies machine learning to IT operations to reduce alert noise, detect anomalies, and speed up incident response. Learn what it does and its limits.