Observability Engineering

A book-shaped table of contents for observability engineering: foundations through architecture, metrics, logging, tracing, profiling, OpenTelemetry, instrumentation, Kubernetes/cloud, data platforms, visualization, alerting, SRE integration, cost, security, platform engineering, AI-driven operations, and MAANG interview preparation — cross-linking existing prometheus/grafana-cloud/kubernetes/sre/platform-engineering notes instead of duplicating them.

2 — Log Schemas

Covers designing a consistent field schema across services so logs from different teams remain queryable together.

4 — Log Pipelines

Covers the collection-to-storage pipeline for logs — parsing, enrichment, and routing before they land in a backend.

5 — Log Sampling

Covers reducing log volume by sampling non-error traffic while preserving full fidelity on errors and slow requests.

6 — Log Retention

Covers setting retention windows per log tier and the tradeoff between debugging lookback and storage cost.