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.

1 — Why Tracing Exists

Covers the request-fan-out problem that metrics and logs can't solve alone, and why tracing became necessary in microservice architectures.

2 — Trace Context

Covers the trace ID / span ID / trace flags that identify a request and its position in a trace, and how they are carried across process boundaries.

4 — Context Propagation

Covers how trace context survives async boundaries, message queues, and batch jobs — and the common places it silently breaks.

5 — Trace Sampling

Covers head-based sampling decisions made at trace start, and their tradeoff against tail-based sampling on completeness vs. cost.