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 — Designing An Observability Platform

Frames a platform-level design exercise: ingestion scale, tenancy, storage tiering, and query latency as first-class requirements.

2 — Data Plane vs Control Plane

Separates the high-throughput telemetry data path from the low-throughput configuration/policy path, and why conflating them causes outages.

4 — Agent Based vs Agentless Collection

Weighs sidecar/DaemonSet agents against agentless eBPF or vendor-API scraping for coverage, overhead, and maintenance cost.

5 — Edge Aggregation

Covers pre-aggregating and filtering telemetry at the collection edge to cut cardinality and egress cost before it reaches the backend.