Chapter 14 — Observability Data Lake
Chapter of AIOps, Cost & Incident Management, part of System Design.
Purpose
Cold/warm/hot tiers, Parquet storage, query federation (Thanos/Cortex/Mimir).
[stub: observability-data-lake]— fill this in. Greppable doc-debt marker.
Metadata
| Dimension | Detail |
|---|---|
| Author | Amit Singh |
| Scope | MAANG interview preparation — not production documentation |
Local graph
Linked from 2 notes
Data Engineering
A book-shaped table of contents for data engineering: foundations and lifecycle, data modeling, storage systems, ingestion and CDC, distributed processing (Spark/Flink), SQL mastery, workflow orchestration, data quality, platform and cloud architecture, pipeline observability, security and governance, performance engineering, system design, and MAANG interview preparation through capstone builds — cross-linking the existing observability book instead of duplicating it.
System Design
Principal/Staff-level system design reference collection for MAANG interview preparation — observability pipelines, distributed systems, reliability engineering, and beyond.
Related notes
Chapter 15 — Cost Optimization Pipeline
Adaptive sampling, metric drop rules, cardinality-aware ingestion.
Chapter 16 — Incident Management Platform
Alert correlation, incident lifecycle, escalation, runbook automation.
Chapter 13 — Runbook Automation / AIOps Engine
LLM-powered diagnosis, trigger-action mappings, safety guardrails.
Chapter 4 — Distributed Tracing Backend
Trace assembly from spans, tail-based vs. head-based sampling.