Study notes
Data systems, read and built closely.
Chapter-by-chapter notes on Designing Data-Intensive Applications and Kafka: The Definitive Guide, plus hands-on PostgreSQL and ClickHouse modules — the argument in order, every figure and diagram redrawn, the production failure modes catalogued, and a self-test at the end of each chapter.
- 50
- chapters
- 408
- sections
- 607
- figures
- 686
- terms
- 109
- cross-links
DDIA
Designing Data-Intensive Applications
14 chapters
Kafka
Kafka: The Definitive Guide
15 chapters
PostgreSQL
PostgreSQL
11 chapters
ClickHouse
ClickHouse
10 chapters
Roadmap
P5RedisData structures, caching, pub/sub, distributed locks
P6RabbitMQExchanges, queues, routing, dead letters, retries
P7MinIOS3-compatible object storage, buckets, presigned URLs
P8ObservabilityPrometheus, Grafana, Loki, distributed tracing
P9NginxReverse proxy, load balancing, TLS, caching
P10KubernetesPods, deployments, services, StatefulSets, Helm
the rule
For every technology: what problem does it solve, why wasn't something else enough, how does it work internally, how is it deployed, monitored, scaled, and backed up — and what actually breaks in production. If you can answer those, you've learned it, not memorized it.
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