Applied technology
Technologies in Practice
Kafka, caching, CDC, databases, and reliability tooling — explained through product constraints, operating costs, and implementation trade-offs.
Kafka
Design for ordering, consumer lag, retries, and operational limits.
- Kafka for Real Product Systems
- Partitioning and Ordering
- Retries / DLQ / Consumer Lag
- When Kafka Is Overkill
Caching
Use cache intentionally and keep consistency failure modes visible.
- Redis in Production
- Cache-Aside / Write-Through / Write-Behind
- Cache Invalidation Strategies
- When Cache Makes Consistency Worse
CDC & Data Movement
Capture changes safely and reason about latency, backfills, and replay.
- Debezium
- AWS DMS
- Outbox
- Replication in Practice
Databases
Match storage shape to transactional, analytical, and operational needs.
- PostgreSQL in Practice
- MS SQL in Practice
- Redshift Usage Patterns
- Choosing Storage by Workload
Reliability Tooling
Use locks, jobs, rate limiting, and observability as operating mechanisms, not buzzwords.
- Distributed Locks
- Background Jobs
- Rate Limiting
- Observability for Real Systems