Redis Caching Patterns That Hold Up in Production
Cache-aside, write-through, read-through, and the stampede protection that separates a cache from a foot-gun. With concrete Java examples.
Tag
Cache-aside, write-through, read-through, and the stampede protection that separates a cache from a foot-gun. With concrete Java examples.
How to replace legacy systems one slice at a time without a big-bang rewrite. The pattern, the gates, and the traps that stretch migrations into years.
What DLQs are, why you must have one for every message consumer, and the operational patterns that keep bad messages from blocking the good ones.
Why every non-trivial backend needs idempotency keys, the common designs, and the mistakes that let duplicates slip through anyway.
Why "save to DB, then publish to Kafka" is almost always wrong, and the outbox pattern that fixes it — with real Java code, schema, and production considerations.
How to coordinate operations across services that each have their own database. Orchestrated vs choreographed sagas, compensating actions, and when to use which.