A production-focused guide to JVM garbage collection — choosing between G1/ZGC/Shenandoah, heap sizing for containers, GC log analysis, finding memory leaks in Spring Boot, and JFR profiling techniques that solved real outages.
A practical guide to thread safety patterns that survive production traffic — covering immutability, concurrent collections, CompletableFuture, rate limiting, and atomic operations with real bug examples.
How to ensure your APIs handle retries gracefully, prevent double charges, and avoid duplicate orders — with full Spring Boot implementation examples.
The mental models that separate senior engineers from juniors — and none of them involve knowing more programming languages or frameworks.
A performance engineering deep-dive covering virtual threads, connection pooling, async I/O, caching layers, read replicas, message batching, zero-copy serialization, and load shedding — with real JMH benchmarks and before/after metrics.
An honest evaluation of event sourcing — when it shines, when it's overkill, the hidden costs nobody warns you about, and a decision framework to help you choose.
A progressive guide to event-driven systems — starting from domain events and building up to Kafka, event sourcing, CQRS, and eventual consistency with full Spring Boot implementations at every stage.
A deep comparison of distributed lock implementations with benchmarks, failure modes, production war stories, and Spring Boot code for each approach
A practical breakdown of fan-out-on-write vs fan-out-on-read, Redis timelines, Kafka event propagation, and caching — with Spring Boot code you can actually run
An opinionated filter of the Gang of Four patterns — which ones you use daily in modern Spring Boot, and which ones the framework already handles for you