Tag archive

#resilience

Topic-specific entry points for internal linking, discovery, and deeper subject exploration.

8 articles

Backpressure Propagation: Designing Flow Control in Microservices

Backpressure Propagation When your database is slow, your worker is slow. When your worker is slow, your Kafka consumer lags. When Kafka lags, your producer buffer fills up. Backpressure is the signal that propagates thi…

Apr 20, 20263 min read

Deep DiveReliability Engineering Mastery

#backpressure#resilience#microservices

System DesignAdvanced

Graceful Degradation: Feature Shedding

Graceful Degradation Most distributed systems do not fail all at once. They degrade in layers: rising tail latency, thread pool saturation, cache misses, partial dependency outages, then total user-visible failure. Grace…

Apr 20, 20264 min read

Deep Dive

#reliability#system-design#resilience

MessagingAdvanced

Retry Queues vs. DLQ: Architecting Resilient Message Consumers

Retry Queues vs. DLQ: Beyond Simple Retries In a high-scale messaging system, failures are not a matter of 'if', but 'when'. Most developers make the mistake of either retrying indefinitely (blocking the partition) or dr…

Apr 20, 20261 min read

Comparison

#kafka#messaging#resilience

JavaAdvanced

Spring Boot Timeouts: The Production Guide for HTTP, DB, Redis, and Kafka

Timeouts are one of the highest-return production settings in a Spring Boot service. Without them, slow dependencies turn into stuck threads, connection pool exhaustion, retry storms, cascading failures, and deploys that…

Apr 8, 20269 min read

Deep Dive

#spring boot#timeouts#java

JavaAdvanced

Spring Boot Production Readiness Checklist: Timeouts, Pools, Health Checks, and Observability

Spring Boot makes it easy to start a service. Production makes it clear whether the service is actually ready. A production-ready service is not just one that passes unit tests. It has bounded timeouts, sane thread pools…

Apr 7, 20264 min read

Deep Dive

#spring boot#production readiness#java

System DesignAdvanced

Designing a Retry System Without Causing a Retry Storm

Retry logic is the second most dangerous code in a distributed system, after "delete all records." The intent is to improve reliability by recovering from transient failures. The actual effect, when implemented naively,…

May 22, 202510 min read

Deep Dive

#retry#circuit breaker#resilience

JavaIntermediate

Thread Pool Exhaustion in Spring Boot: Diagnosis, Prevention, and Recovery

Thread pool exhaustion is one of the most deceptive production failures in Spring Boot services. The service is technically running — JVM process alive, health endpoint returning 200, no OutOfMemoryError in logs — but re…

Apr 8, 20259 min read

Deep Dive

#spring boot#java#tomcat

System DesignAdvanced

Microservices Patterns: Circuit Breaker, Retry, Bulkhead, and Saga

A monolith fails as a unit — one process, one crash, everything stops. A microservices system fails differently: some services go down, some slow to a crawl, some remain perfectly healthy. This partial-failure behaviour…

Feb 28, 202514 min read

Deep Dive

#microservices#resilience#circuit breaker