webcoderspeed.com
19 articles
Design API gateways for rate limiting, JWT auth, request aggregation, and versioning. Learn gateway vs service mesh and Kong vs cloud vendors.
Master thread pool isolation, semaphore-based bulkheads, tenant isolation, and failure injection testing for fault-tolerant systems.
You added a circuit breaker to protect against cascading failures. But it never opens — requests keep failing, the downstream service stays overloaded, and your system doesn''t recover. Here''s why circuit breakers fail silently and how to configure them correctly.
Order created at 10:00. Order cancelled at 10:01. Your consumer processes them in reverse — cancellation arrives first, then creation "succeeds." The order is now in an invalid state. Event ordering bugs are subtle, expensive, and entirely avoidable.
User updates their profile. Refreshes the page — old data shows. They update again. Still old data. They''re furious. Your system is eventually consistent — but nobody told the user (or the developer who designed the UI). Here''s how to manage consistency expectations in distributed systems.
Build federated GraphQL APIs across microservices. Learn Apollo Federation architecture, @key and @external directives, entity resolution, router configuration, performance with DataLoader, query planning, cost limits, and observability.
Build production gRPC services in Node.js. Learn Protocol Buffer schema design, server setup with @grpc/grpc-js, unary and streaming communication, interceptors for auth/logging, grpc-gateway for REST compatibility, health checking, and reflection for debugging.
Network timeout on a payment request. Client retries. Customer gets charged twice. This is the most expensive bug in fintech — and it''s completely preventable with idempotency keys. Here''s the complete implementation.
Learn how to integrate LLM calls into microservice architectures with async patterns, job queues, and service contracts that don''t introduce latency bottlenecks.
You split your MVP into 12 microservices before you had 100 users. Now a simple feature requires coordinating 4 teams, 6 deployments, and debugging across 8 services. The architecture that was supposed to scale you faster is the reason you ship slower than your competitors.
The industry consensus has shifted. Here''s why modular monoliths are winning and when microservices still make sense.
In distributed systems, failure is never all-or-nothing. A service returns a response — but it''s corrupt. An API call times out — but the action already executed. A message is delivered — but the reply never arrives. This is partial failure, and it is the hardest problem in distributed systems.
Two requests check inventory simultaneously — both see 1 item in stock. Both proceed to purchase. You ship 2 items from 1. Race conditions in distributed systems are subtler than single-process races because you can''t use mutexes across services. Here''s how to prevent them.
Your service is degraded, returning errors 30% of the time. Smart clients with retry logic start hammering it — 3 retries each means 3x the load on an already failing system. The retry storm amplifies the original failure until full collapse. Here''s how to retry safely.
Master choreography and orchestration sagas, compensation transactions, and failure handling for distributed transaction management without 2PC.
You rename a column. The new service version uses the new name. The old version, still running during the rolling deploy, tries to use the old name. Database error. The migration that passed all your tests breaks production because both old and new code run simultaneously during deployment.
You split into microservices but all of them share the same PostgreSQL database. You have the operational overhead of microservices with none of the independent scalability. A schema migration blocks all teams. A bad query in Service A slows down Service B.
Service A calls Service B synchronously. Service B calls Service C. Service C calls Service A. Now a deploy to any of them requires coordinating all three. A bug in Service B takes down Services A and C. This isn''t microservices — it''s a distributed monolith.
Build zero trust backend with mTLS, SPIFFE identities, service-to-service JWT tokens, request signing, and dynamic database credentials via Vault.