Testing
Testing NestJS microservices is harder than testing monolithic HTTP apps because you now have distributed components, message brokers, and transport-specific behavior to deal with. The test strategy depends on what you're testing: the message handler logic itself, the transport serialization, or the end-to-end flow across services. This guide
Testing
Unit testing in NestJS is not complicated, but it does require understanding how the framework's dependency injection container works. Once you get that, writing fast, isolated tests for services, controllers, and providers becomes straightforward. This guide walks through the real mechanics — no hand-waving. How NestJS Testing Works NestJS
Testing
End-to-end tests for NestJS apps test the full HTTP stack — routing, guards, pipes, middleware, serialization — without deploying to a server. You boot your actual NestJS application inside the test process, send real HTTP requests against it, and assert on real HTTP responses. No mocks, no shortcuts. This guide covers how
Testing
Testing GraphQL APIs in NestJS requires a different approach than REST. The entry point is always POST /graphql, the response is always 200 OK (even for errors), and you need to think about resolvers, subscriptions, schema validation, and the N+1 problem. This guide covers all of it. Testing Resolvers
Testing
Firebase Cloud Messaging (FCM) is the backbone of push notifications for Android, iOS, and web apps, but testing it without hitting real devices is a challenge most teams skip. This guide shows how to write reliable unit tests for FCM payloads, multicast sends, and topic subscriptions using unittest.mock in
Testing
Authentication bugs are some of the most costly bugs to ship. Testing fastify-jwt means verifying that protected routes reject unauthenticated requests, that expired tokens fail gracefully, that the refresh flow issues new tokens correctly, and that RBAC rules enforce role boundaries. This post covers all four, with test patterns you
Testing
Fastify's plugin system is one of its best features — and one of the trickier things to test properly. This post covers how to use inject() for in-process route testing, how to verify lifecycle hooks fire in the right order, and how to assert that decorators are registered and
Node.js
BullMQ is the modern successor to Bull for Node.js background job processing. It uses Redis for persistence and supports advanced patterns: priorities, rate limiting, flows (parent/child jobs), and job groups. Testing BullMQ requires understanding when to use real Redis versus mocks, and how to make workers testable. Testing
Testing
Socket.io applications require testing at three layers: the HTTP upgrade handshake, the event protocol layer (emit/on, ACKs, rooms), and real concurrency behavior under load. This guide covers in-process test setup, Jest event testing, middleware mocking, and scalable load patterns. Socket.io is the de-facto standard for bidirectional real-time
Testing
Alexa Skill testing requires a layered approach: unit tests for individual intent handlers, integration tests for full request/response cycles, and end-to-end simulation with Bespoken. This guide covers all three layers with concrete examples in Node.js and Python. Building a reliable Alexa Skill is only half the battle. Without
Node.js
Building a CLI tool with oclif is pleasantly structured. Each subcommand is a class with a run() method. Flags and args are declared statically. The framework handles parsing, help generation, and error formatting. The problem is that most teams treat this structure as incidental and test nothing until something breaks
Monorepo
pnpm workspaces provide a lightweight monorepo solution built into the pnpm package manager. Unlike Nx or Turborepo, pnpm workspaces have no build graph awareness or caching — they give you the foundation to run commands across packages, and you layer tooling on top. Understanding how to run tests across packages, share