Platform Engineering
Crossplane turns Kubernetes into a universal control plane for infrastructure — but untested compositions are ticking time bombs. This guide covers the full Crossplane testing stack: unit-style testing with kuttl, Uptest for provider integration tests, composition validation with crossplane beta validate, and end-to-end infrastructure tests that provision real cloud resources in
CI/CD
The Dagger Python SDK lets you write CI pipelines as ordinary Python functions. No YAML, no DSL — just Python. You can import Dagger functions like any library, test them with pytest, and run them locally with the same command that runs in CI. This guide focuses on practical patterns: running
CI/CD
Dagger.io flips the CI/CD model on its head: instead of YAML pipelines that are impossible to test locally, you write your pipelines in Python, TypeScript, or Go — and run them anywhere. The same pipeline runs on your laptop, in GitHub Actions, and in GitLab CI without modification. This
CI/CD
Both Dagger and GitHub Actions run your tests in CI. The difference is how you define and debug those pipelines. This guide compares them on the things that matter when you're running test suites: local execution, caching, services, parallelism, and debugging when something breaks. The Core Difference GitHub
CI/CD
The Dagger TypeScript SDK lets you write CI pipelines in TypeScript — the same language as your application. Your pipeline is type-safe, unit-testable, and runs identically on your laptop and in GitHub Actions. This guide focuses on Node.js and Next.js testing workflows: running Vitest, Jest, Playwright, and integrating with
CI/CD
Integration tests that hit real databases and message queues are harder to run than unit tests. In GitHub Actions, you configure service containers in YAML and hope they start before your tests run. In Dagger, you define services as code, bind them to your test container, and get the same
Testing
Performance is a feature in games. A 60 FPS game feels completely different from the same game at 30 FPS. Players notice stutters, long load times, and frame drops — and they stop playing. Performance testing catches regressions before players experience them. This guide covers tools and techniques for profiling game
Testing
Webhook signature verification is the one security control standing between your server and arbitrary POST requests. If you're not testing it, you're trusting that your implementation is correct — which is how security bugs get shipped. This guide covers how to test HMAC and JWT signature verification
Testing
MQTT is the backbone of most IoT systems — lightweight, broker-based, designed for unreliable networks. Testing MQTT is different from testing REST APIs: you're testing asynchronous publish/subscribe flows, quality of service levels, retained messages, and broker behavior under load. This guide covers practical MQTT testing strategies from unit
Testing
Game testing is often manual — play through levels, look for bugs. But most game logic is testable code: inventory systems, physics interactions, AI decisions, save/load functionality. The Unity Test Framework brings standard unit and integration testing to game development. This guide covers how to write meaningful automated tests for
Testing
Webhooks are notoriously hard to test. They arrive asynchronously, carry cryptographic signatures, and the service sending them is usually not your code. Mock servers solve this by letting you simulate incoming webhook events locally — without waiting for real events from Stripe, GitHub, or Shopify. This guide shows how to set
Testing
Testing IoT firmware is hard. You need hardware that may be scarce, expensive, or not yet manufactured. A device crash takes seconds to reproduce but hours to debug without proper tools. Simulators change this equation — they let you run firmware tests on any CI server without touching real hardware. This