Unity
Unity CI/CD Testing Pipeline: GitHub Actions, GameCI, and Cloud Build
Running Unity tests locally is fine. Running them automatically on every pull request is how you actually catch regressions before they ship.
CI/CD
CI/CD pipeline guides — integrate automated testing into your deployment pipeline and ship with confidence.
Latest
Chaos Engineering
Chaos Engineering in CI/CD: Automating Resilience Validation in Your Pipeline
Most teams run chaos experiments manually — a team gathers, runs an experiment, watches dashboards, and documents findings. This works, but it doesn't scale.
Shift-Left Testing
Shift-Left Testing in CI/CD Pipelines: A Practical Implementation Guide
Shift-left testing changes where quality lives in your delivery pipeline.
Testing
Debugging Webhook Failures in CI: A Systematic Approach
Webhook failures in CI are some of the most frustrating bugs to debug. The test passes locally but fails in CI. The webhook arrives but nothing happens.
CI/CD
Dagger Python SDK: Writing Testable CI Pipelines with Python
The Dagger Python SDK lets you write CI pipelines as ordinary Python functions. No YAML, no DSL — just Python.
CI/CD
Dagger.io Testing Guide: Programmatic CI Pipelines That Actually Test
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
Dagger vs GitHub Actions: When to Use Each for Testing Pipelines
Both Dagger and GitHub Actions run your tests in CI. The difference is how you define and debug those pipelines.
CI/CD
Dagger TypeScript SDK: CI Testing Pipelines for Node.js and Next.js
The Dagger TypeScript SDK lets you write CI pipelines in TypeScript — the same language as your application.
CI/CD
Dagger Integration Tests: Running Real Databases and Services in CI
Integration tests that hit real databases and message queues are harder to run than unit tests.
AI Testing
Continuous LLM Evaluation: Building an Evals Pipeline for Production AI
Deploying an LLM is not a one-time event. Prompts change. Models get updated. Retrieval indexes get refreshed.
Testing
How to Add Smoke Tests to Your CI/CD Pipeline and Gate Deployments
A deployment pipeline without smoke tests is like a fire sprinkler system with no water pressure test. Everything looks fine until the moment you need it.
AI Testing
Agentic Testing Workflows: How AI Agents Run Your Test Suite
Agentic testing means AI agents that autonomously handle steps in the testing cycle — creating tests, running them, analyzing failures, and fixing issues — without waiting for explicit human instruction at each step. This guide covers the patterns, tools, and implementation approach for teams adopting agentic testing workflows in 2026. Key Takeaways