CI/CD pipeline guides — integrate automated testing into your deployment pipeline and ship with confidence.
CI/CD
Slow CI pipelines, flaky tests, and unknown test coverage gaps are invisible taxes on engineering velocity. You feel them as "the build is red again" conversations and 40-minute pipeline waits, but without data you cannot quantify them or prioritize fixing them. Datadog CI Visibility gives you that
Deployment Testing
Database migration bugs are among the most damaging deployment failures. A bad migration can corrupt data, lock tables during peak traffic, or make rollback impossible. Most teams test their application code thoroughly and test their migrations barely at all. This guide covers how to build database migration testing into your
Database Testing
A bad database migration is one of the worst production incidents you can have. Unlike a bad code deploy, you can't just roll back — the data is already mutated. A migration that drops a column, truncates a table, or corrupts data during a lock-heavy ALTER can take
Test Reliability
Retry logic in CI pipelines feels like a practical solution to flaky tests. Test fails? Run it again. If it passes on the second try, merge. Engineers can keep working, pipelines stay green, velocity is maintained. The problem: you're not fixing the flakiness. You're hiding it.
Data Testing
Software engineers have spent decades building CI/CD practices that make deployments safe and reliable. Data engineers are catching up—and the lessons transfer directly. A data pipeline CI/CD system automatically tests every change before it reaches production, catches regressions before they corrupt your warehouse, and gives teams the
Testing
Recording tests in Repeato's desktop app is one thing — getting them running automatically on every commit is another. Repeato provides a CLI tool that runs tests headlessly, which means you can wire it into GitHub Actions, Jenkins, GitLab CI, or any other pipeline that can run shell commands.
Testing
A Cucumber test suite with 200 scenarios running sequentially might take 10-15 minutes. That's too long for a feedback loop during development and an obstacle in CI pipelines. Parallel execution can cut that to 2-4 minutes, but it requires making your tests thread-safe. This guide
No-Code Testing
A no-code testing tool is only valuable if the tests run automatically and stay up to date as your application changes. Reflect.io's CI/CD integration and AI-assisted maintenance solve both challenges. This guide covers deploying Reflect tests in your pipeline and managing test health over
Code Coverage
Coverage gates block pull request merges when new code isn't adequately tested. Set them up using Codecov, SonarQube, or custom scripts in GitHub Actions. The key is enforcing patch coverage (new code) rather than project coverage (overall), which prevents penalizing teams for pre-existing gaps. Key Takeaways Enforce
Performance Testing
Core Web Vitals are Google's user-experience metrics that directly impact search rankings. Most teams check them manually in PageSpeed Insights—once a quarter, usually after someone notices traffic dropped. That's reactive and slow. This guide shows you how to measure LCP, CLS, and INP automatically
Copado
Standard Salesforce deployment is manual, error-prone, and doesn't scale. Change sets break when dependencies are missing. Direct org-to-org deployments overwrite each other when multiple developers are working in parallel. Copado's CI/CD pipeline replaces this with a Git-based, automated process where every
Testing
Running Ranorex tests in CI is not as simple as pointing a script at your test suite and pressing go. GUI automation requires a display, a licensed runner, and some thought about parallelism. This guide covers the actual setup — command-line execution, environment requirements, and pipeline configuration for Jenkins, Azure