CI/CD Patterns and Antipatterns - Things your Pipeline Should (Not) Do

Is your CI pipeline a slow, frustrating ritual? Learn the patterns to eliminate flaky builds, reduce developer wait times, and ship code faster.

#1about 2 minutes

The hidden costs of slow and frustrating CI/CD pipelines

Slow, frustrating, and wasteful CI/CD pipelines interrupt developer flow and have a negative environmental impact.

#2about 3 minutes

Antipattern: Running the same pipeline for every trigger

The 'ritual' antipattern involves wastefully running identical, comprehensive pipelines for pull requests, merges, and nightly schedules.

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Use conditional logic to run only necessary steps

Create context-specific pipelines for different triggers and use path filtering to run only the jobs relevant to the code that has changed.

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Antipattern: Stop hoarding unnecessary build artifacts

The 'hoarding' antipattern wastes storage and makes navigation difficult by keeping every build artifact indefinitely instead of using automated cleanup.

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Antipattern: Order pipeline steps for the fastest feedback

Prioritize tests that are most likely to fail, such as integration tests, to get feedback faster instead of following a conventional testing pyramid order.

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Antipattern: Break monolithic pipelines into parallel jobs

Replace a single, long-running sequential pipeline with multiple parallel jobs for independent components like frontend and backend to significantly reduce wall-clock time.

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Antipattern: Use caching and tooling images to avoid redundant work

Leverage caching for dependencies, build outputs, and Docker layers, and use pre-built tooling images to avoid starting from scratch on every run.

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Antipattern: Prevent pipeline interference with unique identifiers

Avoid race conditions where concurrent pipelines overwrite shared resources like a 'latest' tag by using unique identifiers like the Git SHA for artifacts.

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Antipattern: Properly size your build agents and runners

Ensure build agents are at least as powerful as developer machines to prevent resource-related failures, and consider self-hosted runners for full control over hardware.

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