How do I ensure test results are visible in GitLab?

Use the artifacts:reports syntax to specify JUnit or coverage report paths, allowing GitLab to parse and display them directly within the UI.

How do I cache dependencies like node_modules?

You define a cache key (ideally based on a lock file like package-lock.json) and specify the paths to be cached in your .gitlab-ci.yml configuration.

Does this skill support distributed runners?

Yes, it includes patterns for configuring distributed S3-based caching for GitLab Runners to share cache across different infrastructure nodes.

What is the main difference between artifacts and cache in GitLab CI?

Artifacts are used to pass data between jobs or stages and are guaranteed to persist, while cache is used to speed up job execution by storing dependencies and is considered 'best effort' storage.

Can I use different caching policies?

Yes, you can use 'pull' for jobs that only need to read the cache, 'push' for jobs that update it, or 'pull-push' (the default) for both functions.

GitLab CI Artifacts & Caching

Name: GitLab CI Artifacts & Caching
Author: TheBushidoCollective

byTheBushidoCollective

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Deployment & DevOps

Optimizes GitLab CI/CD pipelines by configuring efficient build artifact management and intelligent dependency caching.

About

This skill empowers developers to streamline GitLab CI/CD workflows by implementing sophisticated data passing and caching strategies. It provides domain-specific patterns for managing job outputs via artifacts, generating automated reports (JUnit, coverage), and accelerating build times through optimized caching of dependencies like node_modules. Whether configuring lock-file-based cache keys or setting up distributed S3 runners, this skill ensures pipelines are reliable, cost-effective, and performant.

Key Features

Configure artifact paths and expiration policies for inter-job data passing
Set up distributed caching configurations for scalable GitLab Runner environments
Generate and manage automated CI/CD reports for testing and code coverage
Define fine-grained cache policies to minimize redundant uploads and downloads
39 GitHub stars
Implement intelligent caching strategies using lock-file keys and fallback mechanisms

Use Cases

Generating and storing JUnit test reports and coverage visualizations for merge requests
Passing build binaries from a compilation stage to deployment without rebuilding
Accelerating JavaScript/Node.js builds by caching heavy node_modules between pipeline runs

About

Key Features

Configure artifact paths and expiration policies for inter-job data passing
Set up distributed caching configurations for scalable GitLab Runner environments
Generate and manage automated CI/CD reports for testing and code coverage
Define fine-grained cache policies to minimize redundant uploads and downloads
39 GitHub stars
Implement intelligent caching strategies using lock-file keys and fallback mechanisms

Use Cases

Generating and storing JUnit test reports and coverage visualizations for merge requests
Passing build binaries from a compilation stage to deployment without rebuilding
Accelerating JavaScript/Node.js builds by caching heavy node_modules between pipeline runs