GitLab CI/CDGitLab ArtifactsGitLab CachePipeline Optimization

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GitLab Artifacts vs Cache Explained

Understand when to use GitLab artifacts, cache, or both, including dependency flow, retention, security, cache keys, reports, storage, and pipeline performance.

CI artifacts preserved between stages while dependency cache accelerates future jobs
CI artifacts preserved between stages while dependency cache accelerates future jobs
Contents

Artifacts and cache solve different pipeline problems. Artifacts preserve job outputs for later jobs, reports, downloads, or deployments. Cache reuses dependency data to reduce repeated downloads or computation. A pipeline often uses both, but never for the same purpose.

Quick comparison

CharacteristicArtifactsCache
Primary purposePreserve outputs and reportsReuse dependencies or intermediate reusable data
Typical examplesPackages, binaries, test reports, logsPackage-manager downloads, compiler cache
Reliability expectationRequired output for downstream workPerformance optimization that may be missing
RetentionExplicit expiry and project storageCache policy and backend lifecycle
Security concernSensitive output and download accessCache poisoning and cross-branch reuse

Use artifacts for required outputs

If a downstream job must consume exactly what an upstream job produced, use artifacts or an artifact repository. Preserve immutable packages, test reports, coverage data, and deployment manifests with appropriate expiry and access controls.

Use cache for acceleration

Cache package-manager downloads or compiler state that can be regenerated safely. A job should still work when the cache is empty. Choose keys that prevent incompatible branches, architectures, lock files, or tool versions from sharing data.

A common combined pattern

  1. Restore a dependency cache using a lock-file-based key.
  2. Install dependencies and update the cache if policy allows.
  3. Build the application.
  4. Publish the build output as an artifact.
  5. Download that artifact in test or deployment jobs.
  6. Promote release packages to a durable repository when needed.

Security controls

  • Do not cache credentials or decrypted secret files.
  • Separate protected and untrusted branch caches.
  • Avoid executable cache content from unknown pipelines.
  • Set artifact access and expiry deliberately.
  • Scan release artifacts and preserve checksums.
  • Do not treat short-lived job artifacts as a permanent release repository.

Performance diagnosis

Measure download time, archive creation, extraction, cache hit rate, artifact size, and storage growth. A cache can slow a pipeline when large archives are uploaded and downloaded even though dependencies change frequently.

The rule is simple: artifacts carry required results forward; cache makes repeatable preparation faster. If losing the data would make the pipeline incorrect, it should not exist only in cache.

GitLab job artifacts documentation

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