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Speed up GitHub Actions by caching reusable dependencies and running independent jobs at the same time. Build cache keys from dependency inputs such as lockfiles, make sure installs still work after a cache miss, and use needs only where one job truly depends on another. Caches reduce repeated downloads; artifacts preserve or pass job outputs. Neither caching nor parallelism guarantees a fixed time saving, so compare actual run durations and cache-hit rates in your repository.
Find the work that is making the workflow slow
Start with representative workflow runs and identify where elapsed time goes: installing dependencies, compiling, testing, waiting for runners, or executing independent work in sequence. The remedy depends on the bottleneck. A dependency cache can reduce repeated downloads, while parallel jobs can overlap independent tasks; neither helps much if the work is elsewhere or runners are unavailable.
GitHub-hosted runners start with a clean runner image, so tools such as npm, Yarn, Maven, and Gradle may repeatedly download packages. GitHub describes caching as a way to reduce that repeated work, but does not promise a particular time saving. Measure run duration and cache hits before and after a change rather than assuming an improvement.
Cache dependencies that are expensive to recreate
Use a cache for downloaded packages or other reusable files that are costly to regenerate. GitHub’s dependency caching guide cautions that jobs should still be able to re-download or regenerate files when a cache is unavailable. A cache is an optimization, not the authoritative source of required dependencies.
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Build keys from dependency inputs
Include context that affects the cached contents—commonly the operating system, tool context, and dependency lockfile hash—in the key. A changed lockfile should produce a different key, avoiding reuse of a cache built for a different dependency set.
Configure restore-key prefixes from most specific to least specific. If the exact key is absent, the cache action can look for a useful prefix match. GitHub’s dependency caching reference explains matching, restore keys, and branch-based cache scope. A matching key does not remove the need to run the package manager’s install step: cache entries can be absent, out of scope, or evicted.
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Keep installation recoverable
Structure the workflow so the normal install command can fetch missing packages. This makes a cache miss a slower run rather than a failed build. Check hit and miss behavior in actual runs; an oversized cache or a poor hit rate may not save time.
Choose a cache or an artifact based on what the file is for
| Choice | Use it for | Important trade-off |
|---|---|---|
| Dependency cache | Reusing packages or intermediate files across workflow runs. | It can miss, be scoped, or be evicted; the workflow must be able to recover without it. Restored contents also have security implications. |
| Artifact | Preserving a job’s output, such as a build product, test report, or log, or passing files between jobs. | It represents output to retain or share, not a reusable dependency cache. |
GitHub documents these as separate features: see dependency caching and workflow artifacts. Use the feature that matches the file’s lifecycle rather than treating caches and artifacts as interchangeable.
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Run independent jobs in parallel
GitHub Actions runs workflow jobs in parallel by default. Separate independent test suites, platform builds, or version checks into different jobs—or use a matrix when the same job should run with multiple configurations. Parallelism can shorten elapsed time only if tasks can overlap and runner capacity is available; it can also consume more concurrent resources and Actions minutes.
Use needs only for real prerequisites
Set needs when a job requires another job to finish first, such as a deployment that depends on a successful build. Jobs without that dependency can start independently. Adding unnecessary dependencies creates a serial chain and prevents otherwise independent work from overlapping. See GitHub’s workflow syntax reference.
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Use matrices for repeated configurations
A matrix expands a job across combinations such as operating systems or runtime versions. Matrix jobs are not guaranteed to run in a particular order. Set max-parallel when a large fan-out would exceed useful runner capacity or put too much load on an external service. GitHub’s matrix guidance covers variations and parallel limits.
As listed in GitHub’s Actions limits documentation accessed in 2026, a workflow run can expand to at most 256 matrix jobs. The same page lists standard GitHub-hosted runner concurrent-job totals of 20 for Free, 40 for Pro, 60 for Team, and 500 for Enterprise, as well as separate macOS caps. These are service limits, not a guarantee that a particular repository can start that many jobs simultaneously. Limits can change, so check the current page and your plan when planning fan-out.
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Use concurrency to prevent conflicts or cancel stale work
The concurrency setting controls overlapping executions; it is not a way to increase parallelism. It can keep deployments from overlapping or cancel checks for outdated commits. GitHub’s concurrency documentation says that, by default, only one run in a concurrency group can be pending; a newly pending run cancels the earlier pending one. If work should wait in order instead of being replaced, use the documented queue option where appropriate. Avoid concurrency groups for work that should run side by side.
Protect cache contents and monitor cache limits
Never put tokens, credentials, or other secrets in a cache. A workflow that can read an entry receives its contents, and cache access follows branch and tag scopes rather than job identity. Treat restored files as untrusted, especially when lower-trust events can read them. GitHub describes read-only defaults for low-trust triggers; explicitly granting cache write access can reintroduce cache-poisoning risk. Review the security guidance in Dependency caching before changing permissions.
GitHub’s dependency caching reference, accessed in 2026, gives a default total cache size of 10 GB per repository and says entries not accessed for more than seven days are removed. Organization settings can configure different size or retention limits; see organization Actions settings for configurable controls. The Actions limits page, also accessed in 2026, lists cache-operation limits of 200 uploads, 1,500 downloads, and 400 deletes per minute per repository. These defaults and service limits can change; check the current documentation and your organization’s settings.
Quick Recap
Apply changes in a useful order
- Measure: inspect representative runs and identify whether installation, compilation, tests, queueing, or serial job dependencies dominate.
- Cache reusable files: select the package manager’s local cache, create keys from relevant dependency inputs, and add ordered restore-key prefixes.
- Preserve the fallback: leave the install or regeneration path able to succeed on a cache miss.
- Separate independent work: use jobs or a matrix for work that can overlap, and encode only actual prerequisites with
needs. - Set operational controls: cap matrix fan-out with
max-parallelif needed; use concurrency groups only to manage conflicting or obsolete runs. - Compare results: review durations, cache hits, and resource use across runs to see whether the changes helped this repository.
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