Debug-action-cache _top_ Access

On Linux:

Add a step after restore to list the cached directory:

Using debug-action-cache to find the exact key to delete:

The operation of a debug-action-cache can be broken down into a few straightforward steps:

: To ensure the validity and accuracy of cached results, cache invalidation strategies are employed. This may involve removing entries from the cache based on certain criteria, such as when related code changes are made, or after a specified period. debug-action-cache

The debug-action-cache process is the bridge between the theoretical speed of incremental builds and the practical reality of software complexity. As we move toward more distributed and cloud-native development environments, the ability to peer into the cache and resolve discrepancies is no longer an optional skill—it is a fundamental requirement for maintaining stable, scalable, and fast development cycles.

Some advanced users also set RUNNER_TOOL_CACHE_DEBUG to true , but ACTIONS_STEP_DEBUG triggers the specific debug-action-cache protocol.

| Symptom | Debug Log Evidence | Fix | | :--- | :--- | :--- | | Cache never restores | GET response: 404 for all keys | Check hashFiles glob pattern. Use ls before cache step to ensure file exists. | | Cache restores empty folder | Path '/cache/node_modules' does not exist | Your path is relative. Use absolute path or $ github.workspace /node_modules . | | Cache upload takes 20 minutes | Compressing 50,000 files | You are caching temporary files (e.g., __pycache__ ). Add !**/__pycache__ to exclude. | | Cache uses too much space | Cache size: 11.2GB (exceeds 10GB limit) | Split cache: One for node_modules , one for build . Use actions/cache/save conditionally. | | Random cache misses | restoreKeys: [ 'Linux-node-' ] matches Linux-node-stable | Make your restore-keys more specific, e.g., $ runner.os -node-$ github.ref - |

A slow CI/CD pipeline can be a major productivity bottleneck, and inefficient caching is often the hidden culprit. In the world of GitHub Actions, effective caching is a cornerstone of performance, yet it is also a common source of mysterious failures and wasted time. The concept of "debug-action-cache" isn't a specific command or tool—it is a systematic approach to identifying, diagnosing, and resolving issues related to the actions/cache utility. This guide provides a deep dive into the architecture of GitHub Actions caching and offers actionable strategies for troubleshooting when things go wrong, ensuring your workflows run as efficiently as possible. On Linux: Add a step after restore to

Cache saved successfully with key: ubuntu-latest-npm-abc123...

Combine this with debug-action-cache logs from the workflow run (download the raw logs). Match the cacheKey from the API with the Cache restored from key in the logs. If the last_accessed_at is older than your run, your restore key is wrong.

This guide provides a comprehensive overview of debugging the GitHub Actions cache

Run Bazel with --verbose_failures to see if there are errors reading from or writing to the remote cache 2.2.1. As we move toward more distributed and cloud-native

step to output detailed logs, including the internal API calls used to check for existing cache versions. GitHub Docs 2. Inspecting Cache States via the UI

Enable ACTIONS_RUNNER_DEBUG as before, but also set CACHE_DEBUG=TRUE in your step's environment:

: Utilizes actions like actions/cache to store npm nodes, Ruby gems, or Cargo registries based on explicit cache keys.