DEVOPS

Dropbox CI Artifact Retention Sweeper

On a nightly schedule, scans a Dropbox build-artifacts folder, deletes files older than the retention window unless they back a live GitHub release tag.

CategoryDevOps
Enginesim
Difficultyintermediate
Triggerschedule
Steps7
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNightly schedule fires
  • ActionList Dropbox artifacts folderDropboxDropbox
  • LogicKeep files older than retention window
  • ActionFetch live GitHub release tagsGitHubGitHub
  • LogicSpare artifacts backing a live release
  • ActionDelete stale artifacts from DropboxDropboxDropbox
  • OutputPost deletion report to SlackSlack

What it does

Each night this workflow walks your Dropbox build-artifacts folder, finds every file past the retention window, and checks each candidate against your live GitHub release tags before deleting. Artifacts that still back a published release are spared; everything else stale is pruned. A summary of what was kept, deleted, and reclaimed lands in Slack.

When to use it

Use it when CI dumps build outputs to Dropbox and the folder grows without bound. It enforces a clear retention policy automatically while guaranteeing you never delete an artifact a current release still depends on.

How it works

  1. 1A nightly schedule fires the sweep.
  2. 2List the Dropbox artifacts folder with file paths, sizes, and modified dates.
  3. 3A filter keeps only files older than the retention window (e.g. 30 days).
  4. 4Fetch current GitHub release tags and match each stale file against the set.
  5. 5A branch spares any artifact tied to a live release; the rest are marked for deletion.
  6. 6Delete the marked files from Dropbox.
  7. 7Post a Slack report listing deleted count, spared count, and bytes reclaimed.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect DropboxFiles and folders.
  2. 2
    Connect GitHubRepos, issues, pull requests, actions.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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