ENGINEERING

Flag runbooks stale since the service last deployed

On a weekly schedule, compares each service's last GitHub release date against the last-edited date of its Confluence runbook.

CategoryEngineering
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule fires the audit
  • ActionFetch latest release date per repo from GitHubGitHubGitHub
  • ActionRead runbook last-modified date from ConfluenceConfluenceConfluence
  • LogicKeep runbooks older than their service's last deploy
  • LogicRank stale runbooks by staleness window
  • OutputPost ranked staleness digest to SlackSlack

What it does

Surfaces on-call runbooks that have drifted behind the code they document. For each service, it reads the latest GitHub release timestamp and the matching Confluence runbook's last-modified date, then flags any runbook older than its newest deploy so owners know exactly what needs a refresh.

When to use it

Run it weekly when your runbooks live in Confluence and you ship through tagged GitHub releases. It is the lightweight first line of defense against the classic incident-night surprise of a runbook describing infrastructure that changed three deploys ago.

How it works

  1. 1A weekly schedule fires the audit.
  2. 2It pulls the latest release per repo from GitHub, capturing the published-at date.
  3. 3It fetches each service's runbook page from Confluence and reads its last-updated timestamp.
  4. 4A comparison step keeps only services whose runbook date is earlier than the release date.
  5. 5Stale entries are formatted into a ranked digest (oldest gap first).
  6. 6The digest is posted to a Slack channel, tagging each runbook owner with the staleness window in days.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitHubRepos, issues, pull requests, actions.
  2. 2
    Connect ConfluenceSpaces, pages, blueprints.
  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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