SUMMARIZATION

Draft a release postmortem in Confluence from Sentry health

When a Sentry release is marked as a bad deploy, compiles its error signatures, regression timeline, and crash-rate impact into a pre-filled postmortem page in Confluence ready…

CategorySummarization
EngineSim + Paperclip
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerSentry release flagged bad deploySentrySentry
  • ActionPull issues, timeline, and commitsSentrySentry
  • ActionFetch linked GitLab commitsGitLabGitLab
  • ActionDraft postmortem sectionsOpenAI
  • OutputCreate pre-filled Confluence pageConfluenceConfluence

What it does

This workflow jump-starts the postmortem. When a Sentry release is flagged as a problem deploy, it gathers the error signatures, the crash-rate timeline, affected user counts, and the linked commits, then drafts a structured incident write-up as a Confluence page with summary, impact, and timeline sections already filled in.

When to use it

Use it after a rough release when writing the postmortem from scratch is the part nobody wants to start. It produces a solid first draft so the team edits rather than authors from a blank page.

How it works

  1. 1Sentry fires a webhook when a release is tagged as a bad deploy.
  2. 2The flow pulls the release's issues, crash-rate timeline, and associated GitLab commits.
  3. 3An OpenAI step organizes everything into summary, user-impact, root-signature, and timeline sections.
  4. 4A Confluence page is created from a postmortem template, pre-populated with that content and linked back to Sentry and the commits for review.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect SentryErrors, performance, releases.
  2. 2
    Connect ConfluenceSpaces, pages, blueprints.
  3. 3
    Connect GitLabRepos, MRs, pipelines, registry.
  4. 4
    Connect OpenAIModels, embeddings, files.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

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