ENGINEERING

Auto-file a budget-breach postmortem ticket when an SLO blows its window

When a Honeycomb SLO exhausts its error budget for the compliance window, it creates a Linear postmortem issue pre-filled with the burn timeline and recent Vercel deploys.

CategoryEngineering
Enginesim
Difficultyintermediate
Triggerwebhook
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerHoneycomb SLO budget-exhausted webhookHoneycomb
  • ActionPull burn-rate timeline from HoneycombHoneycomb
  • ActionList Vercel deploys in the breach windowVercelVercel
  • ActionCreate pre-filled Linear postmortem issueLinearLinear
  • OutputNotify owning team in SlackSlack

What it does

Makes budget breaches automatically accountable. When a Honeycomb SLO burns through its budget for the full compliance window, this workflow assembles the context an investigator needs: the burn timeline from Honeycomb and the list of Vercel production deploys in that window. It files a Linear postmortem issue with that evidence attached and assigns it to the service owner.

When to use it

Use it when your team commits to a postmortem for every error-budget breach and you want the paperwork started automatically with real data instead of a blank template days later. Good for teams with an SLO review cadence.

How it works

  1. 1A Honeycomb SLO budget-exhausted webhook triggers the flow.
  2. 2The workflow pulls the burn-rate timeline for the breached window from Honeycomb.
  3. 3It queries the Vercel API for production deployments during that window.
  4. 4It creates a Linear postmortem issue pre-filled with the timeline, suspect deploys, and owner assignment.
  5. 5It posts a Slack note linking the new postmortem issue to the owning team.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HoneycombDistributed traces and queries.
  2. 2
    Connect VercelDeploys, runtime logs, analytics.
  3. 3
    Connect LinearIssues, projects, cycles, triage.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  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.

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