ENGINEERING

Require a Linear approval when burn rate is borderline before promoting

When a Vercel promotion is requested and the Honeycomb burn rate sits in a warning band, it holds the promotion and opens a Linear issue requiring a named approver to sign off…

CategoryEngineering
Enginesim
Difficultyintermediate
Triggerwebhook
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerVercel promotion requested webhookVercelVercel
  • ActionRead SLO burn rate from HoneycombHoneycomb
  • LogicClassify: healthy / warning / critical
  • ActionOpen Linear approval issue for warning bandLinearLinear
  • OutputNotify owner in Slack with approval linkSlack

What it does

Adds a human gate only when the data is ambiguous. Instead of blocking outright, this workflow looks at the Honeycomb SLO burn rate at promotion time. If it is in a borderline warning band (healthy but trending hot), it pauses the promotion and creates a Linear approval issue assigned to the on-call owner. The promotion resumes only after the issue is marked approved.

When to use it

Use it when a hard auto-block is too blunt but you still want a checkpoint for risky-looking deploys. Good for teams who want a documented, auditable approval trail in Linear for every borderline release.

How it works

  1. 1A Vercel promotion-requested webhook starts the flow.
  2. 2The workflow pulls the current burn rate for the service's SLO from Honeycomb.
  3. 3A branch routes: healthy passes through, critical hard-blocks, and the warning band falls through to approval.
  4. 4For the warning band it opens a Linear issue with the burn-rate context and assigns the on-call owner.
  5. 5It posts a Slack message linking the Linear issue and noting the promotion is held pending sign-off.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect VercelDeploys, runtime logs, analytics.
  2. 2
    Connect HoneycombDistributed traces and queries.
  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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