ENGINEERING

On-demand release-health triage agent in chat

A chat-triggered agent that investigates a named release on request — pulling Sentry crash-free health, Honeycomb traces, and the GitHub commit range — then recommends hold.

CategoryEngineering
Enginepaperclip
Difficultyadvanced
Triggerchat
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerChat message naming a release versionSlack
  • ActionPull Sentry crash-free health and error groupsSentrySentry
  • ActionQuery Honeycomb error rate and latencyHoneycomb
  • ActionFetch GitHub commit range since last healthy releaseGitHubGitHub
  • LogicWeigh signals into hold/rollback/proceed verdict
  • OutputReply in thread with verdict, evidence, and commit linkSlack

What it does

Lets an engineer ask, in chat, whether a specific release is safe to promote. The agent gathers Sentry health, Honeycomb telemetry, and the relevant GitHub commits, then reasons across them to recommend a clear action.

When to use it

Use it when a gate fires ambiguously or someone wants a fast human-in-the-loop read before promoting manually. Best for on-call engineers who need a synthesized answer instead of opening four tabs at 2am.

How it works

  1. 1A chat message names a release version and asks for a verdict.
  2. 2The agent pulls that version's crash-free sessions rate, top error groups, and adoption from Sentry.
  3. 3It queries Honeycomb for server error rate and latency on the same version and window.
  4. 4It fetches the GitHub commit range since the last healthy release to scope suspect changes.
  5. 5The agent weighs the signals, accounting for sample size and severity, and forms a hold, roll back, or proceed recommendation.
  6. 6It replies in the chat thread with the verdict, the evidence behind it, and a link to the implicated commits.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect SentryErrors, performance, releases.
  2. 2
    Connect HoneycombDistributed traces and queries.
  3. 3
    Connect GitHubRepos, issues, pull requests, actions.
  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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