CHATBOTS

Auto-Context Reply on Every Datadog Alert

When a Datadog monitor fires, this workflow automatically posts a context-rich reply in the alert's Slack thread with the metric graph, the owning team, and the last three deploys.

CategoryChatbots
Enginesim
Difficultyintermediate
Triggerwebhook
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDatadog alert webhook receivedHTTP webhook
  • ActionFetch metric snapshot and owning team tagDatadogDatadog
  • ActionGet last three deploys to the serviceGitHubGitHub
  • LogicClassify alert as deploy-adjacent or environmental
  • OutputReply in the alert's Slack thread with contextSlack

What it does

Every time Datadog sends an alert to Slack, this workflow enriches it in place. It reads the incoming alert webhook, gathers the supporting evidence, and replies in the same thread so responders see the full picture without asking. It turns a bare alert into a briefing.

When to use it

Use it on noisy or critical channels where responders waste the first two minutes gathering basics. Best for teams that route Datadog alerts to Slack and want proactive context attached to every fire.

How it works

A Datadog alert webhook triggers the flow. The workflow parses the monitor ID and breach time, then calls Datadog for the metric snapshot image and the owning team tag. It queries GitHub for the last three deploys to the affected service. A logic step decides whether the alert is deploy-adjacent (a deploy within 30 minutes) or environmental. It then posts a formatted reply into the existing Slack alert thread with the graph, owner, deploy list, and a one-line hypothesis.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect DatadogMetrics, traces, log search.
  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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