CHATBOTS
"Is X degraded?" Status Concierge for Slack
Answers natural-language health questions in Slack by mapping the named service to its Datadog monitors and replying with live status, the worst alert, and a link to the monitor.
How it runs
The automated pipeline, trigger to output.
- TriggerSlack slash command / mention asks about a serviceSlack
- ActionResolve free-text name to Datadog monitor tagsOpenAI
- ActionQuery Datadog monitor states for matchesDatadog
- LogicPick worst state, decide verdict
- OutputReply in-thread with verdict + monitor linkSlack
What it does
Lets anyone in Slack ask "is checkout degraded right now?" or "how's the payments API?" and get an instant, accurate answer drawn from live Datadog monitor states instead of guesswork or a manual dashboard hunt.
When to use it
During incidents and day-to-day, when teammates flood your on-call or platform channel asking whether a service is healthy. It replaces the reflexive "let me check the dashboard" with a self-serve answer, cutting interruptions for the on-call engineer.
How it works
- 1A Slack slash command or mention fires with the service name the user asked about.
- 2The agent resolves the free-text service name to a Datadog monitor tag or name (e.g. "checkout" to `service:checkout`).
- 3It queries the Datadog Monitors API for all matching monitors and their current states.
- 4A logic step picks the worst state (Alert > Warn > No Data > OK) and decides the verdict.
- 5The reply posts back in-thread: a plain verdict ("Yes, checkout is degraded"), the triggering monitor name, when it last transitioned, and a deep link to Datadog.
Set it up
What you configure once, before turning it on.
- 1Connect SlackChannels, DMs, threads, mentions.
- 2Connect DatadogMetrics, traces, log search.
- 3Connect OpenAIModels, embeddings, files.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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