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CHATBOTS

Status Concierge HTTP API for Embedded Widgets

Exposes a webhook endpoint that takes a service name and returns a structured JSON health verdict from live Datadog monitors.

CategoryChatbots
Enginesim
Difficultyintermediate
Triggerwebhook
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerInbound HTTP request with service nameHTTP webhook
  • LogicValidate input, map name to monitor query
  • ActionQuery Datadog monitor statesDatadogDatadog
  • LogicRoll up status + assemble monitor list
  • OutputReturn structured JSON verdictHTTP webhook

What it does

Provides a deterministic HTTP endpoint: POST a service name, get back JSON with an overall status, the contributing monitors, and a human-readable one-liner. It turns the chat concierge logic into an API any frontend can call.

When to use it

When you want the same "is X degraded" answer surfaced outside chat — inside your product's help widget, an internal status page, or a support tool's sidebar. Build the UI once and let this endpoint feed it live Datadog truth.

How it works

  1. 1An inbound HTTP webhook receives a JSON body with the requested service name.
  2. 2A logic step validates the input and maps the name to a Datadog monitor query (tag or name filter).
  3. 3The flow calls the Datadog Monitors API for matching monitor states.
  4. 4A logic step computes the rollup status (`ok` / `degraded` / `down` / `unknown`) and assembles the contributing monitor list.
  5. 5The endpoint returns a structured JSON payload with status, monitors, and a display string for the caller to render.

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
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  4. 4
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  5. 5
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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