How to create datadog monitor in Datadog

Create Datadog Monitor in Datadog — start free

Inputs

The fields this action accepts.

Every field can be mapped from an upstream trigger, AI step, table row, or hard-coded literal.

Field	Type	Required	Description
Monitor Name name	string	Required	Monitor Name. Example: High Error Rate
Type type	options	Required	Type. Options: Metric Alert, Service Check, Log Alert, Query Alert
Query query	string	Required	Datadog monitor query
Alert Message message	string	Optional	Message sent when monitor triggers. Supports @mentions.
Tags tags	string	Optional	Comma-separated tags

Sample request

{
  "name": "e.g. High Error Rate",
  "type": "{{trigger.type}}",
  "query": "e.g. avg(last_5m):avg:system.cpu.user{*} > 90",
  "message": "e.g. CPU usage is above 90%! @ops-team",
  "tags": "e.g. env:production, team:backend"
}

Returns

{
  "id": 123,
  "name": "High Error Rate",
  "type": "metric alert",
  "overall_state": "No Data"
}

Use these fields in downstream nodes for routing, logging, or error handling.

FAQ

Questions about Create Datadog Monitor.

What does the Create Datadog Monitor action do in Datadog?

Programmatically defines an alerting monitor with query, thresholds, and notification list. Useful for infrastructure-as-workflow patterns where new services auto-provision their monitoring.

What inputs does Create Datadog Monitor require?

Required: Monitor Name, Type, Query. Every input accepts a static value or a variable from any upstream node in your workflow.

Can I use dynamic inputs from earlier workflow nodes?

Yes. Any field on this action can pull values from upstream nodes, whether that's a form response, a trigger payload, an AI output, or a lookup result.

What happens if Datadog returns an error?

The workflow pauses on the failed node, the error message is captured in the run log, and you can retry the run with one click. Auto-retry policies are configurable per workflow with exponential backoff up to 5 attempts.

Does Create Datadog Monitor support batch operations?

Yes. Run Create Datadog Monitor inside a Loop node to process arrays. TinyCommand handles Datadog's rate limits automatically so you don't have to throttle manually.

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