Monitoring API Key

Datadog REST API

Cloud monitoring and observability platform API

Datadog provides comprehensive monitoring and analytics for cloud-scale applications, infrastructure, and logs. The REST API enables developers to programmatically submit metrics, query monitoring data, manage dashboards and alerts, and integrate Datadog's observability features into their applications and workflows. It's essential for DevOps automation, custom integrations, and building monitoring solutions at scale.

Base URL https://api.datadoghq.com/api/v1

API Endpoints

Method	Endpoint	Description
POST	`/series`	Submit time series data points to Datadog for custom metrics monitoring
POST	`/check_run`	Submit service check status updates for monitoring service health
POST	`/events`	Create events to track deployments, alerts, or application changes
GET	`/query`	Query time series data using Datadog's metric query language
GET	`/dashboard`	List all dashboards in your Datadog account
POST	`/dashboard`	Create a new dashboard with custom widgets and visualizations
GET	`/monitor`	Retrieve all monitors configured in your account
POST	`/monitor`	Create a new monitor with alerting rules and notification channels
PUT	`/monitor/{monitor_id}/mute`	Mute or unmute a specific monitor to suppress alerts temporarily
GET	`/logs-queries/list`	Execute log queries and retrieve matching log events
GET	`/hosts`	List all hosts reporting to Datadog with their metadata and tags
GET	`/tags/hosts`	Get all tags associated with hosts for filtering and organization
POST	`/downtime`	Schedule maintenance downtime windows to suppress alerts
GET	`/usage/timeseries`	Retrieve usage metrics for cost tracking and capacity planning
POST	`/integration/webhooks`	Configure webhook integrations for alert notifications

Code Examples

curl -X POST "https://api.datadoghq.com/api/v1/series" \
  -H "Content-Type: application/json" \
  -H "DD-API-KEY: ${DD_API_KEY}" \
  -d '{
    "series": [{
      "metric": "custom.api.requests",
      "points": [[1234567890, 42.5]],
      "type": "count",
      "tags": ["env:production", "service:api"]
    }]
  }'

const response = await fetch('https://api.datadoghq.com/api/v1/series', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'DD-API-KEY': process.env.DD_API_KEY
  },
  body: JSON.stringify({
    series: [{
      metric: 'custom.api.requests',
      points: [[Math.floor(Date.now() / 1000), 42.5]],
      type: 'count',
      tags: ['env:production', 'service:api']
    }]
  })
});
const data = await response.json();
console.log(data);

import requests
import time

url = 'https://api.datadoghq.com/api/v1/series'
headers = {
    'Content-Type': 'application/json',
    'DD-API-KEY': 'your_api_key_here'
}
data = {
    'series': [{
        'metric': 'custom.api.requests',
        'points': [[int(time.time()), 42.5]],
        'type': 'count',
        'tags': ['env:production', 'service:api']
    }]
}
response = requests.post(url, json=data, headers=headers)
print(response.json())

Connect Datadog to AI

Deploy a Datadog MCP server on IOX Cloud and connect it to Claude, ChatGPT, Cursor, or any AI client. Your AI assistant gets direct access to Datadog through these tools:

submit_metrics Submit custom metrics and performance data to Datadog for monitoring application health and business KPIs

query_metrics Query and analyze time series metrics data to answer questions about system performance, trends, and anomalies

manage_monitors Create, update, or retrieve monitoring alerts and their current status to automate incident response

search_logs Search and filter log data to troubleshoot issues, investigate incidents, or extract insights from application logs

create_dashboard Programmatically create and update dashboards to visualize metrics and provide custom monitoring views

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Datadog REST API

API Endpoints

Code Examples

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