The Best Datadog Integrations and Apps in 2026
Datadog is a monitoring and observability platform that pulls metrics, traces, and logs from your entire stack into one place — but it only earns its keep when it’s wired to the infrastructure, incident tools, and communication channels your team actually uses. As of 2026, Datadog ships more than 1,000 built-in integrations, adding over 110 new technology partners in the last year alone across cloud, AI, security, and hybrid infrastructure.
Here are the Datadog integrations actually worth setting up, grouped by what they do — and then the way to connect Datadog to anything with an API.
Cloud platforms: AWS, Azure, Google Cloud
- Amazon Web Services — Pulls CloudWatch metrics, logs, and events across hundreds of AWS services (EC2, RDS, Lambda, S3, ELB) into Datadog dashboards.
- Microsoft Azure — Native Azure integration streams metrics and logs from VMs, App Service, AKS, and more; also available through Azure’s native partner setup.
- Google Cloud Platform — Monitors Compute Engine, GKE, Cloud SQL, BigQuery, and other GCP services alongside your other clouds.
Containers and orchestration: Kubernetes, Docker
- Kubernetes — Real-time visibility into pods, nodes, deployments, and control-plane health, with the Datadog Agent running as a DaemonSet.
- Docker — Tracks container performance, resource usage, and lifecycle events across your hosts.
- Helm / Amazon EKS / GKE / AKS — Deploy and monitor the Agent across managed Kubernetes flavors with maintained charts.
Incident and on-call: PagerDuty, Opsgenie, ServiceNow
- PagerDuty — Routes Datadog monitor alerts to on-call schedules and syncs incident state both ways.
- Opsgenie — Sends alerts to Opsgenie escalation policies so the right responder gets paged.
- ServiceNow — Opens and updates ServiceNow tickets automatically from monitor alerts and events.
Communication: Slack, Microsoft Teams
- Slack — Delivers alert notifications to channels, and lets you declare, collaborate on, and resolve Datadog incidents without leaving Slack.
- Microsoft Teams — Posts monitor notifications and incident updates to Teams channels for the same close-the-loop workflow.
Source control and CI/CD: GitHub, GitLab
- GitHub — Links code changes and deployments to performance data, and inline source snippets to stack traces in errors.
- GitLab — Tracks pipelines, deployments, and source across GitLab-hosted projects.
- Jenkins / CircleCI / GitHub Actions — CI Visibility connects pipeline runs and test results to your observability data.
Databases and data stores: PostgreSQL, MySQL, MongoDB, Redis
- PostgreSQL / MySQL — Database monitoring with query metrics, slow-query analysis, and host-level health.
- MongoDB / Redis / Elasticsearch — Tracks throughput, latency, replication, and cache performance for your data layer.
No-code automation: Zapier and Make
- Zapier and Make — Connect Datadog to thousands of apps for basic field-mapping — push an alert into a spreadsheet row or a webhook. They’re good for simple one-to-one triggers, but they don’t reason over the alert or decide what to do next; every branch is a rule you build by hand.
The AI way to connect Datadog to anything: Carly
Carly is an AI executive assistant that connects to 200+ tools — Datadog included — and lets you bring your own API key to connect to anything else with a REST API. Instead of static rules, Carly reads the alert, understands what’s happening, and runs the next step on its own — the on-call teammate that never sleeps.
- Acts on triggers 24/7 in the cloud — when a monitor fires, Carly picks it up without you watching a dashboard.
- Reasons over your data instead of just copying a field — it reads the alert context, checks severity, and decides whether to escalate, mute, or notify.
- Ties Datadog to the rest of your stack, including Gmail/Outlook, your calendar, Slack, and your CRM, so an alert becomes a routed message, a ticket, or a scheduled follow-up.
- Builds the workflow from a plain-English description — tell it “if the checkout latency monitor goes critical, page the on-call engineer and post a summary in #incidents,” and it wires it up.
Carly’s AI agents start at $35/month, with non-AI workflow steps running free.
Carly also integrates with Datadog.
How to connect Datadog to a tool with no native integration
- In Datadog, go to Organization Settings → API Keys to create an API key, then Application Keys to create an application key — Datadog requires both for API access (the API key identifies your org, the application key scopes user-level reads).
- Paste both keys into Carly on the integrations page.
- Describe the workflow in plain English — “when the payments API monitor alerts, summarize the affected services and message the on-call channel” — and Carly builds it, no code required.
Frequently Asked Questions
Does Datadog have integrations?
Yes. Datadog offers more than 1,000 built-in integrations spanning cloud providers, containers, databases, incident management, communication tools, and CI/CD — one of the largest integration catalogs in the observability space.
What is the best Datadog integration for automation?
For simple notifications, PagerDuty and Slack cover most on-call routing. For automation that actually acts on alerts — deciding what to do, escalating, and updating other systems — an AI layer like Carly reasons over the alert instead of firing a fixed rule.
How do I connect Datadog to an app that isn’t listed?
Create an API key and an application key in Datadog’s Organization Settings, paste both into Carly on the integrations page, and describe the workflow you want. Carly uses Datadog’s REST API to connect it to any tool, even one without a native integration.
How much does an AI automation for Datadog cost?
Carly’s AI agents start at $35/month, and steps in a workflow that don’t use AI run free. Datadog’s own integrations are included with your Datadog plan.
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