Datadog Application Performance Monitoring

Monitor & optimize your stack at any scale

Pinpoint the source of issues with code-level distributed tracing

- Identify root causes quickly by correlating traces with logs, infrastructure metrics, database queries, network calls, and frontend telemetry—all in one view.
- Improve code performance with visibility into the execution time and resource consumption of every method and code line.
- Resolve active incidents faster and analyze their impact on upstream and downstream services and databases with trace queries.
- Track and alert on business-specific KPIs by creating dashboards, monitors, and SLOs from span-based metrics using any tag.

Improve service performance with all telemetry in context

- Detect the source of service issues rapidly with a centralized view of health metrics and dependencies alongside telemetry from your infrastructure and databases.
- Proactively improve application reliability by setting up SLOs, monitors, and synthetic tests via the Datadog UI, Terraform provider, and APIs.
- Remediate incidents efficiently with quick access to service owners, on-call engineers, runbooks, and more in Service Catalog.
- Secure your cloud applications by identifying threats and code vulnerabilities that are live in production so you can mitigate them before they become breaches.

Track every deployment automatically and ship with confidence

- Adopt canary, blue-green, or any other deployment strategy by tracking performance changes before, during, and after the release.
- Quickly determine if a release is causing high error rates or latency by automatically aggregating health metrics by code version.
- Resolve performance degradations by comparing the impact of recent versions on infrastructure and code performance.
- Prioritize new and ongoing issues with Error Tracking, which automatically groups errors into a manageable set of issues.

Resolve incidents faster with Watchdog AI

- Improve MTTR with automated root cause analysis and minimize the impact on affected services, users, and views.
- Reduce MTTD with automatic and customizable ML-based alerts to detect anomalies and outliers and predict future changes in performance metrics.
- Accelerate investigations with error and latency outliers, which are surfaced at query time to help you find the signal in the noise.
- Minimize downtime and negative impact on end users with automatic faulty deployment detection.

Reduce security risk with open source vulnerability detection in production

- Surface vulnerable open-source libraries loaded in production as you monitor the overall health of your services.
- Prioritize vulnerabilities with the Datadog Severity Score, which factors in vulnerability exposure, CVSS, and live threat activity.
- Avoid discrepancies between pre-production and production code by ensuring remediated vulnerabilities make it to production.