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Datadog Application Performance Monitoring
Monitor & optimize your stack at any scale
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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.
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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.
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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.
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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.
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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.