Datadog Application Performance Monitoring | Datadog
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Datadog Application Performance Monitoring

Detect, troubleshoot, and resolve issues faster with end-to-end distributed tracing and service-centric observability at scale, correlated to all telemetry types.

Product Benefits

Simplify Complexity with End-to-End Monitoring

  • Monitor all aspects of your application architecture from the user interaction to back-end storage - in a single platform
  • Easily identify bottlenecks, errors, heavy traffic issues, slow-running queries, and more with end-to-end application tracing, latency breakdowns, continuous profiling, and real user monitoring
  • Automatically collect, monitor, and visualize high-granularity data and custom metrics in real time, including availability, response times, reliability, error rates, and throughput

Resolve Application Performance Issues Faster

  • Identify critical issues quickly with real-time service maps, AI-powered synthetic monitors, and alerts on latency, exceptions, code-level errors, and more
  • View logs and traces in context with automatic trace_id injection
  • Test hypotheses in seconds by overlaying application events onto time-synchronized metric graphs
  • Eliminate inefficiencies caused by context switching with a consolidated platform for monitoring, paging, and resolving incidents

Easily Optimize Code-Level Performance

  • Detect the most resource-consuming code lines, methods, and classes in your applications in seconds with a lightweight, next-generation profiler that’s easy-to-use and always-on
  • Determine the root cause of code issues with a breakdown of time spent by method on CPU, garbage collection, lock contention, and I/O; improve CPU utilization, memory allocation, and user latency
  • Surface runtime activity and performance problems such as deadlocked threads, inefficient garbage collection, and memory leaks
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Automatically Catch Issues Before They Escalate

  • Release code safely and more efficiently with automatic deployment tracking
  • Ensure that a hotfix actually solves the problem it is trying to fix
  • Adopt canary, blue/green, shadow, or any other deployment strategies with confidence
  • Easily analyze the state of production after individual deployments over time to identify regressions and automate rollbacks

Receive Alerts Only for the Issues that Matter and Eliminate False-Positives

  • Set up recommended alerts with 1 click for anomalies and outliers that account for daily, weekly, and seasonal fluctuations
  • Proactively prevent outages and errors in the future by alerting on metric forecasts
  • Combine alerts into composite alerts for greater granularity and stronger signal to reduce the noise
  • Automatically detect unanticipated outliers, anomalies, and errors with Watchdog
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Spend Less Time Scaling and Maintaining Your Tools

  • Deploy APM in seconds on hosts, containers, serverless functions, and PaaS with effortless auto-instrumentation
  • Utilize hundreds of integrations with third-party frameworks or libraries for unparalleled visibility into Java, .NET, PHP, Node.js, Ruby, Python, Go, or C++ applications
  • Access flexible support for vendor-neutral standards such as OpenTelemetry and OpenTracing
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Live Visibility, Complete Control

  • Search and Analyze your ingested traces live over the last 15 minutes
  • Retain errors and high latency traces automatically for 15 days
  • Control cost-visibility tradeoffs with fine-grained ingestion controls and tag-based retention filters
  • Seamlessly correlate distributed traces with metrics, logs, browser sessions, code profiles, synthetics, and network performance data

Instantly Generate Application Logs, Spans, Metrics, and Span Tags without Redeploying Code

  • Expedite debugging of production issues with granular insights into application behavior and service interactions by adding log statements without changing code
  • Add spans to troubleshoot slow requests and specific operations in your application without leaving the Datadog platform
  • Create metrics on the fly that measure the time any method in your code is consuming in production, and use metric expressions to focus on specific requests
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Loved & Trusted by Thousands

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