Datadog AWS APM

AWS Application Performance Monitoring

Detect, diagnose, and resolve code-level performance issues faster with real-time service maps, synthetic monitors, end-to-end tracing, continuous profiling, and centralized logging all within one platform.

Why Datadog?

End-to-End Distributed Tracing

Set up in minutes, and instantly visualize your traces with full control over ingestion, retention, and costs

Code Hotspots And Thread Level Insights

Optimize the most resource consuming lines of production code with our low-overhead Continuous Profiler

Automatic Deployment Tracking

Requests, errors, and latency metrics for every code deploy including out-of-the-box code version comparisons

Superior Granularity & Retention

0-second OOTB high resolution, 1-second availability for critical metrics, 15-month retention, and no roll-up, ever

Product Benefits

Simplify Complexity with End-to-End Visibility

Monitor all aspects of your microservices 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

Monitor Your Containerized Environment More Effectively

Automatically collect, monitor, and visualize high-granularity metrics from all your containers at 15s. granularity for 15 months
Analyze the health of all your containers by pod, namespace, and node distributed across any cloud environment
Gain visibility into container orchestration and easily manage Kubernetes pods over or under-allocating available resources via the real-time live container view and auto-generated container map
Optimize horizontal auto-scaling by connecting Datadog to your HPA and collecting request rate, latency, and available network bandwidth

Start Monitoring Proactively and Ensure Optimal Performance

Proactively prevent outages and errors by alerting on metric forecasts or specific data point thresholds
Set up alerts for anomalies and outliers that account for daily, weekly, and seasonal fluctuations
Automatically detect unanticipated outliers, anomalies, and errors with Watchdog
Track all key service-level indicator metrics in real time, including availability, response times, reliability, error rates, and throughput

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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