Continuous Profiler

We run Datadog Continuous Profiler on every service in our testing and production environment, which gives us the insight we need to reduce the time it takes to diagnose issues and fix performance bottlenecks.

Ian Schell

Site Reliability Architect at Cvent

Datadog Continuous Profiler gives us unparalleled visibility into resource allocations in production with low overhead, and has become a crucial tool for optimizing CPU and memory performance at Faire.

Raymond Barkhouse

Staff Developer - Platform at Faire

Datadog Continuous Profiler analyzes code performance all the time and in any environment, including production, with negligible overhead. Quickly identify and optimize the most resource-consuming parts in your application code in order to improve MTTR, enhance user experience, and reduce cloud provider costs.

Pinpoint hard to replicate code issues that are invisible to other tools

Continuously profile each line of code in any environment without affecting application performance and user experience
Identify methods that are inefficient under production load, despite having performed well in pre-production environments
Reduce end-user latency and infrastructure costs by resolving code-level bottlenecks

Method-level visibility into every request

Tie every distributed trace to the methods and threads that executed the request
Understand why requests took longer to execute and which ones consumed the most CPU and memory
Determine the root cause of code issues with a breakdown of time spent by method on CPU, garbage collection, lock contention, and I/O

Tie every distributed request to the underlying code profiling data to seamlessly pinpoint the root cause of high latency

Automated code profiling insights, leveraging years of runtime expertise

Derive actionable insights from an automatic heuristic analysis of the main problem areas in your code
Surface runtime performance problems such as deadlocked threads, inefficient garbage collection, and memory leaks
Apply suggested fixes to improve application efficiency, empowering new engineers to operate like seasoned veterans

Leverage an automated analysis of your code to derive actionable insights on deadlocked threads, memory leaks, and more

Track every deploy and eliminate performance regressions

Monitor code performance variations in production by applying long-term, code-level metrics to alerts and dashboards
Compare code behavior and impact across hosts, services, and versions during canary, blue/green, or shadow deploys
Isolate the most resource-heavy functions to quickly understand what is causing a spike and decide whether to roll back or ship a fix