The Timeline view in Datadog Continuous Profiler visualizes how thread and runtime activities related to resource consumption are distributed across threads and the entire runtime. With these insights, you can more quickly investigate root causes of high request latency buried within your code. In this hands-on course, you’ll use the Timeline view along with the Flame Graph view in Continuous Profiler to pinpoint causes of high service latencies in an app service that is built in Java. If you don’t usually work with Java, you’ll still be able to follow along.

Example of a call stack for a Parked thread activity.

Learning Objectives

By the end of this course, you'll be able to do the following:

  1. Interpret the Timeline view in Code Hotspots and Continuous Profiler to understand thread activity, runtime activity, and related code inefficiencies
  2. Investigate the cause of high request latencies using the Timeline view along with the Flame Graph view in Continuous Profiler

Primary Audience

Developers using Continuous Profiler to investigate and improve application performance


Technical Requirements

In order to complete the course, you will need:

  • Google Chrome or Firefox
  • Third-party cookies must be enabled to access labs

Course Navigation

At the bottom of each lesson, click MARK LESSON COMPLETE AND CONTINUE button so that you are marked complete for each lesson and can receive the certificate at the end of the course.

Course Enrollment Period

Please note that your enrollment in this course ends after 30 days. You can re-enroll at any time and pick up where you left off.

Course curriculum

    1. What is Profiling Timeline?

    1. Profiling Timeline complements Flame Graph

    2. Lab: Investigate Thread Activity and Runtime Activity using Profiling Timeline

    1. Summary

    2. Feedback Survey

Optimize Request Latency with Profiling Timeline

  • 1 hours to complete
  • Advanced