Abstract

Observability Pipelines (OP) allow you to collect, filter, and modify your logs within your own infrastructure. Use a UI to configure workers able to process massive amounts of logs. You can then store these logs yourself or send them to any log storage or observability vendor.

Learning Objectives

By the end of this course learners will be able to:

  • Explain the purpose and benefits of using Observability Pipelines (OP)
  • Configure OP in the Datadog UI
  • Install OP in a Kubernetes application
  • Route logs from the Datadog Agent to OP
  • Configure OP processors to filter and redact logs
  • Inspect results using Live Capture
  • Monitor the health of OP pipelines

Primary Audience

This course is for Observability Engineers or Security teams who own or work with the internal infrastructure that multiple teams connect to.

Prerequisites

Learners should know the following information:

  • The basics of a Datadog Agent
  • Fundamental concepts of logs, metrics, attributes, and tags
  • How to use the Learning Environment

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. Course Overview

    1. Using Observability Pipelines

    2. Lab: Using Observability Pipelines

    3. Observability Pipelines Architecture

    1. Course Conclusion

    2. Feedback Survey

Getting Started with Observability Pipelines

  • 1 hours to complete
  • 0 hours of video content
  • Beginner
Enroll for free