Abstract

Logs from different sources in your infrastructure and applications have different attribute naming conventions, structures, and formats. As part of Datadog Log Management, you can use Log Pipelines, Processors, and Standard Attributes to extract key attributes and enrich log details so that all your logs from all sources have a standard attribute naming convention, structure and format. You can also use the Pipeline Scanner to help you manage log processing. In this hands-on course, you'll a build custom pipeline and add a standard attribute to structure and enrich logs from an application service.

Learning Objectives

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

  • Create and modify a log pipeline from scratch
  • Manage log pipelines and processing using the Pipeline Scanner
  • Add Standard Attributes to normalize related attribute names across processed logs

Primary Audience

Developers and Datadog users who will be building and managing log pipelines and settings for Log Management in Datadog.

Prerequisites

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. Processing Logs from Different Sources

    1. Grok Parsing

    2. Pipeline Scanner

    3. Standard Attributes

    1. Lab: Build and Manage a Log Pipeline

    1. Summary

    2. Feedback Survey

Build and Manage Log Pipelines

  • 2 hours to complete
  • 6 Lessons
  • Intermediate
Enroll for free