Cloud Native Logging with Fluentd and Fluent Bit (LFS242)

This course introduces the Fluentd and Fluent Bit log forwarding and aggregation tool for use in cloud native logging. Both tools provide fast and efficient log transformation and enrichment, as well as aggregation and forwarding. These capabilities enable both Fluentd and Fluent Bit to realize the concept of a “unified logging layer”, that helps users consume log data collected from all parts of a large scale, distributed system

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Target group

This course is designed for individuals with a technical background including sysadmins and developers who need to utilize cloud native logging tools.

Target group

Course structure

  • Chapter 1. Course Introduction
  • Chapter 2. Fluent Ecosystem and Unified Logging
  • Chapter 3. Log Input and Output
  • Chapter 4. Filtering Data and Creating Pipelines
  • Chapter 5. Parsing and Formatting Data
  • Chapter 6. Multi-instance Deployments with the Fluent Ecosystem
  • Chapter 7. Monitoring the Unified Logging Layer
  • Chapter 8. Optimizing and Debugging Fluent Ecosystem Configurations
  • Chapter 9. Securing Fluent Ecosystem Deployments
  • Chapter 10. Debugging, Tuning, and Securing Fluentd Configurations
  • Chapter 11. Introduction to Fluent Bit

Benefots

In this course, you will explore the full range of Fluentd and Fluent Bit operations and features, from installing the tools as native processes to running Fluentd and Fluent Bit in container. The course also examines using Fluentd and Fluent Bit as simple log forwarders, as well as using the tools as sophisticated log aggregators and processors. Upon completion, you will have the skills necessary to deploy the Fluent tools in a wide range of production settings.

Upon completion of this course, you will have the skills necessary to deploy Fluentd and Fluent Bit in a wide range of production settings.

To best benefit from this course you should have:

  • Some familiarity with logging and log management is helpful
  • Familiarity with Linux system administration
  • Labs require a minimal Ubuntu 20.04 system with Docker installed.
Benefots

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