EFK Stack

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3 Days

Available On-Site

Available Virtually

Contact Us for Open Enrollment
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Customizable

EFK Stack is an intensive, three-day, hands-on course that helps working technology professionals master Elasticsearch, fluentd, and Kibana. Attendees learn to integrate data from many sources, including application containers, using the fluentd collection and filtering engine. The course then covers aggregating and analyzing real-time data with Elasticsearch’s highly available, schema-less platform.

Students gain experience with the integrated Kibana visualization tool, and 12 hands-on labs give practical experience with each part of the stack. Attendees leave with a clear understanding of EFK and how to use it to pull high-value insights from large-scale streaming datasets in real time.

Day one opens with an architecture walkthrough before moving into installing and configuring fluentd, then spends two modules on inputs, filtering, and output formatting to prepare raw logs for indexing. Day two turns to Elasticsearch, covering installation, the query DSL, and analyzers, mappings, and indexes, before a closing module on suggesters, aggregations, and document modeling for richer search results.

Day three brings Kibana into the picture, starting with installation and configuration and moving into exploring indexes, building dashboards, and discovery. The course wraps with a capstone module that ties fluentd, Elasticsearch, and Kibana together into one working observability pipeline.

Who Should Attend

Developers, IT and QA Staff, Technical Managers and DevOps personnel

What Attendees Will Learn

Upon completing EFK Stack, attendees will be able to:

  • Explain the EFK stack architecture (Elasticsearch, Fluentd, and Kibana)
  • Install and configure Fluentd for data collection
  • Apply Fluentd inputs and filtering
  • Format and buffer Fluentd outputs
  • Install and configure Elasticsearch
  • Query data using the Elasticsearch DSL
  • Apply analyzers, mappings, and indexes
  • Apply suggestions, aggregations, and document modeling
  • Install, configure, and use Kibana for data visualization

Prerequisites

There are no formal prerequisites for this course; general computer literacy is helpful.

Delivery

Available for Instructor-Led (ILT) in-person/onsite training or Virtual Instructor-Led training (VILT) delivery.

Each attendee will require the ability to ssh into a cloud hosted virtual machine (provided with the course). In environments where SSH is not possible, local lab VMs or browser accessible lab systems can be provided. For web-based delivery, participants require an Internet-connected computer capable of teleconferencing.

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