Course · Training · Workshop

Elastic Stack for Observability and Log Management

Hands-on intensive course on the Elastic Stack. Learn how to efficiently manage and visualize logs, metrics, and traces with Elasticsearch, Logstash, Kibana, and Beats.

In today's IT landscape, the ability to collect, process, and analyze large amounts of logs, metrics, and traces is crucial for success. The Elastic Stack is a powerful, open-source toolset that masters these tasks. In this course, you will learn how to use the Elastic Stack to monitor systems, analyze log data, and create meaningful visualizations and dashboards. This course equips you with the tools to reliably monitor systems and quickly detect issues.

In-house course

Tailored for your team.

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Trainers

Jan-Hendrik Heuing

Instructor

Yanick Egli

Trainer & Training Platform Engineer

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Content

In this course, we dive deep into the world of the Elastic Stack and provide you with the knowledge to build a comprehensive observability solution. We cover the following topics:

– Architecture and Core Concepts:

The Importance of Observability: Logs, Metrics, and Traces
The Role of the Elastic Stack: Elasticsearch, Logstash, Kibana, and Beats
Core Data Concepts: Indices, Documents, and Clusters
Integration into modern environments like Kubernetes – Data Processing and Collection:
Log processing with Logstash pipelines
Data collection with various Beats – Analysis with Kibana Query Language (KQL):
Introduction to KQL for log analysis
Analysis of metrics with KQL – Visualization and Dashboards:
Log visualization with Kibana
Creation of interactive dashboards
Effective use of KQL in Kibana – Alerting and Notifications:
Introduction to the alerting framework
Creating alerts based on KQL queries

This course provides a hands-on introduction to the Elastic Stack, enabling you to proactively monitor your systems and identify issues faster.

The actual course content may differ from the above depending on the trainer, delivery, duration and the composition of participants.

Goal

Participants understand the architecture and components of the Elastic Stack. They can collect and process data with Beats and Logstash, analyze it with KQL, and create meaningful dashboards and targeted alerts in Kibana to implement an effective monitoring and log management solution.

Duration

2 or 3 Days

Format

Collaboratively working through an incremental sample project with brief explanations, assignments, solutions, and ongoing support from our top trainers.

Target group

Software and System Engineers, DevOps specialists, and IT administrators responsible for monitoring, log analysis, and maintaining system health, as well as anyone evaluating or introducing modern monitoring solutions.

Prerequisites

Basic understanding in the use of the command line. Basic understanding of version control with GIT. Basic knowledge of IT infrastructure is helpful but not mandatory.

Preparation

After registration, each participant receives a questionnaire with installation instructions. Based on the answers, we provide individual feedback. If required, a mini-setup via remote session can be performed before the training (included in the training). Training laptops can be provided on request, but we recommend to work with your own device to be able to continue directly afterwards.

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More about the Elastic Stack

The Elastic Stack, formerly known as the ELK Stack, is a comprehensive suite of open-source tools for searching, analyzing, and visualizing data in real-time. It consists of the core components Elasticsearch, Logstash, and Kibana, and is complemented by the Beats family for data collection.

Further resources:

History

The history of the Elastic Stack began in 2010 with the development of Elasticsearch by Shay Banon. Elasticsearch was designed as a scalable, distributed search and analytics engine. Shortly thereafter, Kibana was developed as a visualization frontend and Logstash for server-side data processing. These three products formed the original ELK Stack.

With the introduction of Beats, a family of lightweight data shippers, the stack was expanded to become the Elastic Stack. Beats enables the easy collection of data from edge machines and its forwarding to Elasticsearch or Logstash.

Today, the Elastic Stack is one of the leading platforms for observability (logs, metrics, traces), security, and enterprise search. It is used by companies worldwide to monitor complex data landscapes, detect security threats, and gain business-critical insights. Continuous development, including the integration of machine learning and AI features, secures the stack's position as a forward-looking technology.