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Elastic Stack: First Steps

A hands-on guide

Topic: Data
Madhusudhan Konda

The Elastic Stack is a full package for search, analytics, application monitoring, central logging, alerting, anomaly detection, forecasting, and more. It includes Elasticsearch—the de facto standard in the search and analytics field—as well as Kibana Logstash and Beats.

The Elastic Stack is known for its extensive rich functionality, simplistic architecture, comprehensive APIs, high availability and scalability, and blazing performance. But it also comes with a steep learning curve. The Elastic Stack is a complex beast due to various moving parts and a vast ecosystem of products and frameworks. And the official documentation is disjointed, at times barely adequate to quench the thirst of a beginner or someone looking for in-depth knowledge about the product.

Join expert Madhusudhan Konda to learn the Elastic Stack from the ground up. You’ll get hands-on as you learn how to set up the whole suite, from priming Elasticsearch with data and ETL processing with Logstash with Beats to running complex search queries against Elasticsearch and designing visual charts and graphs on Kibana. More importantly, you’ll focus on the practical side of the Elastic Stack, diving into the fundamentals and architecture, dissecting APIs, exploring real-world examples, and debating use cases—ultimately giving you a higher level of confidence in the product.

What you'll learn-and how you can apply it

By the end of this live online course, you’ll understand:

  • The fundamentals of working with the Elastic Stack
  • Tools like Auditbeat, Journalbeat, Winlogbeat, and Heartbeat
  • How to connect Logstash to accept Beats and Elasticsearch
  • The ETL processing framework in Logstash
  • How to customize pipelines
  • How to import data using bulk APIs in Kibana
  • How to create dashboards

And you’ll be able to:

  • Install, set up, and run the Elastic Stack
  • Stream logs and metrics using Filebeats and Metricbeats
  • Enrich, transform, and filter data in Logstash
  • Index and search data in Elasticsearch
  • Query and create visualizations in Kibana

This training course is for you because...

  • You’re a developer, architect, or analyst who wants to learn more about Elasticsearch and other Elastic Stack products.
  • You work with disparate systems and need to integrate the logs and metrics for automated central analysis.
  • You’re setting up a log monitoring system in your organization and want to better understand how the Elastic Stack works.
  • You’re familiar with Elasticsearch but need to expand your knowledge about Logstash, Beats, and Kibana.
  • You need to onboard sensitive data and customize the pipelines for your organization.
  • You want to become an Elasticsearch Engineer and need experience in the other suites of products.

Prerequisites

  • A basic understanding of JSON and REST
  • Familiarity with the Elastic Stack (useful but not required)

Recommended preparation:

  • Complete the course setup instructions

Recommended follow-up:

About your instructor

  • Madhusudhan Konda is a passionate technologist and a lifelong tech learner who loves distilling complex problems into simpler solutions, looking at the big picture and providing technical direction, and experimenting with newer programming languages and shiny frameworks. Over his career, Madhusudhan has held roles such as solution architect, development lead, lead developer, and others, always with a strong inclination toward teaching his fellow techies programming languages, frameworks, and new technologies. He’s been instrumental in delivering high-quality solutions to major clients such as EBRD, Credit Suisse, UBS, Mizuho, Deutsche Bank, Halifax, British Petroleum, British Airways, and Lloyd’s of London, to name a few. His core competencies lie in not only creating simple architectures for complex business problems and designing and developing the software projects from the ground up but also providing strategic road maps, cost-effective architectures, and product designs, leading teams, mentoring, and providing thought leadership. He’s written well-received books and produced video courses on Java, Spring, and the Hibernate ecosystem.

Schedule

The timeframes are only estimates and may vary according to how the class is progressing

Introduction to the Elastic Stack (15 minutes)

  • Presentation: The Elastic ecosystem; overview of the Elastic Stack—Beats, Logstash, Elasticsearch, and Kibana
  • Q&A

Installing Elasticsearch and Kibana (20 minutes)

  • Presentation and demos: Downloading and installing Elasticsearch and Kibana; configuring and running Elasticsearch and Kibana; a short tour of Kibana; CRUD sample documents
  • Q&A

Search (20 minutes)

  • Presentation: Working with search APIs; full-text versus structured data; term level and full-text queries
  • Q&A
  • Break (5 minutes)

Installing Logstash (15 minutes)

  • Presentation and demos: Introduction to Logstash; installing and running Logstash; integrating with Elasticsearch
  • Hands-on exercise: Implement a grok pattern
  • Q&A

Working with Logstash (25 minutes)

  • Presentation: Overview of inputs, filters, and outputs; working with basic components; creating inputs and filters
  • Q&A

Beats (15 minutes)

  • Presentation and demos: Understanding the Beats framework; installing and configuring Metricbeat; installing and configuring Filebeat; working with files
  • Q&A
  • Break (5 minutes)

Integrating Beats with Logstash (15 minutes)

  • Presentation and demos: Integrating Beats with Logstash; extracting metrics using Metricbeat; writing grok patterns for metrics; installing Filebeat and integrating with Logstash
  • Hands-on exercise: Implement Auditbeat-to-Logstash-to-Elasticsearch connectivity
  • Q&A

Beats, Logstash, and Elasticsearch (20 minutes)

  • Presentation: Overview; Beats, Logstash, and Elasticsearch plumbing; end-to-end integration; importing logs data; indexing the logs data in Elasticsearch
  • Q&A

Visualizing data (20 minutes)

  • Presentation and demo: Discovering data in Kibana; visualizing metrics; creating a dashboard
  • Hands-on exercise: Discover log metrics

Wrap-up and Q&A (5 minutes)