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Elastic Stack 8.x Cookbook

Elastic Stack 8.x Cookbook

By : Huage Chen, Yazid Akadiri
5 (3)
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Elastic Stack 8.x Cookbook

Elastic Stack 8.x Cookbook

5 (3)
By: Huage Chen, Yazid Akadiri

Overview of this book

Learn how to make the most of the Elastic Stack (ELK Stack) products—including Elasticsearch, Kibana, Elastic Agent, and Logstash—to take data reliably and securely from any source, in any format, and then search, analyze, and visualize it in real-time. This cookbook takes a practical approach to unlocking the full potential of Elastic Stack through detailed recipes step by step. Starting with installing and ingesting data using Elastic Agent and Beats, this book guides you through data transformation and enrichment with various Elastic components and explores the latest advancements in search applications, including semantic search and Generative AI. You'll then visualize and explore your data and create dashboards using Kibana. As you progress, you'll advance your skills with machine learning for data science, get to grips with natural language processing, and discover the power of vector search. The book covers Elastic Observability use cases for log, infrastructure, and synthetics monitoring, along with essential strategies for securing the Elastic Stack. Finally, you'll gain expertise in Elastic Stack operations to effectively monitor and manage your system.
Table of Contents (16 chapters)
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Creating and setting up data tiering

A data tier consists of several Elasticsearch nodes that have the same data role and usually run on similar hardware. Often, different hardware is configured for each tier; for example, the hot tier might use the most powerful and expensive hardware, while the cold or frozen tiers could utilize less expensive, storage-oriented hardware. Using data tiers is an efficient strategy for reducing hardware requirements in an Elasticsearch cluster while maintaining access to data and the ability to search through it. To illustrate, a single frozen node can keep up to 100 TB of data compared to 2 TB of data for a hot node.

However, there is a caveat: as data moves to colder tiers, query performance can decrease. This is expected since the data is less frequently queried.

Figure 1.16 – Elasticsearch data tiering

Figure 1.16 – Elasticsearch data tiering

As we can see in Figure 1.16, there are four data tiers provided by Elasticsearch:

  • Hot tier: This...

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