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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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Setting up an index lifecycle policy

Throughout the course of this book, we have seen how to ingest various types of data into the Elastic Stack and utilize it for diverse use cases such as observability, business analytics, and search. In real-world scenarios, a common question that arises is, “How do I manage the lifecycle and retention of my data? More importantly, how can I do so efficiently to optimize and reduce hardware costs while still fully leveraging the data?” This is where Index Lifecycle Management (ILM) comes into play. ILM is an extremely useful feature that streamlines the orchestration of your data within an Elasticsearch cluster.

In this recipe, we will put this concept into practice by defining an ILM policy for our Logs data stream. You will learn how to configure a policy and along the way, gaining insight into key aspects such as rollover, ILM phases, and much more.

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