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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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Using hybrid search to build advanced search applications

In the previous recipes, we learned the fundamentals of dense vector search and sparse vector search. In this recipe, we will explore how to build advanced search applications enhanced by nuanced ranking, where traditional keyword search is augmented with semantic context. Hybrid search leverages the benefits of both lexical and vector search, enabling a Search Application to match exact keywords while also understanding the broader context or meaning of a query. It also serves as the foundation for RAG applications, which we will learn about later in this chapter.

Getting ready

Make sure that you have gone through the first two recipes in this chapter:

  • Implementing semantic search with dense vectors
  • Implementing semantic search with sparse vectors

Make sure that the React Search Application vector-search-application is up and running. We will reuse the concept of the search template to test the behavior...

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