Book Image

Getting Started with Elastic Stack 8.0

By : Asjad Athick
Book Image

Getting Started with Elastic Stack 8.0

By: Asjad Athick

Overview of this book

The Elastic Stack helps you work with massive volumes of data to power use cases in the search, observability, and security solution areas. This three-part book starts with an introduction to the Elastic Stack with high-level commentary on the solutions the stack can be leveraged for. The second section focuses on each core component, giving you a detailed understanding of the component and the role it plays. You’ll start by working with Elasticsearch to ingest, search, analyze, and store data for your use cases. Next, you’ll look at Logstash, Beats, and Elastic Agent as components that can collect, transform, and load data. Later chapters help you use Kibana as an interface to consume Elastic solutions and interact with data on Elasticsearch. The last section explores the three main use cases offered on top of the Elastic Stack. You’ll start with a full-text search and look at real-world outcomes powered by search capabilities. Furthermore, you’ll learn how the stack can be used to monitor and observe large and complex IT environments. Finally, you’ll understand how to detect, prevent, and respond to security threats across your environment. The book ends by highlighting architecture best practices for successful Elastic Stack deployments. By the end of this book, you’ll be able to implement the Elastic Stack and derive value from it.
Table of Contents (18 chapters)
Section 1: Core Components
Section 2: Working with the Elastic Stack
Section 3: Building Solutions with the Elastic Stack

Understanding the internals of an Elasticsearch index

When users want to store data (or documents) on Elasticsearch, they do so in an index. An index on Elasticsearch is a location to store and organize related documents. They don't all have to be the same type of data, but they generally have to be related to one another. In the SQL world, an index would be comparable to a database containing multiple tables (where each table is designed for a single type of data).

An index is made up of primary shards. Primary shards can be replicated into replica shards to achieve high availability. Each shard is an instance of a Lucene index with the ability to handle indexing and search requests. The primary shard can handle both read and write requests, while replica shards are read-only. When a document is indexed into Elasticsearch, it is indexed by the primary shard before being replicated to the replica shard. The indexing request is only acknowledged once the replica shard has been...