Book Image

Getting Started with Elastic Stack 8.0

By : Asjad Athick
5 (1)
Book Image

Getting Started with Elastic Stack 8.0

5 (1)
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)
1
Section 1: Core Components
4
Section 2: Working with the Elastic Stack
12
Section 3: Building Solutions with the Elastic Stack

An introduction to observability

Monitoring systems, applications, and assets in your business has been a long-standing practice in IT teams. Teams will generally want to keep an eye on their most critical environments to know whether systems are performing to expectations. This is generally achieved by defining a collection of data points to be collected from systems to understand the state in which the system operates. Metrics can indicate when faults or errors occur; engineers then analyze code, data, and configuration to understand and fix issues.

We've discussed how modern systems are increasingly complex and dynamic, given the demanding problems they solve for customers. Modern architectures often take a highly functional approach to solving problems. For example, teams may choose a relational database to persist ACID-compliant transactions, while leveraging Elasticsearch to offer free text search capabilities on top of the same dataset. Components are also decoupled...