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

Tackling the challenges in onboarding new data sources

Elastic Stack makes it possible to leverage value and insight from large amounts of data, collected from multiple points in your technology stack. The benefit of collecting from multiple layers in your stack is the ability to then stitch events together and correlate activity across the different components during analysis.

However, it is not a trivial task to identify, ingest, and parse all the available and usable data sources, especially in large and complex environments. Some common challenges include the following:

  • Getting access to data sources, especially if the system in question is managed by a different team
  • Extracting, parsing, and making sense of data sources effectively so that the logs that are collected are useful during analysis
  • Investing in the development of custom instrumentation or collection modules for bespoke sources
  • Managing and dealing with large data volumes (and the associated costs...