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

The value of running machine learning on Elasticsearch

Elasticsearch is a powerful tool when it comes to storing, searching, and aggregating large volumes of data. Dashboards and visualizations help with user-driven interrogation and exploration of data, while tools such as Watcher and Kibana alerting allow users to take automatic action when data changes in a predefined or expected manner.

However, a lot of data sources can often represent trends or insights that are hard to capture as a predefined rule or query. Consider the following example:

  • A logging platform collects application logs (using an agent) from about 5,000 endpoints across an environment.
  • The application generates a log line for every transaction executed as soon as the transaction completes.
  • After a software patch, a small subset of the endpoints can intermittently and temporarily fail to write logs successfully. The machine doesn't entirely fail as the failure is intermittent in nature.
  • ...