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

Getting insights from data using aggregations

When looking to understand insights in your data, retrieving documents that fit the question you're looking to answer is just the first part of the problem. For example, if an analyst is looking to understand how much traffic their web servers served in a given day, running a query to retrieve logs in the given period may still return millions of events.

Aggregations allow you to summarize large volumes of data into something easier to consume. Elasticsearch can perform two primary types of aggregations:

  • Metric aggregations can calculate metrics such as count, sum, min, max, and average on numeric data.
  • Bucket aggregations can be used to organize large datasets into groups, depending on the value of a field. Buckets can be created based on a range, date, the frequency of a term in the search results (or corpus), and so on.

An exhaustive list of all supported aggregations can be found in the Elasticsearch guide...