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Getting Started with Elastic Stack 8.0

Getting Started with Elastic Stack 8.0

By : Asjad Athick
4.3 (9)
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Getting Started with Elastic Stack 8.0

Getting Started with Elastic Stack 8.0

4.3 (9)
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)
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1
Section 1: Core Components
4
Section 2: Working with the Elastic Stack
12
Section 3: Building Solutions with the Elastic Stack

Introduction to Logstash

In Chapter 6, Collecting and Shipping Data with Beats, we explored how a key characteristic of modern IT environments is the concept of valuable data being generated in multiple parts of the technology stack. While Beats go a long way in collecting this data to send to Elasticsearch, a key challenge is transforming data to make it useful for search and analysis.

Logstash is a flexible Extract, Transform, Load (ETL) tool designed to solve this problem. While Logstash has no real dependency on Elasticsearch and Beats and can be used for any generic ETL use case, it plays a key role as part of the Elastic Stack.

Logstash is generally used in two main ways as part of the Elastic Stack:

  • As an aggregation point for data prior to ingestion (push model):

Logstash can act as the receiver for data from sources such as Beats agents or Syslog streams. It can also listen for data over HTTP for any compatible source system to send events through.

...

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