You're reading from Getting Started with Elastic Stack 8.0 Run powerful and scalable data platforms to search, observe, and secure your organization

Product type Paperback

Published in Mar 2022

Publisher Packt

ISBN-13 9781800569492

Length 474 pages

Edition 1st Edition

Tools

Elasticsearch

Concepts

Enterprise Search

Author (1):

Asjad Athick

View More author details

Table of Contents (18) Chapters

Preface

1. Section 1: Core Components

2. Chapter 1: Introduction to the Elastic Stack FREE CHAPTER

3. Chapter 2: Installing and Running the Elastic Stack

4. Section 2: Working with the Elastic Stack

5. Chapter 3: Indexing and Searching for Data

6. Chapter 4: Leveraging Insights and Managing Data on Elasticsearch

7. Chapter 5: Running Machine Learning Jobs on Elasticsearch

8. Chapter 6: Collecting and Shipping Data with Beats

9. Chapter 7: Using Logstash to Extract, Transform, and Load Data

10. Chapter 8: Interacting with Your Data on Kibana

11. Chapter 9: Managing Data Onboarding with Elastic Agent

12. Section 3: Building Solutions with the Elastic Stack

13. Chapter 10: Building Search Experiences Using the Elastic Stack

14. Chapter 11: Observing Applications and Infrastructure Using the Elastic Stack

15. Chapter 12: Security Threat Detection and Response Using the Elastic Stack

16. Chapter 13: Architecting Workloads on the Elastic Stack

17. Other Books You May Enjoy

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.