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Getting Started with Elastic Stack 8.0

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

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Product type Paperback
Published in Mar 2022
Publisher Packt
ISBN-13 9781800569492
Length 474 pages
Edition 1st Edition
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Author (1):
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Asjad Athick Asjad Athick
Author Profile Icon Asjad Athick
Asjad Athick
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Table of Contents (18) Chapters Close

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

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...
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