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Getting Started with Elastic Stack 8.0

You're reading from  Getting Started with Elastic Stack 8.0

Product type Book
Published in Mar 2022
Publisher Packt
ISBN-13 9781800569492
Pages 474 pages
Edition 1st Edition
Languages
Author (1):
Asjad Athick Asjad Athick
Profile icon Asjad Athick

Table of Contents (18) Chapters

Preface Section 1: Core Components
Chapter 1: Introduction to the Elastic Stack Chapter 2: Installing and Running the Elastic Stack Section 2: Working with the Elastic Stack
Chapter 3: Indexing and Searching for Data Chapter 4: Leveraging Insights and Managing Data on Elasticsearch Chapter 5: Running Machine Learning Jobs on Elasticsearch Chapter 6: Collecting and Shipping Data with Beats Chapter 7: Using Logstash to Extract, Transform, and Load Data Chapter 8: Interacting with Your Data on Kibana Chapter 9: Managing Data Onboarding with Elastic Agent Section 3: Building Solutions with the Elastic Stack
Chapter 10: Building Search Experiences Using the Elastic Stack Chapter 11: Observing Applications and Infrastructure Using the Elastic Stack Chapter 12: Security Threat Detection and Response Using the Elastic Stack Chapter 13: Architecting Workloads on the Elastic Stack Other Books You May Enjoy

Architectures to handle complex requirements

Elastic Stack is designed to be extremely flexible in how it can be deployed and used to solve your big data use cases. This section will explore specialized architecture patterns that can be used to handle more complex architectural requirements for your solution.

Elasticsearch (and other stack components) can be configured to be highly available and fault-tolerant in a single geographical region when following standard architecture best practices. Given the sensitive latency and bandwidth requirements for inter-node communication within an Elasticsearch cluster, it is generally not possible to deploy a cluster that spans multiple geographical regions. This presents two main challenges:

  • Standard architecture clusters are not resilient to complete failures within a geographical region.
  • Users and data in other geographies will experience high latencies, pay more in terms of data transfer costs, and have reduced bandwidth for...
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