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Big Data Analytics Using Splunk: Deriving Operational Intelligence from Social Media, Machine Data, Existing Data Warehouses, and Other Real-Time Streaming Sources
book

Big Data Analytics Using Splunk: Deriving Operational Intelligence from Social Media, Machine Data, Existing Data Warehouses, and Other Real-Time Streaming Sources

by Peter Zadrozny, Raghu Kodali
May 2013
Beginner to intermediate content levelBeginner to intermediate
376 pages
11h 3m
English
Apress
Content preview from Big Data Analytics Using Splunk: Deriving Operational Intelligence from Social Media, Machine Data, Existing Data Warehouses, and Other Real-Time Streaming Sources

CHAPTER 16

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Scaling and High Availability

All of the examples and projects in the book so far have been based on using a single instance of Splunk, which acts as an indexer and searcher. In this chapter, we will review how to scale Splunk by adding more servers to handle the indexing and search components. You will also learn the basic principles of clustering, which increases the resiliency of Splunk by handling automatic failover of indexers. We will set up a sample cluster to illustrate the basic steps of this process.

Scaling Splunk

The functionality of Splunk can be roughly broken down into three basic areas:

  • Collecting data
  • Indexing the ...
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Publisher Resources

ISBN: 9781430257615Purchase book