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Implementing Splunk (Update)

Implementing Splunk (Update)

By : VINCENT BUMGARNER, James D. Miller
4.5 (4)
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Implementing Splunk (Update)

Implementing Splunk (Update)

4.5 (4)
By: VINCENT BUMGARNER, James D. Miller

Overview of this book

If you are a data analyst with basic knowledge of Big Data analysis but no knowledge of Splunk, then this book will help you get started with Splunk. The book assumes that you have access to a copy of Splunk, ideally not in production, and many examples also assume you have administrator rights.
Table of Contents (15 chapters)
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14
Index

Common data sources

Your data may come from a number of sources; these can be files, network ports, or scripts. Let's walk through a few common scenarios.

Monitoring logs on servers

In this scenario, servers write their logs to a local drive, and a forwarder process monitors these logs. This is the typical Splunk installation.

The advantages of this approach include:

  • This process is highly optimized. If the indexers are not overworked, events are usually searchable within a few seconds.
  • Slowdowns caused by network problems or indexer overload are handled gracefully. The forwarder process will pick up where it left off when the slowdown is resolved.
  • The agent is light, typically using less than 100 megabytes of RAM and a few percent of one CPU. These values go up with the amount of new data written and the number of files being tracked. See inputs.conf in Chapter 11, Configuring Splunk, for details.
  • Logs without a time zone specified will inherit the time zone of the machine running the forwarder...
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