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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

Splunk instance types

In a distributed deployment, different Splunk processes will serve different purposes. There are four stages of processing that are generally spread across two to four layers. The stages of processing include:

  • input: This stage consumes raw data from log files, ports, or scripts.
  • parsing: This stage splits the raw data into events, parses time, sets base metadata, runs transforms, and so on.
  • indexing: This stage stores the data and optimizes the indexes.
  • searching: This stage runs queries and presents the results to the user. All these different stages ca be accomplished in one process, but splitting them across servers can improve performance as the log volumes and search load increase.

Splunk forwarders

Each machine that contains the log files generally runs a Splunk forwarder process. The job of this process is to read the logs on that machine or to run scripted inputs.

This installation is either of the following:

  • A full installation of Splunk, configured to forward data...
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