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Implementing Splunk: Big Data Reporting and Development for Operational Intelligence

You're reading from  Implementing Splunk: Big Data Reporting and Development for Operational Intelligence

Product type Book
Published in Jan 2013
Publisher Packt
ISBN-13 9781849693288
Pages 448 pages
Edition 1st Edition
Languages
Concepts
Author (1):
VINCENT BUMGARNER VINCENT BUMGARNER
Profile icon VINCENT BUMGARNER

Table of Contents (19) Chapters

Implementing Splunk: Big Data Reporting and Development for Operational Intelligence
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. The Splunk Interface 2. Understanding Search 3. Tables, Charts, and Fields 4. Simple XML Dashboards 5. Advanced Search Examples 6. Extending Search 7. Working with Apps 8. Building Advanced Dashboards 9. Summary Indexes and CSV Files 10. Configuring Splunk 11. Advanced Deployments 12. Extending Splunk Index

Writing a scripted input to gather data


Scripted inputs allow you to run some piece of code on a scheduled basis, and capture the output as if it were simply being written to a file. It does not matter what language the script is written in, or where it lives, as long it is executable. We touched on this topic in the Using scripts to gather data section in Chapter 11, Advanced Deployments. Let's write a few more examples.

Capturing script output with no date

One common problem with script output is the lack of a predictable date or date format. In this situation, the easiest thing to do is to tell Splunk to not try to parse a date at all, and instead use the current date instead. Let's make a script that lists open network connections:

from subprocess import Popen
from subprocess import PIPE
from collections import defaultdict
import re


def add_to_key(fieldname, fields):
    return " " + fieldname + "+" + fields[fieldname]

output = Popen("netstat -n -p tcp", stdout=PIPE, 
             ...
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