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Home > Data > Big Data > Implementing Splunk: Big Data Reporting and Development for Operational Intelligence
Implementing Splunk: Big Data Reporting and Development for Operational Intelligence
Implementing Splunk: Big Data Reporting and Development for Operational Intelligence

Implementing Splunk: Big Data Reporting and Development for Operational Intelligence: Learn to transform your machine data into valuable IT and business insights with this comprehensive and practical tutorial

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Implementing Splunk: Big Data Reporting and Development for Operational Intelligence

Chapter 2. Understanding Search

To successfully use Splunk, it is vital that you write effective searches. Using the index efficiently will make your initial discoveries faster, and the reports you create will run faster for you and others. In this chapter, we will cover:

  • How to write effective searches

  • How to search using fields

  • Understanding time

  • Saving and sharing searches

Using search terms effectively

The key to creating an effective search is to take advantage of the index. Splunk's index is effectively a huge word index, sliced by time. The single most important factor for the performance of your searches is how many events are pulled from disk. The following few key points should be committed to memory:

  • Search terms are case insensitive: Searches for error, Error, ERROR, and ErRoR are all the same thing.

  • Search terms are additive: Given the search item mary error, only events that contain both words will be found. There are Boolean and grouping operators to change this behavior; we will discuss these later.

  • Only the time frame specified is queried: This may seem obvious, but it's a big difference from a database, which would always have a single index across all events in a table. Since each index is sliced into new buckets over time, only the buckets that contain events for the time frame in question need to be queried.

  • Search terms are words, not parts...

Boolean and grouping operators

There are a few operators that you can use to refine your searches (note that these operators must be in uppercase to not be considered search terms):

  • AND is implied between terms. error mary is the same as error AND mary.

  • OR allows you to specify multiple values. error OR mary means "find any event that contains either word".

  • NOT applies to the next term or group. error NOT mary would find events that contain error but do not contain mary.

  • "" identifies a phrase. "Out of this world" will find this exact sequence of words. Out of this world would find any event that contains all of these words, but not necessarily in that order.

  • ( ) is used for grouping terms. Parentheses can help avoid confusion in logic. For instance, these two statements are equivalent:

    • bob error OR warn NOT debug

    • (bob AND (error OR warn)) AND NOT debug

  • = is reserved for specifying fields. Searching for an equal sign can be accomplished by wrapping it in quotes.

  • [ ] is used to perform...

Clicking to modify your search

Though you can probably figure it out by just clicking around, it is worth discussing the behavior of the GUI when moving your mouse around and clicking.

  • Clicking on any word or field value will add that term to the search.

  • Clicking on a word or field value that is already in the query will remove it from the query.

  • Clicking on any word or field value while holding down Alt (option on the Mac) will append that search term to the query, preceded by NOT. This is a very handy way to remove irrelevant results from query results.

Event segmentation

In Chapter 1, The Splunk Interface, we touched upon this setting in the Options dialog. The different options change what is highlighted as you mouse over the text in the search results, and therefore what is added to your query when clicked on. Let's see what happens to the phrase ip=10.20.30.40 with each setting:

  • inner highlights individual words between punctuation. Highlighted items would be ip, 10, 20, 30, and 40.

  • outer...

Using fields to search

When we explored the GUI in Chapter 1, The Splunk Interface, you probably noticed fields everywhere. Fields appear in the field picker on the left and under every event. Where fields actually come from is transparent to the user, who simply searches for key=value. We will discuss adding new fields in Chapter 3, Tables, Charts, and Fields, and in Chapter 10, Configuring Splunk.

Using the field picker

The field picker gives us easy access to the fields currently defined for the results of our query. Clicking on any field presents us with details about that field in our current search results.

As we go through the following items in this widget, we see a wealth of information right away:

  • Appears in X% of results is a good indication of whether we are getting the results we think we're getting. If every event in your results should contain this field, and this is not 100 percent, either your search can be made more specific or a field definition needs to be modified.

  • Show...

Using wildcards efficiently

Though the index is based on words, it is possible to use wildcards when needed, although some care must be taken.

Only trailing wildcards are efficient

Stated simply, bob* will find events containing Bobby efficiently, but *by or *ob* will not. The latter cases will scan all events in the time frame specified.

Wildcards are tested last

Wildcards are tested after all other terms. Given the search: authclass *ob* hello world, all other terms besides *ob* will be searched first. The more you can limit the results using full words and fields, the better your search will perform.

Supplementing wildcards in fields

Given the following events, a search for world would return both events:

2012-02-07T01:04:31.102-0600 INFO AuthClass Hello world. [user=Bobby, ip=1.2.3.3]
2012-02-07T01:23:34.204-0600 INFO BarClass Goodbye. [user=Bobby, ip=1.2.3.3, message="Out of this world"]

What if you only wanted the second event, but all you know is that the event contains world somewhere in...

All about time

Time is an important and confusing topic in Splunk. If you want to skip this section, absorb one concept—time must be parsed properly on the way into the index as it cannot be changed later without indexing the raw data again.

How Splunk parses time

Given the date 11-03-04, how would you interpret this date? Your answer probably depends on where you live. In the United States, you would probably read this as November 3, 2004. In Europe, you would probably read this as March 11, 2004. It would also be reasonable to read this as March 4, 2011.

Luckily, most dates are not this ambiguous, and Splunk makes a good effort. It is absolutely worth the trouble to give Splunk a little help by configuring the time format. We'll discuss the relevant configurations in Chapter 10, Configuring Splunk.

How Splunk stores time

Once the date is parsed, the date stored in Splunk is always stored as GMT epoch. Epoch time is the number of seconds since January 1, 1970, the birthday of Unix. By storing...

Making searches faster

We have talked about using the index to make searches faster. When starting a new investigation, following a few steps will help you get results faster:

  1. Set the time to the minimum time that you believe will be required to locate relevant events. For a chatty log, this may be as little as a minute. If you don't know when the events occurred, you might search a larger time frame and then zoom in by clicking on the timeline while the search is running.

  2. Specify the index if you have multiple indexes. It's good to get into the habit of starting your queries with the index name, for example, index=myapplicationindex error bob.

  3. Specify other fields that are relevant. The most common fields to specify are sourcetype and host, for example, index=myapplicationindex sourcetype="impl_splunk_gen" error bob.

    Note

    If you find yourself specifying the field source on a regular basis, you could probably benefit from defining more source types. Avoid using the sourcetype field to capture...

Sharing results with others

It is often convenient to share a specific set of results with another user. You could always export the results to a CSV file and share it, but this is cumbersome. Instead, to use a URL for sharing, start by choosing Save & share results… from the Save menu.

This opens the Save and Share Results panel.

The URL under Link to the results can be copied and sent to other users. A user visiting this URL will see exactly the same results you did, assuming the job has not expired.

The results are also available in the Jobs window. Clicking on the Jobs link in the top bar opens the Jobs window.

The App menu, Owner menu, Status menu, and search bar let you filter what jobs are displayed.

The table has the following columns:

  • Dispatched at is the time at which the search started.

  • Owner is the user that started the job. Sometimes jobs will appear with system as the user if the saved search is configured in an application but not owned by a particular user.

  • Application specifies...

Saving searches for reuse

Let's build a query, save it, and make an alert out of it.

First, let's find errors that affect mary, one of our most important users. This can simply be the query mary error. Looking at some sample log messages that match this query, we see that some of these events probably don't matter (the dates have been removed to shorten the lines).

  ERROR LogoutClass error, ERROR, Error! [user=mary, ip=3.2.4.5]
  WARN AuthClass error, ERROR, Error! [user=mary, ip=1.2.3.3]
  ERROR BarCLass Hello world. [user=mary, ip=4.3.2.1]
  WARN LogoutClass error, ERROR, Error! [user=mary, ip=1.2.3.4]
  DEBUG FooClass error, ERROR, Error! [user=mary, ip=3.2.4.5]
  ERROR AuthClass Nothing happened. This is worthless. Don't log this.[user=mary, ip=1.2.3.3]

We can probably skip the DEBUG messages; the LogoutClass messages look harmless; and the last message actually says that it's worthless.

mary error NOT debug NOT worthless NOT logoutclass limits the results to:

  WARN AuthClass error...

Creating alerts from searches

Any saved search can also be run on a schedule. One use for scheduled searches is firing alerts. To get started, choose Alert… from the Create menu.

A wizard interface is presented, covering three steps.

Schedule

The Schedule step provides the following options:

  • Trigger in real-time whenever a result matches: This option will leave a real-time search running all the time and will immediately fire an alert whenever an event is seen.

    This option will create an alert every time an event that matches your search occurs. There is an important throttling option in the next step.

  • Run on a schedule once every…: New options now appear below the menu.

    • Schedule: You can choose to either run your search on a set schedule or run your alert according to a cron schedule. Keep in mind that the time frame selected in the time picker will be used each time the query runs—you probably don't want to run a query looking at 24 hours of data every minute.

    • Trigger if lets you choose when...

Summary

In this chapter, we covered searching in Splunk and doing a few useful things with those search results. There are lots of little tricks that we will touch upon as we go forward.

In the next chapter, we will start using fields for more than searches; we'll build tables and graphs, and then, we'll learn how to make our own fields.

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Key benefits

  • Learn to search, dashboard, configure, and deploy Splunk on one machine or thousands
  • Start working with Splunk fast, with a tested set of practical examples and useful advice
  • Step-by-step instructions and examples with a comprehensive coverage for Splunk veterans and newbies alike

Description

Splunk is a data collection, indexing, and visualization engine for operational intelligence. It's a powerful and versatile search and analysis engine that lets you investigate, troubleshoot, monitor, alert, and report on everything that's happening in your entire IT infrastructure from one location in real time. Splunk collects, indexes, and harnesses all the fast moving machine data generated by our applications, servers, and devices - physical, virtual, and in the cloud.Given a mountain of machine data, this book shows you exactly how to learn to use Splunk to make something useful from it. Depending on your needs, you can learn to search, transform, and display data, or learn to administer your Splunk installation, large or small. "Implementing Splunk: Big Data Reporting and Development for Operational Intelligence" will help you get your job done faster, whether you read from the beginning or jump to what you need to know today. New and experienced users alike will find nuggets of wisdom throughout.This book provides you with valuable examples and step-by-step instructions, showing you how to take advantage of everything Splunk has to offer you, to make the most out of your machine data."Implementing Splunk: Big Data Reporting and Development for Operational Intelligence" takes you on a journey right from inception to a fully functioning implementation of Splunk. Using a real-world data walkthrough, you'll be shown how to search effectively, create fields, build dashboards, reports, and package apps, manage your indexes, integrate into the enterprise, and extend Splunk. This practical implementation guide equips you with high-level knowledge for configuring, deploying, extending, and integrating Splunk. Depending on the goal and skills of the reader, enough topics are covered to get you on your way to dashboard guru, app developer, or enterprise administrator. This book uses examples curates reference, and sage advice to help you make the most of this incredibly powerful tool.

Who is this book for?

The book targets professionals and organizations who want to implement or have already implemented Splunk for log analysis and indexing. Analysts and IT staff for end-to-end investigation, performance monitoring, and so on will also learn from the practical examples. It would even help managers to build reports and summarize the health, performance, and activity of their IT infrastructure and business. You will also find it helpful as a technical administrator, consultant, or end user.This book aims to be useful to Splunk users of all levels, from complete newbie to seasoned user. The book assumes that you have access to a copy of Splunk, ideally not in production. Many examples also assume your user has admin rights.

What you will learn

  • How to write searches that are fast and lean
  • How to create fields from your unstructured data
  • How to enrich your data with lookups and commands
  • How to transform your data into useful and beautiful reports
  • How to build professional looking and informative dashboards
  • How to make apps to organize and share your searches and dashboards
  • How to manage configurations for one to thousands of instances
  • How to integrate with enterprise systems
  • How to extend Splunk with scripts and advanced configuration

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Table of Contents

12 Chapters
The Splunk Interface Chevron down icon Chevron up icon
The Splunk Interface
Logging in to Splunk
The Home app
The top bar
Search app
Using the time picker
Using the field picker
Using Manager
Summary
Understanding Search Chevron down icon Chevron up icon
Understanding Search
Using search terms effectively
Boolean and grouping operators
Clicking to modify your search
Using fields to search
Using wildcards efficiently
All about time
Making searches faster
Sharing results with others
Saving searches for reuse
Creating alerts from searches
Summary
Tables, Charts, and Fields Chevron down icon Chevron up icon
Tables, Charts, and Fields
About the pipe symbol
Using top to show common field values
Using stats to aggregate values
Using chart to turn data
Using timechart to show values over time
Working with fields
Summary
Simple XML Dashboards Chevron down icon Chevron up icon
Simple XML Dashboards
The purpose of dashboards
Using wizards to build dashboards
Scheduling the generation of dashboards
Editing the XML directly
UI Examples app
Building forms
Summary
Advanced Search Examples Chevron down icon Chevron up icon
Advanced Search Examples
Using subsearches to find loosely related events
Using transaction
Determining concurrency
Calculating events per slice of time
Rebuilding top
Summary
Extending Search Chevron down icon Chevron up icon
Extending Search
Using tags to simplify search
Using event types to categorize results
Using lookups to enrich data
Using macros to reuse logic
Creating workflow actions
Using external commands
Summary
Working with Apps Chevron down icon Chevron up icon
Working with Apps
Defining an app
Included apps
Installing apps
Building your first app
Editing navigation
Customizing the appearance of your app
Object permissions
App directory structure
Adding your app to Splunkbase
Summary
Building Advanced Dashboards Chevron down icon Chevron up icon
Building Advanced Dashboards
Reasons for working with advanced XML
Reasons for not working with advanced XML
Development process
Advanced XML structure
Converting simple XML to advanced XML
Module logic flow
Understanding layoutPanel
Reusing a query
Using intentions
Creating a custom drilldown
Third-party add-ons
Summary
Summary Indexes and CSV Files Chevron down icon Chevron up icon
Summary Indexes and CSV Files
Understanding summary indexes
When to use a summary index
When to not use a summary index
Populating summary indexes with saved searches
Using summary index events in a query
Using sistats, sitop, and sitimechart
How latency affects summary queries
How and when to backfill summary data
Reducing summary index size
Calculating top for a large time frame
Storing raw events in a summary index
Using CSV files to store transient data
Summary
Configuring Splunk Chevron down icon Chevron up icon
Configuring Splunk
Locating Splunk configuration files
The structure of a Splunk configuration file
Configuration merging logic
An overview of Splunk .conf files
User interface resources
Summary
Advanced Deployments Chevron down icon Chevron up icon
Advanced Deployments
Planning your installation
Splunk instance types
Common data sources
Sizing indexers
Planning redundancy
Working with multiple indexes
Deploying the Splunk binary
Using apps to organize configuration
Configuration distribution
Using LDAP for authentication
Using Single Sign On
Load balancers and Splunk
Multiple search heads
Summary
Extending Splunk Chevron down icon Chevron up icon
Extending Splunk
Writing a scripted input to gather data
Using Splunk from the command line
Querying Splunk via REST
Writing commands
Writing a scripted lookup to enrich data
Writing an event renderer
Writing a scripted alert action to process results
Summary

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Putzmanmusing Dec 25, 2013
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Great book and shows you how splunk is thee tool for big data. This proves the point that's Splunk today is not your grandfathers Splunk of yesterday.
Amazon Verified review Amazon
Amazon Customer Sep 01, 2013
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I really enjoyed this book and in a weekend it took an awful lot the mystery out of Splunk and got me productive very quickly.
Amazon Verified review Amazon
Paul Schofield Mar 23, 2013
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Vince does a great job of walking a user through installing, configuring, using and optimizing Splunk for any organization. There are many chapters that I will read and re-read as I use Splunk everyday to get my IT work done.Thumbs up!
Amazon Verified review Amazon
Jason Mar 03, 2014
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
This book is a must read if you are planning to implement Splunk in your environment. I was looking for more of what it can do and how to do it, but still worth my time.
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Tfritz Feb 05, 2014
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
Very good book for beginner to intermediate. Its a little light on specifics for some of the more complicated tasks. Splunks web site isn't the best source for documentation so it's nice to have a reference.
Amazon Verified review Amazon

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Deep Learning with TensorFlow and Keras – 3rd edition
Deep Learning with TensorFlow and Keras – 3rd edition
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Oct 2022 698 pages
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Machine Learning Engineering with Python
Machine Learning Engineering with Python
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Aug 2023 462 pages
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About the author

Profile icon VINCENT BUMGARNER
VINCENT BUMGARNER
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Vincent Bumgarner has been designing software for over 20 years, working with many languages on nearly as many platforms. He started using Splunk in 2007 and has enjoyed watching the product evolve over the years. While working for Splunk, he has helped many companies train dozens of users to drive, extend, and administer this extremely flexible product. At least one person in every company he has worked with has asked for a book, and he hopes that this book will help fill their shelves.
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