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Home > Data > Operational Intelligence > Splunk Operational Intelligence Cookbook
Splunk Operational Intelligence Cookbook
Splunk Operational Intelligence Cookbook

Splunk Operational Intelligence Cookbook: Transform Big Data into business-critical insights and rethink operational Intelligence with Splunk , Second Edition

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Splunk Operational Intelligence Cookbook

Chapter 2. Diving into Data – Search and Report

In this chapter, we will cover the basic ways to search data in Splunk. We will cover the following recipes:

  • Making raw event data readable
  • Finding the most accessed web pages
  • Finding the most used web browsers
  • Identifying the top-referring websites
  • Charting web page response codes
  • Displaying web page response time statistics
  • Listing the top-viewed products
  • Charting the application's functional performance
  • Charting the application's memory usage
  • Counting the total number of database connections

Introduction

In the previous chapter, we learned about the various ways to get data into Splunk. In this chapter, we will dive right into the data and get our hands dirty.

The ability to search machine data is one of Splunk's core functions, and it should come as no surprise that many other features and functions of Splunk are heavily driven-off searches. Everything from basic reports and dashboards to data models and fully featured Splunk applications are powered by Splunk searches behind the scenes.

Splunk has its own search language known as the Search Processing Language (SPL). This SPL contains hundreds of search commands, most of which also have several functions, arguments, and clauses. While a basic understanding of SPL is required in order to effectively search your data in Splunk, you are not expected to know all the commands! Even the most seasoned ninjas do not know all the commands and regularly refer to the Splunk manuals, website, or Splunk Answers (http://answers.splunk...

Making raw event data readable

When a basic search is executed in Splunk from the search bar, the search results are displayed in a raw event format by default. To many users, this raw event information is not particularly readable, and valuable information is often clouded by other less valuable data within the event. Additionally, if the events span several lines, only a few events can be seen on the screen at any one time.

In this recipe, we will write a Splunk search to demonstrate how we can leverage Splunk commands to make raw event data readable, tabulating events and displaying only the fields we are interested in.

Getting ready

To step through this recipe, you will need a running Splunk Enterprise server, with the sample data loaded from Chapter 1, Play Time – Getting Data In. You should be familiar with the Splunk search bar and search results area.

How to do it…

Follow the given steps to search and tabulate the selected event data:

  1. Log in to your Splunk server.
  2. Select...

Finding the most accessed web pages

One of the data samples we loaded in Chapter 1, Play Time – Getting Data In, contained access logs from our web server. These have a Splunk sourcetype of access_combined and detail all pages accessed by the users of our web application. We are particularly interested in knowing which pages are being accessed the most, as this information provides great insight into how our e-commerce web application is being used. It could also help influence changes to our web application such that rarely visited pages are removed, or our application is redesigned to be more efficient.

In this recipe, we will write a Splunk search to find the most accessed web pages over a given period of time.

Getting ready

To step through this recipe, you will need a running Splunk Enterprise server, with the sample data loaded from Chapter 1, Play Time – Getting Data In. You should be familiar with the Splunk search bar and the time range picker to the right of it.

How to...

Finding the most used web browsers

Users visiting our website use a variety of devices and web browsers. By analyzing the web access logs, we can understand which browsers are the most popular and, therefore, which browsers our site must support at the least. We can also use this same information to help identify the types of devices that people are using.

In this recipe, we will write a Splunk search to find the most used web browsers over a given period of time. We will then make use of both the eval and replace commands to clean up the data a bit.

Getting ready

To step through this recipe, you will need a running Splunk Enterprise server, with the sample data loaded from Chapter 1, Play Time – Getting Data In. You should be familiar with the Splunk search bar and the time range picker to the right of it.

How to do it…

Follow the given steps to search for the most used web browsers:

  1. Log in to your Splunk server.
  2. Select the Search & Reporting application.
  3. Ensure that the time...

Identifying the top-referring websites

Our web access logs continue to give us great information about our website and the users visiting the site. Understanding where our users are coming from provides insight into potential sales leads and/or which marketing activities might be working better over others. For this information, we look for the referer_domain field value within the log data.

In this recipe, we will write a Splunk search to find the top-referring websites.

Getting ready

To step through this recipe, you will need a running Splunk Enterprise server, with the sample data loaded from Chapter 1, Play Time – Getting Data In. You should be familiar with the Splunk search bar and the time range picker.

How to do it…

Follow the given steps to search for the top-referring websites:

  1. Log in to your Splunk server.
  2. Select the Search & Reporting application.
  3. Ensure that the time range picker is set to Last 24 hours and type the following search into the Splunk search bar. Then...

Charting web page response codes

Log data often contains seemingly cryptic codes that have all sorts of meanings. This is true of our web access logs, where there is a status code that represents a web page response. This code is very useful as it can tell us whether certain events were successful or not. For example, error codes found in purchase events are less than ideal, and if our website was at fault, then we might have lost a sale.

In this recipe, we will write a Splunk search to chart web page responses against the various web pages on the site.

Getting ready

To step through this recipe, you will need a running Splunk Enterprise server, with the sample data loaded from Chapter 1, Play Time – Getting Data In. You should be familiar with the Splunk search bar and the time range picker.

How to do it…

Follow the given steps to chart the web page response codes over time:

  1. Log in to your Splunk server.
  2. Select the Search & Reporting application.
  3. Ensure that the time range picker...

Introduction

In the previous chapter, we learned about the various ways to get data into Splunk. In this chapter, we will dive right into the data and get our hands dirty.

The ability to search machine data is one of Splunk's core functions, and it should come as no surprise that many other features and functions of Splunk are heavily driven-off searches. Everything from basic reports and dashboards to data models and fully featured Splunk applications are powered by Splunk searches behind the scenes.

Splunk has its own search language known as the Search Processing Language (SPL). This SPL contains hundreds of search commands, most of which also have several functions, arguments, and clauses. While a basic understanding of SPL is required in order to effectively search your data in Splunk, you are not expected to know all the commands! Even the most seasoned ninjas do not know all the commands and regularly refer to the Splunk manuals, website, or Splunk Answers (http://answers.splunk.com...

Making raw event data readable

When a basic search is executed in Splunk from the search bar, the search results are displayed in a raw event format by default. To many users, this raw event information is not particularly readable, and valuable information is often clouded by other less valuable data within the event. Additionally, if the events span several lines, only a few events can be seen on the screen at any one time.

In this recipe, we will write a Splunk search to demonstrate how we can leverage Splunk commands to make raw event data readable, tabulating events and displaying only the fields we are interested in.

Getting ready

To step through this recipe, you will need a running Splunk Enterprise server, with the sample data loaded from Chapter 1, Play Time – Getting Data In. You should be familiar with the Splunk search bar and search results area.

How to do it…

Follow the given steps to search and tabulate the selected event data:

  1. Log in to your Splunk server.

  2. Select the Search &amp...

Finding the most accessed web pages

One of the data samples we loaded in Chapter 1, Play Time – Getting Data In, contained access logs from our web server. These have a Splunk sourcetype of access_combined and detail all pages accessed by the users of our web application. We are particularly interested in knowing which pages are being accessed the most, as this information provides great insight into how our e-commerce web application is being used. It could also help influence changes to our web application such that rarely visited pages are removed, or our application is redesigned to be more efficient.

In this recipe, we will write a Splunk search to find the most accessed web pages over a given period of time.

Getting ready

To step through this recipe, you will need a running Splunk Enterprise server, with the sample data loaded from Chapter 1, Play Time – Getting Data In. You should be familiar with the Splunk search bar and the time range picker to the right of it.

How to do it…

Follow...

Finding the most used web browsers

Users visiting our website use a variety of devices and web browsers. By analyzing the web access logs, we can understand which browsers are the most popular and, therefore, which browsers our site must support at the least. We can also use this same information to help identify the types of devices that people are using.

In this recipe, we will write a Splunk search to find the most used web browsers over a given period of time. We will then make use of both the eval and replace commands to clean up the data a bit.

Getting ready

To step through this recipe, you will need a running Splunk Enterprise server, with the sample data loaded from Chapter 1, Play Time – Getting Data In. You should be familiar with the Splunk search bar and the time range picker to the right of it.

How to do it…

Follow the given steps to search for the most used web browsers:

  1. Log in to your Splunk server.

  2. Select the Search & Reporting application.

  3. Ensure that the time range picker is...

Identifying the top-referring websites

Our web access logs continue to give us great information about our website and the users visiting the site. Understanding where our users are coming from provides insight into potential sales leads and/or which marketing activities might be working better over others. For this information, we look for the referer_domain field value within the log data.

In this recipe, we will write a Splunk search to find the top-referring websites.

Getting ready

To step through this recipe, you will need a running Splunk Enterprise server, with the sample data loaded from Chapter 1, Play Time – Getting Data In. You should be familiar with the Splunk search bar and the time range picker.

How to do it…

Follow the given steps to search for the top-referring websites:

  1. Log in to your Splunk server.

  2. Select the Search & Reporting application.

  3. Ensure that the time range picker is set to Last 24 hours and type the following search into the Splunk search bar. Then, click on Search...

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Key benefits

  • *This is the most up-to-date book on Splunk 6.3 and teaches you how to tackle real-world operational intelligence scenarios efficiently
  • *Get business insights using machine data using this easy-to-follow guide
  • *Search, monitor, and analyze your operational data skillfully using this recipe-based, practical guide

Description

Splunk makes it easy for you to take control of your data, and with Splunk Operational Cookbook, you can be confident that you are taking advantage of the Big Data revolution and driving your business with the cutting edge of operational intelligence and business analytics. With more than 70 recipes that demonstrate all of Splunk’s features, not only will you find quick solutions to common problems, but you’ll also learn a wide range of strategies and uncover new ideas that will make you rethink what operational intelligence means to you and your organization. You’ll discover recipes on data processing, searching and reporting, dashboards, and visualizations to make data shareable, communicable, and most importantly meaningful. You’ll also find step-by-step demonstrations that walk you through building an operational intelligence application containing vital features essential to understanding data and to help you successfully integrate a data-driven way of thinking in your organization. Throughout the book, you’ll dive deeper into Splunk, explore data models and pivots to extend your intelligence capabilities, and perform advanced searching to explore your data in even more sophisticated ways. Splunk is changing the business landscape, so make sure you’re taking advantage of it.

Who is this book for?

This book is intended for users of all levels who are looking to leverage the Splunk Enterprise platform as a valuable operational intelligence tool. The recipes provided in this book will appeal to individuals from all facets of business, IT, security, product, marketing, and many more! Also, existing users of Splunk who want to upgrade and get up and running with Splunk 6.3 will find this book invaluable.

What you will learn

  • *Use Splunk to gather, analyze, and report on data
  • *Create dashboards and visualizations that make data meaningful
  • *Build an operational intelligence application with extensive features and functionality
  • *Enrich operational data with lookups and workflows
  • *Model and accelerate data and perform pivot-based reporting
  • *Build real-time, scripted, and other intelligence-driven alerts
  • *Summarize data for longer term trending, reporting, and analysis
  • *Integrate advanced JavaScript charts and leverage Splunk s API
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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jun 08, 2016
Length: 436 pages
Edition : 2nd
Language : English
ISBN-13 : 9781785284991
Vendor :
Splunk
Category :
Data
Concepts :
Operational Intelligence
Tools :
Splunk

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Product Details

Publication date : Jun 08, 2016
Length: 436 pages
Edition : 2nd
Language : English
ISBN-13 : 9781785284991
Vendor :
Splunk
Category :
Data
Concepts :
Operational Intelligence
Tools :
Splunk

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Table of Contents

11 Chapters
1. Play Time – Getting Data In Chevron down icon Chevron up icon
1. Play Time – Getting Data In
Introduction
Indexing files and directories
Getting data through network ports
Using scripted inputs
Using modular inputs
Using the Universal Forwarder to gather data
Loading the sample data for this book
Defining field extractions
Defining event types and tags
2. Diving into Data – Search and Report Chevron down icon Chevron up icon
2. Diving into Data – Search and Report
Introduction
Making raw event data readable
Finding the most accessed web pages
Finding the most used web browsers
Identifying the top-referring websites
Charting web page response codes
Displaying web page response time statistics
Listing the top viewed products
Charting the application's functional performance
Charting the application's memory usage
Counting the total number of database connections
3. Dashboards and Visualizations – Making Data Shine Chevron down icon Chevron up icon
3. Dashboards and Visualizations – Making Data Shine
Introduction
Creating an Operational Intelligence dashboard
Using a pie chart to show the most accessed web pages
Displaying the unique number of visitors
Using a gauge to display the number of errors
Charting the number of method requests by type and host
Creating a timechart of method requests, views, and response times
Using a scatter chart to identify discrete requests by size and response time
Creating an area chart of the application's functional statistics
Using a bar chart to show the average amount spent by category
Creating a line chart of item views and purchases over time
4. Building an Operational Intelligence Application Chevron down icon Chevron up icon
4. Building an Operational Intelligence Application
Introduction
Creating an Operational Intelligence application
Adding dashboards and reports
Organizing the dashboards more efficiently
Dynamically drilling down on activity reports
Creating a form for searching web activity
Linking web page activity reports to the form
Displaying a geographical map of visitors
Scheduling PDF delivery of a dashboard
5. Extending Intelligence – Data Models and Pivoting Chevron down icon Chevron up icon
5. Extending Intelligence – Data Models and Pivoting
Introduction
Creating a data model for web access logs
Creating a data model for application logs
Accelerating data models
Pivoting total sales transactions
Pivoting purchases by geographic location
Pivoting slowest responding web pages
Pivot charting top error codes
6. Diving Deeper – Advanced Searching Chevron down icon Chevron up icon
6. Diving Deeper – Advanced Searching
Introduction
Calculating the average session time on a website
Calculating the average execution time for multi-tier web requests
Displaying the maximum concurrent checkouts
Analyzing the relationship of web requests
Predicting website traffic volumes
Finding abnormally-sized web requests
Identifying potential session spoofing
7. Enriching Data – Lookups and Workflows Chevron down icon Chevron up icon
7. Enriching Data – Lookups and Workflows
Introduction
Looking up product code descriptions
Flagging suspect IP addresses
Creating a session state table
Adding hostnames to IP addresses
Searching ARIN for a given IP address
Triggering a Google search for a given error
Creating a ticket for application errors
Looking up inventory from an external database
8. Being Proactive – Creating Alerts Chevron down icon Chevron up icon
8. Being Proactive – Creating Alerts
Introduction
Alerting on abnormal web page response times
Alerting on errors during checkout in real time
Alerting on abnormal user behavior
Alerting on failure and triggering a scripted response
Alerting when predicted sales exceed inventory
9. Speeding Up Intelligence – Data Summarization Chevron down icon Chevron up icon
9. Speeding Up Intelligence – Data Summarization
Introduction
Calculating an hourly count of sessions versus completed transactions
Backfilling the number of purchases by city
Displaying the maximum number of concurrent sessions over time
10. Above and Beyond – Customization, Web Framework, REST API, HTTP Event Collector, and SDKs Chevron down icon Chevron up icon
10. Above and Beyond – Customization, Web Framework, REST API, HTTP Event Collector, and SDKs
Introduction
Customizing the application navigation
Adding a force-directed graph of web hits
Adding a calendar heatmap of product purchases
Adding cell highlighting of average product price
Remotely querying Splunk's REST API for unique page views
Creating a Python application to return unique IP addresses
Creating a custom search command to format product names
Collecting data from remote scanning devices
Index Chevron down icon Chevron up icon
Index

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Phil May 03, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Awesome Book!!! Have used and update many of my scripts to gather information!!
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Amazon Customer Nov 03, 2017
Full star icon Full star icon Full star icon Full star icon Full star icon 5
good reference
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Amazon Customer Dec 30, 2017
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Wow~~ What a wonderful books. This book is very easy to read and understand. The topics is very useful.Splunk has many functions. This book shows you how to use those functions. It is very practical.
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Scotty B Jul 18, 2016
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
Some great information in the book with explanations for commands but it's organized in a strange fashion. You can read through the book and learn things about splunk but it's difficult to go to a specific idea or topic. Information is organized in a "recipe" format. So you basically have a bunch of examples of how to do things but this would not really work out to well as a reference to find information quickly.
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Kevin Marks Sep 27, 2017
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It's good, but I knew half of already. I'll use it as reference.
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Generative AI with LangChain
Generative AI with LangChain
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Dec 2023 376 pages
Full star icon 4.1 (33)
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Modern Generative AI with ChatGPT and OpenAI Models
Modern Generative AI with ChatGPT and OpenAI Models
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May 2023 286 pages
Full star icon 4.1 (29)
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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
Full star icon 4.5 (44)
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Machine Learning Engineering with Python
Machine Learning Engineering with Python
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Aug 2023 462 pages
Full star icon 4.6 (36)
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About the 4 authors

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Profile icon Josh Diakun
Josh Diakun
Josh Diakun is an IT operations and security specialist with a focus on creating data-driven operational processes. He has over 10 years of experience managing and architecting enterprise-grade IT environments. For the past 7 years, he has been architecting, deploying and developing on Splunk as the core platform for organizations to gain security and operational intelligence. Josh is a founding partner at Discovered Intelligence, a company specializing in data intelligence services and solutions. He is also a co-founder of the Splunk Toronto User Group.
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Profile icon Jose E. Hernandez
Jose E. Hernandez
Jose Hernandez is currently the Director of Security Solutions at Zenege Inc. with a vast experience in security analytics. He started his professional career at Prolexic Technologies (now Akamai) in DDOS fighting attacks from anonymous and lulzsec against fortune 100 companies. While working at Splunk Inc. as a Security Architect, he built and released an auto-mitigation framework that has been used to automatically fight attacks in large organizations. In the past, he has helped build security operation centers as well as run a public threat intelligence service. Jose is originally from Miami, Florida where he completed his Master's degree in Information Security from Nova Southeastern University. He also achieved two undergraduate Bachelor degrees from Florida International University in the field of Management of Information Systems and Information Technologies. Although security information has been the focus of his career, Jose has found that his true passion is in solving problems and creating solutions. As an example, he built an underwater remote control vehicle called the SensorSub, which was used to test and measure toxicity in Miami's waterways. As per the contact information, my email is josehelps@gmail.com, twitter: divious_1 and github divious1
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Profile icon Derek Mock
Derek Mock
Derek Mock is a software developer and big data architect who specializes in IT operations, information security, and cloud technologies. He has 15 years' experience developing and operating large enterprise-grade deployments and SaaS applications. He is a founding partner at Discovered Intelligence, a company specializing in data intelligence services and solutions. For the past 6 years, he has been leveraging Splunk as the core tool to deliver key operational intelligence. Derek is based in Toronto, Canada, and is a co-founder of the Splunk Toronto User Group.
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Profile icon Paul R. Johnson
Paul R. Johnson
Paul R Johnson has over 10 years of data intelligence experience in the areas of information security, operations, and compliance. He is a partner at Discovered Intelligence, a company specializing in data intelligence services and solutions. Paul previously worked for a Fortune 10 company, leading IT risk intelligence initiatives and managing a global Splunk deployment. Paul co-founded the Splunk Toronto User Group and lives and works in Toronto, Canada.
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Shipping Details

USA:

'

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

Economy: Can deliver to P. O. Boxes and private residences.
Trackable service with delivery to addresses in Australia only.
Delivery time ranges from 7-9 business days for VIC and 8-10 business days for Interstate metro
Delivery time is up to 15 business days for remote areas of WA, NT & QLD.

Premium: Delivery to addresses in Australia only
Trackable delivery to most P. O. Boxes and private residences in Australia within 4-5 days based on the distance to a destination following dispatch.

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Disclaimer:
All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.


Unfortunately, due to several restrictions, we are unable to ship to the following countries:

  1. Afghanistan
  2. American Samoa
  3. Belarus
  4. Brunei Darussalam
  5. Central African Republic
  6. The Democratic Republic of Congo
  7. Eritrea
  8. Guinea-bissau
  9. Iran
  10. Lebanon
  11. Libiya Arab Jamahriya
  12. Somalia
  13. Sudan
  14. Russian Federation
  15. Syrian Arab Republic
  16. Ukraine
  17. Venezuela
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