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Splunk Operational Intelligence Cookbook

Splunk Operational Intelligence Cookbook

4.2 (15)
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Splunk Operational Intelligence Cookbook

Splunk Operational Intelligence Cookbook

4.2 (15)
Buy this Book

Overview of this book

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 a business – IT, Security, Product, Marketing, and many more!
Table of Contents (12 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. Play Time – Getting Data In
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1. Play Time – Getting Data In
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Introduction
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Indexing files and directories
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Getting data through network ports
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Using scripted inputs
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Using modular inputs
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Using the Universal Forwarder to gather data
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Loading the sample data for this book
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Defining field extractions
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Defining event types and tags
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Summary
2
2. Diving into Data – Search and Report
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2. Diving into Data – Search and Report
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Introduction
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Making raw event data readable
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Finding the most accessed web pages
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Finding the most used web browsers
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Identifying the top-referring websites
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Charting web page response codes
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Displaying web page response time statistics
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Listing the top viewed products
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Charting the application's functional performance
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Charting the application's memory usage
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Counting the total number of database connections
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Summary
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3. Dashboards and Visualizations – Make Data Shine
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3. Dashboards and Visualizations – Make Data Shine
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Introduction
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Creating an Operational Intelligence dashboard
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Using a pie chart to show the most accessed web pages
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Displaying the unique number of visitors
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Using a gauge to display the number of errors
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Charting the number of method requests by type and host
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Creating a timechart of method requests, views, and response times
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Using a scatter chart to identify discrete requests by size and response time
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Creating an area chart of the application's functional statistics
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Using a bar chart to show the average amount spent by category
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Creating a line chart of item views and purchases over time
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Summary
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4. Building an Operational Intelligence Application
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4. Building an Operational Intelligence Application
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Introduction
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Creating an Operational Intelligence application
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Adding dashboards and reports
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Organizing the dashboards more efficiently
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Dynamically drilling down on activity reports
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Creating a form to search web activities
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Linking web page activity reports to the form
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Displaying a geographical map of visitors
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Scheduling the PDF delivery of a dashboard
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Summary
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5. Extending Intelligence – Data Models and Pivoting
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5. Extending Intelligence – Data Models and Pivoting
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Introduction
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Creating a data model for web access logs
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Creating a data model for application logs
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Accelerating data models
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Pivoting total sales transactions
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Pivoting purchases by geographical location
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Pivoting slowest responding web pages
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Pivot charting top error codes
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Summary
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6. Diving Deeper – Advanced Searching
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6. Diving Deeper – Advanced Searching
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Introduction
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Calculating the average session time on a website
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Calculating the average execution time for multi-tier web requests
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Displaying the maximum concurrent checkouts
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Analyzing the relationship of web requests
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Predicting website-traffic volumes
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Finding abnormally sized web requests
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Identifying potential session spoofing
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Summary
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7. Enriching Data – Lookups and Workflows
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7. Enriching Data – Lookups and Workflows
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Introduction
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Looking up product code descriptions
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Flagging suspicious IP addresses
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Creating a session state table
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Adding hostnames to IP addresses
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Searching ARIN for a given IP address
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Triggering a Google search for a given error
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Creating a ticket for application errors
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Looking up inventory from an external database
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Summary
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8. Being Proactive – Creating Alerts
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8. Being Proactive – Creating Alerts
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Introduction
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Alerting on abnormal web page response times
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Alerting on errors during checkout in real time
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Alerting on abnormal user behavior
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Alerting on failure and triggering a scripted response
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Alerting when predicted sales exceed inventory
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Summary
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9. Speed Up Intelligence – Data Summarization
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9. Speed Up Intelligence – Data Summarization
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Introduction
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Calculating an hourly count of sessions versus completed transactions
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Backfilling the number of purchases by city
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Displaying the maximum number of concurrent sessions over time
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Summary
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10. Above and Beyond – Customization, Web Framework, REST API, and SDKs
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10. Above and Beyond – Customization, Web Framework, REST API, and SDKs
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Introduction
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Customizing the application's navigation
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Adding a force-directed graph of web hits
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Adding a calendar heatmap of product purchases
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Remotely querying Splunk's REST API for unique page views
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Creating a Python application to return unique IP addresses
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Creating a custom search command to format product names
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Summary
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Index
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Index

Adding a force-directed graph of web hits

As you have seen from the other recipes throughout the book, we have used many of the normal everyday visualizations seen commonly in spreadsheets and presentations. As data intelligence tools such as Splunk push the boundaries of getting data into a user's hands, there is a need to deliver and represent data via new and unique visualizations.

This recipe will show you how to install the Splunk web framework and create a force-directed graph (FDG) of relationships between web page hits that will be populated as a new dashboard in the Operational Intelligence application.

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 navigating the Splunk user interface and using the Splunk search language. Some basic knowledge of JavaScript is recommended.

How to do it...

Follow the steps in this recipe to add a force-directed...

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