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Splunk Operational Intelligence Cookbook

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Splunk Operational Intelligence Cookbook

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Splunk Operational Intelligence Cookbook
Oct, 2014 | 414 pages
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Table of Contents (17 chapters)
Splunk Operational Intelligence Cookbook
Splunk Operational Intelligence Cookbook
Credits
Credits
About the Authors
About the Authors
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Play Time – Getting Data In
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
Summary
2
Diving into Data – Search and Report
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
Summary
3
Dashboards and Visualizations – Make Data Shine
Dashboards and Visualizations – Make 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
Summary
4
Building an Operational Intelligence Application
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 to search web activities
Linking web page activity reports to the form
Displaying a geographical map of visitors
Scheduling the PDF delivery of a dashboard
Summary
5
Extending Intelligence – Data Models and Pivoting
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 geographical location
Pivoting slowest responding web pages
Pivot charting top error codes
Summary
6
Diving Deeper – Advanced Searching
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
Summary
7
Enriching Data – Lookups and Workflows
Enriching Data – Lookups and Workflows
Introduction
Looking up product code descriptions
Flagging suspicious 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
Summary
8
Being Proactive – Creating Alerts
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
Summary
9
Speed Up Intelligence – Data Summarization
Speed 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
Summary
10
Above and Beyond – Customization, Web Framework, REST API, and SDKs
Above and Beyond – Customization, Web Framework, REST API, and SDKs
Introduction
Customizing the application's navigation
Adding a force-directed graph of web hits
Adding a calendar heatmap of product purchases
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
Summary
Index
Index

Listing the top viewed products

Our web access logs capture the product IDs (the item field in the logs) that users are viewing and adding to their shopping carts. Understanding the top products that people view can help influence our sales and marketing strategy and even product direction. Additionally, products viewed on an e-commerce website might not always necessarily translate into sales of that product.

In this next recipe, we will write a Splunk search to chart the top 10 products that users successfully view and compare against the number of successful shopping cart additions for each product. For example, if a product has a high number of views, but the product is not being added to carts, this could indicate that something is not right—perhaps, the pricing of the product is too high.

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...

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