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
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.Style and approach
Splunk is an excellent platform that allows you to make sense of machine data with ease. The adoption of Splunk has been huge and everyone who has gone beyond installing Splunk wants to know how to make most of it. This book will not only teach you how to use Splunk in real-world scenarios to get business insights, but will also get existing Splunk users up to date with the latest Splunk 6.3 release.
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.
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.
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.
Splunk is an extremely powerful tool for searching, exploring, and visualizing data of all types. Splunk is becoming increasingly popular, as more and more businesses, both large and small, discover its ease and usefulness. Analysts, managers, students, and others can quickly learn how to use the data from their systems, networks, web traffic, and social media to make attractive and informative reports. This course will teach everything right from installing and configuring Splunk.
The first module is for anyone who wants to manage data with Splunk. You'll start with very basics of Splunk— installing Splunk— before then moving on to searching machine data with Splunk. You will gather data from different sources, isolate them by indexes, classify them into source types, and tag them with the essential fields.
With more than 70 recipes on hand in the second module 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.
Dive deep into Splunk to find the most efficient solution to your data problems in the third module. Create the robust Splunk solutions you need to make informed decisions in big data machine analytics. From visualizations to enterprise integration, this well-organized high level guide has everything you need for Splunk mastery.
This learning path combines some of the best that Packt has to offer into one complete, curated package. It includes content from the following Packt products:Splunk Essentials - Second EditionSplunk Operational Intelligence Cookbook - Second EditionAdvanced SplunkStyle and approach
Packed with several step by step tutorials and a wide range of techniques to take advantage of Splunk and its wide range of capabilities to deliver operational intelligence within your enterpise
In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.Peer under the hood of the systems you already use, and learn how to use and operate them more effectivelyMake informed decisions by identifying the strengths and weaknesses of different toolsNavigate the trade-offs around consistency, scalability, fault tolerance, and complexityUnderstand the distributed systems research upon which modern databases are builtPeek behind the scenes of major online services, and learn from their architectures
Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.Use the IPython shell and Jupyter notebook for exploratory computingLearn basic and advanced features in NumPy (Numerical Python)Get started with data analysis tools in the pandas libraryUse flexible tools to load, clean, transform, merge, and reshape dataCreate informative visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsAnalyze and manipulate regular and irregular time series dataLearn how to solve real-world data analysis problems with thorough, detailed examples
If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out.Get a crash course in PythonLearn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data scienceCollect, explore, clean, munge, and manipulate dataDive into the fundamentals of machine learningImplement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clusteringExplore recommender systems, natural language processing, network analysis, MapReduce, and databases