Splunk Developer S Guide Second Edition

Learn the A to Z of building excellent Splunk applications with the latest techniques using this comprehensive guideAbout This Book• This is the most up-to-date book on Splunk 6.3 for developers• Get ahead of being just a Splunk user and start creating custom Splunk applications as per your needs• Your one-stop-solution to Splunk application developmentWho This Book Is ForThis book is for those who have some familiarity with Splunk and now want to learn how to develop an efficient Splunk application. Previous experience with Splunk, writing searches, and designing basic dashboards is expected.What You Will Learn• Implement a Modular Input and a custom D3 data visualization• Create a directory structure and set view permissions• Create a search view and a dashboard view using advanced XML modules• Enhance your application using eventtypes, tags, and macros• Package a Splunk application using best practices• Publish a Splunk application to the Splunk communityIn DetailSplunk provides a platform that allows you to search data stored on a machine, analyze it, and visualize the analyzed data to make informed decisions. The adoption of Splunk in enterprises is huge, and it has a wide range of customers right from Adobe to Dominos. Using the Splunk platform as a user is one thing, but customizing this platform and creating applications specific to your needs takes more than basic knowledge of the platform.This book will dive into developing Splunk applications that cater to your needs of making sense of data and will let you visualize this data with the help of stunning dashboards.This book includes everything on developing a full-fledged Splunk application right from designing to implementing to publishing. We will design the fundamentals to build a Splunk application and then move on to creating one. During the course of the book, we will cover application data, objects, permissions, and more. After this, we will show you how to enhance the application, including branding, workflows, and enriched data. Views, dashboards, and web frameworks are also covered.This book will showcase everything new in the latest version of Splunk including the latest data models, alert actions, XML forms, various dashboard enhancements, and visualization options (with D3). Finally, we take a look at the latest Splunk cloud applications, advanced integrations, and development as per the latest release.Style and approachThis book is an easy-to-follow guide with lots of tips and tricks to help you master all the concepts necessary to develop and deploy your Splunk applications.

This guide follows a Splunk software engineering team on a journey to build solutions with partners, focusing on the real world use cases to showcase various technologies of the Splunk Developer Platform. Like a documentary, it captures our story from envisioning and user experience prototyping to development, packaging and multiple production deployments. It includes the diverse perspectives of developers and testers, administrators and product owners, security experts and release engineers. As on any real journey, we make mistakes, have arguments, and change our minds along the way. So in addition to showing you how best to do things, we highlight the pitfalls and issues that we encounter, and the solutions we find.The key element of this guidance, of course, is the code. We've made the code repos open, and recommend you study the source code of the reference apps and the associated tests. In fact, you can see and replay the code in motion, as it was developed. We encourage you to reuse and learn from it.The second edition is expanded with 10 new chapters, including 3 new ones in the Journey covering OAuth, alerting and high performance HTTP Event Collector. Additionally we include a new section - the Essentials where we've generalized the lessons learned from this Journey and other development projects into fundamental patterns and practices. We still cover the full spectrum of application development from getting data into Splunk Enterprise to packaging and distributing your app. Each topic combines design and implementation guidelines in a way that supports an iterativedevelopment process. These guidelines cover not only Splunk Enterprise operational and programming concepts that the application deals with directly, but also consider performance, quality, and maintenance issues in recommending particular approaches.

Learn the A to Z of building excellent Splunk applications with the latest techniques using this comprehensive guide About This Book This is the most up-to-date book on Splunk 6.3 for developers Get ahead of being just a Splunk user and start creating custom Splunk applications as per your needs Your one-stop-solution to Splunk application development Who This Book Is For This book is for those who have some familiarity with Splunk and now want to learn how to develop an efficient Splunk application. Previous experience with Splunk, writing searches, and designing basic dashboards is expected. What You Will Learn Implement a Modular Input and a custom D3 data visualization Create a directory structure and set view permissions Create a search view and a dashboard view using advanced XML modules Enhance your application using eventtypes, tags, and macros Package a Splunk application using best practices Publish a Splunk application to the Splunk community In Detail Splunk provides a platform that allows you to search data stored on a machine, analyze it, and visualize the analyzed data to make informed decisions. The adoption of Splunk in enterprises is huge, and it has a wide range of customers right from Adobe to Dominos. Using the Splunk platform as a user is one thing, but customizing this platform and creating applications specific to your needs takes more than basic knowledge of the platform. This book will dive into developing Splunk applications that cater to your needs of making sense of data and will let you visualize this data with the help of stunning dashboards. This book includes everything on developing a full-fledged Splunk application right from designing to implementing to publishing. We will design the fundamentals to build a Splunk application and then move on to creating one. During the course of the book, we will cover application data, objects, permissions, and more. After this, we will show you how to enhance the application, including branding, workflows, and enriched data. Views, dashboards, and web frameworks are also covered. This book will showcase everything new in the latest version of Splunk including the latest data models, alert actions, XML forms, various dashboard enhancements, and visualization options (with D3). Finally, we take a look at the latest Splunk cloud applications, advanced integrations, and development as per the latest release. Style and approach This book is an easy-to-follow guide with lots of tips and tricks to help you master all the concepts necessary to develop and deploy your Splunk applications.

This guide follows a Splunk software engineering team on a journey to build solutions with partners, focusing on the real world use cases to showcase various technologies of the Splunk Developer Platform. Like a documentary, it captures our story from envisioning and user experience prototyping to development, packaging and multiple production deployments. It includes the diverse perspectives of developers and testers, administrators and product owners, security experts and release engineers. As on any real journey, we make mistakes, have arguments, and change our minds along the way. So in addition to showing you how best to do things, we highlight the pitfalls and issues that we encounter, and the solutions we find. The key element of this guidance, of course, is the code. We've made the code repos open, and recommend you study the source code of the reference apps and the associated tests. In fact, you can see and replay the code in motion, as it was developed. We encourage you to reuse and learn from it.

Learn how to architect, implement, and administer a complex Splunk Enterprise environment and extract valuable insights from business data. Key FeaturesUnderstand the various components of Splunk and how they work together to provide a powerful Big Data analytics solution. Collect and index data from a wide variety of common machine data sourcesDesign searches, reports, and dashboard visualizations to provide business data insightsBook Description Splunk is a leading platform and solution for collecting, searching, and extracting value from ever increasing amounts of big data - and big data is eating the world! This book covers all the crucial Splunk topics and gives you the information and examples to get the immediate job done. You will find enough insights to support further research and use Splunk to suit any business environment or situation. Splunk 7.x Quick Start Guide gives you a thorough understanding of how Splunk works. You will learn about all the critical tasks for architecting, implementing, administering, and utilizing Splunk Enterprise to collect, store, retrieve, format, analyze, and visualize machine data. You will find step-by-step examples based on real-world experience and practical use cases that are applicable to all Splunk environments. There is a careful balance between adequate coverage of all the critical topics with short but relevant deep-dives into the configuration options and steps to carry out the day-to-day tasks that matter. By the end of the book, you will be a confident and proficient Splunk architect and administrator. What you will learnDesign and implement a complex Splunk Enterprise solutionConfigure your Splunk environment to get machine data in and indexedBuild searches to get and format data for analysis and visualizationBuild reports, dashboards, and alerts to deliver critical insightsCreate knowledge objects to enhance the value of your dataInstall Splunk apps to provide focused views into key technologiesMonitor, troubleshoot, and manage your Splunk environmentWho this book is for This book is intended for experienced IT personnel who are just getting started working with Splunk and want to quickly become proficient with its usage. Data analysts who need to leverage Splunk to extract critical business insights from application logs and other machine data sources will also benefit from this book.

This guide follows a Splunk software engineering team on a journey to build solutions with partners, focusing on the real world use cases to showcase various technologies of the Splunk Developer Platform. Like a documentary, it captures our story from envisioning and user experience prototyping to development, packaging and multiple production deployments. It includes the diverse perspectives of developers and testers, administrators and product owners, security experts and release engineers. As on any real journey, we make mistakes, have arguments, and change our minds along the way. So in addition to showing you how best to do things, we highlight the pitfalls and issues that we encounter, and the solutions we find.The key element of this guidance, of course, is the code. We've made the code repos open, and recommend you study the source code of the reference apps and the associated tests. In fact, you can see and replay the code in motion, as it was developed. We encourage you to reuse and learn from it.

Explore architectural approaches to building Data Lakes that ingest, index, manage, and analyze massive amounts of data using Big Data technologies About This Book Comprehend the intricacies of architecting a Data Lake and build a data strategy around your current data architecture Efficiently manage vast amounts of data and deliver it to multiple applications and systems with a high degree of performance and scalability Packed with industry best practices and use-case scenarios to get you up-and-running Who This Book Is For This book is for architects and senior managers who are responsible for building a strategy around their current data architecture, helping them identify the need for a Data Lake implementation in an enterprise context. The reader will need a good knowledge of master data management and information lifecycle management, and experience of Big Data technologies. What You Will Learn Identify the need for a Data Lake in your enterprise context and learn to architect a Data Lake Learn to build various tiers of a Data Lake, such as data intake, management, consumption, and governance, with a focus on practical implementation scenarios Find out the key considerations to be taken into account while building each tier of the Data Lake Understand Hadoop-oriented data transfer mechanism to ingest data in batch, micro-batch, and real-time modes Explore various data integration needs and learn how to perform data enrichment and data transformations using Big Data technologies Enable data discovery on the Data Lake to allow users to discover the data Discover how data is packaged and provisioned for consumption Comprehend the importance of including data governance disciplines while building a Data Lake In Detail A Data Lake is a highly scalable platform for storing huge volumes of multistructured data from disparate sources with centralized data management services. This book explores the potential of Data Lakes and explores architectural approaches to building data lakes that ingest, index, manage, and analyze massive amounts of data using batch and real-time processing frameworks. It guides you on how to go about building a Data Lake that is managed by Hadoop and accessed as required by other Big Data applications. This book will guide readers (using best practices) in developing Data Lake's capabilities. It will focus on architect data governance, security, data quality, data lineage tracking, metadata management, and semantic data tagging. By the end of this book, you will have a good understanding of building a Data Lake for Big Data. Style and approach Data Lake Development with Big Data provides architectural approaches to building a Data Lake. It follows a use case-based approach where practical implementation scenarios of each key component are explained. It also helps you understand how these use cases are implemented in a Data Lake. The chapters are organized in a way that mimics the sequential data flow evidenced in a Data Lake.