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9781514615744: Building Splunk Solutions (Second edition): Splunk Developer Guide
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Biographie de l'auteur :
Grigori Melnik is a Principal Product Manager at Splunk focusing on the Developer Platform. Formerly at Microsoft, he produced patterns & practices components and architectural guidance. Prior to that, he was a researcher and developer — long enough ago to remember the joy of programming in Fortran. He is an Associate Editor-in-Chief, IEEE Software magazine & an Adj Professor of Computer Science at the University of Calgary. He speaks around the world on the topics of operational & business intelligence, code reuse, cloud computing, agile methods, and software testing. He holds a PhD in Computer Science from the University of Calgary. Contact him at http://twitter.com/gmelnik

Dominic Betts is a Sr Content Developer at Microsoft and is based in the UK. He has a background in in software development, IT training, and content creation for developers, architects, and IT professionals. Previously, he has co-authored a number of books with the Microsoft patterns & practices team. His current area of interest is IoT.

Matthew Tevenan is a Sr Technical Writer at Splunk. He writes documentation for the Splunk Developer Platform, as well as for DB Connect & other Splunk software. Prior to that, he worked at Microsoft on products such as the Windows Client SDK, Windows Media SDK, and Internet Explorer. Matthew holds a MSc, Tech Communication from the University of Washington & a BA, French from the University of San Francisco.

David Foster is an experienced Splunk developer who has worked on several Splunk apps (Exchange, VMware, Twitter, Flurry) and on the Splunk platform itself (Splunk Web Framework, several SDKs). Beyond Splunk, David has been developing software over 20 years in a wide variety of languages and environments. Currently David is engaged with inspiring the next generation of grade schoolers to write their own computer programs.

Brian Schutz is a Sr Software Developer at Conducive Consulting. He holds a BSc Computer Science from the Texas State University.

Liying Jiang is a Software Engineer in the Splunk Seattle QA team. She has helped to ship Splunk 6 and various Splunk SDKs and apps. Before Splunk, Liying worked at Microsoft for seven years as a member of SQL Server, Office 365 billing & Commerce catalog teams.
Présentation de l'éditeur :
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 iterative development 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.

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