| Sumario: | 5+ Hours of Video Instruction As all companies become software companies, the reliability of software becomes an integral part of a business’ success. Continuous testing is critical for delivering robust software and increasing reliability and confidence when software is released. Without constant validation, failure is imminent. Continuous integration allows developers to automate the debugging of new code as it is integrated and identify problems early in the release process. Jenkins is a widely used CI/CD platform, but the lack of a thorough understanding of best practices and scalability is pervasive. It is easy to install Jenkins, but it is difficult to get it right. This course walks you through industry standard best practices to deploy and maintain continuous testing with Jenkins. In this course, you learn how to deploy and configure a Jenkins instance with a real-world use case scenario. Description Cloud technology advancement has changed the face of the tech world, with more emphasis on continuous integration and delivery. Learn how to deploy, configure, and take advantage of Jenkins for Continuous Integration and Continuous Delivery (CI/CD) and pipeline-like workflows. This LiveLesson walks you through the industry standard best practices of deploying Jenkins in a continuous testing environment. Learn to create fully functional Jenkins servers based on Infrastructure as Code (IaC) as well as deploy Jenkins in both AWS and Google Cloud. Learn the advanced features of Jenkins, including the Jenkins Job Builder. Finally, learn several real-world Jenkins deployment case studies. The associated code can be accessed at: https://github.com/alfredodeza/static and https://github.com/alfredodeza/pipeline-jobs About the Instructor Noah Gift is a lecturer at UC Davis Graduate School of Management MSBA program, the Graduate Data Science program, MSDS, at Northwestern, the Data Science program at UC Berkeley, and the USF Health Informatics program. He is teaching and designing graduate Machine Learning, AI, Data Science courses, and consulting on Machine Learning and Cloud Architecture for students and faculty. These responsibilities include leading a multi-cloud certification initiative for students. Noah is also a Python Software Foundation Fellow, AWS Subject Matter Expert (SME) on Machine Learning, AWS Certified Solutions Architect and AWS Academy Accredited Instructor, Google Certified Professional Cloud Architect, and Microsoft MT...
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