Adrian Gonzalez Sanchez is a Cloud, Data and AI Specialist at Microsoft, as well as the Industrial AI Lead for the Spanish Observatory of Ethical AI (OdiseIA). He has previously worked as a Senior Consultant and Product Owner in AI and data science with CGI Canada and IVADO Labs, Head of AI Customer success for Peritus.ai, and other data-driven companies in Europe and Latin America. He is a trainer for the cole des Dirigeants at HEC Montreal, the Continuing Education Department at Concordia University, and online training courses for O'Reilly Media and the Linux Foundation. He also collaborates with 2U / GetSmarter as a tutor and facilitator for MIT Sloan's AI and Blockchain executive courses, and Harvard VPAL's Fintech course.

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Learn how to prepare for--and pass--the KCNA (Kubernetes and Cloud Native Associate) certification exam. This practical guide serves as both a study guide and point of entry for practitioners looking to explore and adopt cloud native technologies. Adrian Gonzalez Sanchez teaches you not only the core technology fundamentals, but also the community and industry that KCNA serves. With the meteoric rise in cloud adoption, cloud native technologies such as Kubernetes have become the de facto industry standard. Other Kubernetes certifications--CKAD, CKA, and CKS--are all geared towards higher level technical proficiency. The KCNA certification exam covers the cloud native environment generally as well as the fundamental Kubernetes skills and knowledge. This guide helps you learn:

How to best and most efficiently prepare for the KCNA exam
The latest cloud native developments and their importance
The fundamentals of Kubernetes, cloud native development, and related CNCF projects
The core elements of Kubernetes applications
The crucial elements of modern cloud native development
How to differentiate and choose cloud native technologies
The market value of passing the KCNA exam About the author: Adrian Gonzalez Sanchez is a cloud, data and AI specialist at Microsoft, and the Industrial AI Lead for the Spanish Observatory of Ethical AI (OdiseIA).