Kube by Example expands training curriculum with new learning paths for Kubernetes developers

We see Kubernetes as the foundation for hybrid cloud, and hybrid cloud as the future of IT. The technology remains among both the most loved and most wanted tools in this year’s Stack Overflow Developer survey. Given its prevalence and strategic importance, we have also seen developers seeking out and engaging with Kubernetes-focused training resources like Kube by Example, an online destination for free Kubernetes-focused tutorials, news and community interaction.

As the company behind the industry’s leading enterprise Kubernetes platform, Red Hat has backed Kube by Example and is diligently working to establish it as the premier destination for developers and operators to sharpen their Kubernetes skills in a hands-on environment.

Since announcing our support for Kube by Example earlier this year, the team has been working hard to expand the curriculum, enhance the learning experience, and engage even more IT professionals as they learn this critical technology. Today, we are pleased to share progress toward that goal.

Two new learning paths are available today, with a third coming soon:

• Operators with Helm, Ansible and Go: This learning path illustrates how technologies like Helm and Operators can be used to simplify the process of packaging, deploying and running containerized applications on Kubernetes, and then taking advantage of powerful capabilities in Ansible to automate them. This path also introduces learners to the Go programming language underlying many of the Operator framework and Helm chart subsystems.
• Migrating to Kubernetes: Learners will discover various tools in Konveyor, an open source tool used to modernize and migrate applications for open hybrid cloud environments, and the techniques that can accelerate rehosting, replatforming, and refactoring applications to Kubernetes.
• AI and Machine Learning on Kubernetes: For the past several years, data science has been one of the most sought-after jobs in the U.S. as organizations have increasingly looked to harness data analysis tools and capabilities like artificial intelligence and machine learning (AI/ML) to drive business decisions. This learning path explores different ways Jupyter Notebooks can be used alongside other services available on Kubernetes to build interactive computational environments that help solve common problems in the AI/ML space. (Coming soon!)

In addition to the new learning paths, we are improving the overall functionality of Kube by Example by adding new features aimed at giving learners a greater ability to engage more deeply with the community curriculum instructors. For instance, we are in the process of enhancing the search capabilities and course tagging to make it easier to find individual courses; adding course ratings to give learners the ability to share feedback on the full breadth of Kube by Example training; and we are introducing a new blog and community hub where learners can ask questions and begin to interact with one another.

We’re pleased to invest in Kube by Example to make it a more valuable source of information and inspiration for the community of developers involved in Kubernetes. Check out the new learning paths, and as always, we welcome you to share questions, feedback and ideas!