Each week, the Kubernetes community shares an enormous amount of interesting and informative content including articles, blog posts, tutorials, videos, and much more. We’re highlighting just a few of our favorites from the week before. This week we’re talking machine learning, scalability, service mesh, and contributing to Kubernetes.
If you’ve ever wonder what goes into maintaining an open-source project with as much velocity as Kubernetes, this article is a great place to start. Abraham Ingersoll from Gravitational dives into the inner workings of SIGs and working groups, the Kubernetes release cycle, feature development process, and community support.
As the cloud native landscapes evolve, more and more questions come up as to when to use Kubernetes and when to use Serverless to build an application. In this article, Niklas Heidloff from IBM outlines the pros and cons of each option and how to decide what’s best for your use case.
Scheduling in Kubernetes helps ensure that pods are only placed on nodes that have sufficient free resources. In this post, Alexandru Topliceanu from Pusher.com walks you through the implementation of the default scheduler in Kubernetes. Dive into the genericScheduler, volumes, algorithm, predicates, custom scheduler, and more to learn how to support long-running processes.
Autoscaling is one of the most useful features in Kubernetes, but autoscaling based on custom metrics can be complicated to set up since it’s still an alpha feature. In this Medium post, Marko Lukša from Red Hat shows you how to set up horizontal pod autoscaling based on application-provided custom metrics on minikube.
Stay tuned for more exciting content from the Kubernetes community next week, and join the KubeWeekly mailing list for the latest updates delivered directly to your inbox.
Is there a piece of content that you think we should highlight? Tweet at us! We’d love to hear what you’re reading, watching, or listening to.