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.
First Beta Version of Kubernetes 1.10 is Here – Your Chance to Provide Feedback, Kubernetes.io
The Kubernetes community has been hard at work on the first beta version on Kubernetes 1.10. The March release is targeting over a dozen new alpha features, and over two dozen mature features including production-ready versions of Kubelet TLS Bootstrapping, API aggregation, and more detailed storage metrics. Nick Chase of Mirantis put together this sneak peek of what’s included in 1.10, and how you can provide your feedback during beta testing.
On Securing the Kubernetes Dashboard, Heptio
Recently, Tesla’s Kubernetes infrastructure was compromised and used by attackers to mine cryptocurrency. Tesla’s Kubernetes dashboard was exposed with to the internet, including visible AWS API keys and secrets. In this post, Joe Beda of Heptio explains how to secure your Kubernetes Dashboard to prevent this from happening including RBAC configurations, per-user credentials, and a full tutorial on screening with oauth2_proxy.
How to know if Kubernetes is right for your SaaS, freeCodeCamp
Kubernetes is a great tool to scale, deploy, and manage SaaS applications. But it’s important to know if and when Kubernetes is a good fit for your current situation before investing the time and resources. If you’re currently deciding whether or not to adopt Kubernetes, check out this overview by Ben Sears of ServiceBot.io. Walk through what you should know about the benefits of containers, if Kubernetes will solve your current problems, and if it fits into your future plans for your application architecture.
Ensure High Availability and Uptime With Kubernetes Horizontal Pod Autoscaler and Prometheus, Weaveworks
Autoscaling in Kubernetes allows you to automatically scale workloads up or down based on resource usage. In this post, Stefan Prodan of Weaveworks explains how to use Cluster Autoscaling and the Horizontal Pod Autoscaler (HPA) to optimize for availability and uptime, including how to set up Prometheus to expose the right metrics for autoscaling.
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.