While Kubernetes has many advantages, it also brings new security challenges that should be considered. Therefore, it is crucial to understand the various security risks that exist in containerized environments, and specifically in Kubernetes.

This post is focused on how to do a full deployment of Pod Security Policies with everything locked down and how to grant exceptions.

When running multiple services and applications on a Kubernetes cluster, a centralized, cluster-level work stack will assist you quickly type through and analyze the serious volume of log knowledge made by your Pods. One well-liked centralized solution is that the Elasticsearch, Fluentd, and Kibana (EFK) stack.

In this article I will show how to self host Azure functions in a Kubernetes cluster.

Consider a Kubernetes cluster with 3 worker nodes having a memory of 10GB each. Suppose the developers end up deploying some pods by mistake which consumes almost all the cpu and memory available in the node. Hence causing resource contention in the others application pods which serves traffic from consumers. This could also be caused when hackers inject high resource consuming pods intentionally into the system.

So you have a Kubernetes cluster and are using (or considering using) the NGINX ingress controller to forward outside traffic to in-cluster services. That’s awesome!