Building simple automation through Github & Dockerhub Auto build to build containers and then deploy it to GKE through Kubernetes Manifest:

Troubleshoot your Kubernetes application with ease and understand its mechanics

In this post I describe a problem I had running IdentityServer 4 behind an Nginx reverse proxy. In my case, I was running Nginx as an ingress controller for a Kubernetes cluster, but the issue is actually not specific to Kubernetes, or IdentityServer - it's an Nginx configuration issue.

This is aimed at people that just begin exploring Google cloud / Kubernetes, and an attempt to consolidate the week of (sometimes confusing) research

When it comes to infrastructure, Kubernetes and its associated ops discipline ClusterOps are definitely the hottest new tech to burst onto the scene for quite a while.

Recently, someone asked me what the difference between NodePorts, LoadBalancers, and Ingress were. They are all different ways to get external traffic into your cluster, and they all do it in different ways. Let’s take a look at how each of them work, and when you would use each.

If you want to expose any service running inside Kubernetes there are a couple of ways of doing it, a very handy one is to have an Ingress. In this post we are going to explain ingresses, ingress controllers, ingress definitions and the interaction between them.

In previous articles, we’ve been talking about how to use Kubernetes to spin up resources. So far, we’ve been working exclusively on the command line, but there’s an easier and more useful way to do it: creating configuration files using YAML. In this article, we’ll look at how YAML works and use it to define first a Kubernetes Pod, and then a Kubernetes Deployment.

In this article we will be looking at building a simple contacts demo web application using Angular 8 front end and JAVA Spring Boot backend with mangoDB as a storage. We will containerize this app with help of docker and deploy to Google Kubernetes cluster.

Kubernetes is a powerful open-source system, initially developed by Google, for managing containerized applications in a clustered environment. It aims to provide better ways of managing related, distributed components and services across varied infrastructure.