Since my first tentative steps in to Kubernetes it’s been an interesting journey. For the most part I suspect the most common way to interact with Kubernetes is to use a managed platform through one of the main public cloud players (that’s certainly been my experience), but it doesn’t do a lot to understand the nuts and bolts of the platform. I’d been meaning to try and get stuck in . . .
If, like me, you’ve come from a traditional sysadmin background then Kubernetes can be daunting to say the least, this doesn’t get much easier when it comes to trying to get to grips with how to debug networking issues. Kubernetes networking is VAST and supports a number of complex implementations that vary between the major Kubernetes-as-a-Service platforms (GKE, EKS, AKS) as well as many other options. The broad strokes are . . .
In the last post we looked at how to automate the creation of GKE Kubernetes clusters in GCP, however the deployment of workloads to these clusters was still something of a manual process. Enter Helm; a package manager for Kubernetes which allows us to use declarative configuration to push our cluster and container definitions from external repositories. If you’ve never heard of it, I recommend the IBM Cloud video here . . .
Google Cloud Platform tends to be forgotten from the conversation a lot when talking about public cloud offerings, however their hosted Kubernetes offering GKE (Google Kubernetes Engine) has for me been the best of the major offerings for getting to grips with the platform and the best reason to use GCP at all. Without much issue we can get Terraform integrated with GCP, provision and scale out clusters as we . . .