Kubernetes has become something of the standard for the orchestration of containers. While there are certainly other options, the Kubernetes platform remains the most prevalent. With that in mind, I decided to migrate my home lab from docker servers to Kubernetes clusters.
Before: Docker Servers
Long story short: my home lab has transitioned from Windows servers running IIS to a mix of Linux and Windows containers to Linux only containers. The apps are containerized, but the DBs still run on some SQL servers.
Build and deployment is automated: Build through Azure DevOps Pipelines & Self Hosted Agents (Teamcity before that), and deployment through Octopus Deploy. Container images for my projects live on a Proget server feed.
The Plan
“Consolidate” (and I’ll tell you later why that is in quotes) my servers into Kubernetes Clusters. It seemed an easy plan.
- Internal K8 Cluster – Runs Rancher and any internal tooling (including Elastic/Kibana) I want to be there, but not available externally
- Non Production K8 Cluster – Runs my *.net and *.org sites, used for test and staging environments
- Production K8 Cluster – Runs my *.com sites (external) including any external tooling.
I spent some time learning Packer to provision Hyper-V vms for my clusters. The clusters all ended up with a control plane (4vCPU, 8GB RAM) and two workers (2vCPU, 6GB RAM).
The Results
The Kubernetes Clusters
There was a LOT of trial and error in getting Kubernetes going, particularly with Rancher. So much, in fact, that I probably provisioned the clusters 3 or 4 times each because I felt like I messed up and wanted to do it over again.
Initially, I tried to manually provision the K8 cluster. Yes, it worked.. but RKE is nicer. And, after my manually provisioned K8 cluster went down, I provisioned the internal cluster with RKE. That makes updates easier, as I have the config file.
I provisioned the non-production and production clusters using the Rancher GUI. However, that was the “manually provisioned” cluster, so, when it went down, I lost the config files. I currently have two clusters which look like “imported” clusters in Rancher, so they are harder to manage through the Rancher GUI.
Storage
In order to utilize persistent volume claims, I configured NFS on my Synology and installed the nfs-subdir-external-provisioner in all of my clusters. It installs a storage class which can be used in persistent volume claims, and will provision directories in my NFS.
Ingress
Right now, I’m using the Nginx Ingress controller from Rancher. I haven’t played with it much, other than the basics. Perhaps more on that when I dig in.
Current Impressions
Rancher
It works… but mine is flaky. I think it may be due to some resource starvation. I may try to provision a new internal cluster with better VMs and see how that works.
I do like the deployment of clusters using RKE, however, I can see how it would be difficult to manage when there is more than one person involved.
Kubernetes
Once it was running, it’s great: creating new APIs or apps and getting them running in a scalable fashion is easy. Helm charts make deployment and updating a snap.
That said, I would not trust myself to run this in production without a LOT more training.
References
- Rancher Kubernetes Engine Installation
- nfs-subdir-external-provisioner – Storage class for Persistent Volume Claims on an NFS drive
- Helm Docs – General documentation for Helm
- Octopus Helm Chart – Used to deploy my internal Octopus application.
Comments
One response to “Moving the home lab to Kubernetes”
This toolchain looks familiar 😉