There's no correct answer here. Your choice seems reasonable _if_ you already have some previous familiarity with managing k8s. If not, you might want to consider starting with a managed k8s solution from a cloud provider. The bulk of the work will be containerizing your stack, and getting familiar with all the concepts. You don't want to do all that while also keeping k8s running. After that you would be able to relatively easily migrate to a self-hosted cluster if you need to.
If you do want to self-host, k3s could also be an option, like a sibling comment suggested. It's simpler to start with, though it still has a learning curve since it's a lightweight version of k8s. I reckon that you would still want to run at least 3 nodes for redundancy/failover, and maybe a couple more for just DB workloads. But you can certainly start with one to setup your workflow, and then scale out to more nodes as needed.
If you do want to self-host, k3s could also be an option, like a sibling comment suggested. It's simpler to start with, though it still has a learning curve since it's a lightweight version of k8s. I reckon that you would still want to run at least 3 nodes for redundancy/failover, and maybe a couple more for just DB workloads. But you can certainly start with one to setup your workflow, and then scale out to more nodes as needed.