Running Databases on Kubernetes

1

KubeDB

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2

StackGres

The key for me is the level of automation that you can reach at a reasonable "development cost". Let me elaborate. K8s, if anything, is an API. An API that allows you to interact with compute, storage and networks in a way that is abstracted from the actual underlying infrastructure. This is incredibly powerful. You can, essentially, code and automate all your infrastructure. But this goes beyond deployment, something you could achieve (more or less) with tools like Terraform or Pulumi. Enter "Day 2 operations". Day 2 operations are essential for any database. And cloud services have done a good job at automating them. Speaking of Postgres, my daily job, things like HA, backups but also minor and major version upgrades are table stakes day 2 operations. If you want to build these day 2 operations in the cloud (say on VMs), even though you have APIs do to so, a) they don't implement a pattern like Kubernete's reconciliation cycle; and b) you have a distinct API per cloud. K8s solves both problems, making it way "cheaper" to build such an automation. On K8s, a given operator can code these day 2 operations against K8s APIs. Therefore, if you want to build such automation, either you are a cloud provider (and potentially do this only for your own cloud) or you do it on Kubernetes. This is so much true, that existing operators have already gone beyond what DBaaS do. Speaking of StackGres [0] (disclaimer: founder), we have implemented day 2 operations (other than the "table stakes" ones that I mentioned before) that no other DBaaS offers as of today, such as vacuums, repacks and even benchmarks (and more day 2 operations will be developed). See [1] for the CRD specs of SGDbOps, our "Day 2 operations" if you are interested. [0] https://stackgres.io.

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