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Agree with this on all points.

We went from a virtualized server model to managed Kubernetes and costs have escalated considerably. The additional complexity and maintenance overheads of Kubernetes are not trivial and required additional staff hires just to keep things ticking. I think the cost so far from moving from two cages in separate datacentres running blades to AWS is approximately a 6x multiplier including staff. This was all driven on the back of "we must have microservices to scale", something we have failed entirely to do. It's a complete own goal.



I think it mainly works for startups which can build it as a greenfield and are extremely sensitive to scaling (either they are exploding within 2 years or they're dead within 2 years). So they plan to scale from 0 to millions quickly. For that kinda business it makes sense because once the exploding growth comes it's super easy to scale up and even do that automatically. That's the power of Kubernetes.

For an existing business not in a hyper-growth phase with lots of restrictions and policies and processes and legacy stuff it's just extra work with no gain. It's just a round peg in a square hole. Wrong tool for the job.


That's because you've moved to AWS which is an expensive cloud.

You could have easily run Kubernetes on your virtualised servers.


IME nothing easy about maintaining your own storage cluster!


Nothing easy in general about running a distributed platform for highly-available applications.


True but compute nodes are basically stateless in comparison to anything storage.


Define easily?


Still requires SRE but alot easier than it used to be: https://www.talos.dev/v1.8/

Also, k3s. https://k3s.io/




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