[koffiezet]

It's not just "abstracting the server". Kubernetes abstracts more than just "a server", it works on a level higher. It does this for storage, networking, compute, services, workloads, scaling, ... and all this is done through a standardised API. This APIforces you to standardise application deployments, making centrally managed logging, monitoring, tracing, ... a breeze. Once you have it working for one application, it'll work for all of them.

And do you need to run this on Amazon, Gcloud, Azure,one of the smaller cloud providers like DigitalOcean or locally on Kind/k3s? It'll require very little work to get them working on any of these - if any. Cloud specific services and persistent storage will be the main issues, but that's something you can't really get around.

Now is it perfect? Absolutely not, as with any tech, there will always be problems and bottlenecks. But it allows development to scale, not just the workloads, and the skills required are transferable, which makes it a much easier sell.

[freedomben]

I completely agree with everything you said, except:

> Cloud specific services and persistent storage will be the main issues, but that's something you can't really get around.

That isn't wrong necessarily, but products like OpenShift Container Storage (OpenShift Data Foundations now actually) can provide a common API to erase that problem. ODF uses Ceph under the hood so you can get block, file, and (s3 compatible) object storage no matter where you are.

Cloud specific services are indeed a problem, but many of them have open source/portable solutions that you an choose that can run everywhere. Such as Fission, RabbitMQ, Kafka (not my favorite), Argo CD, etc. Really the things I run into most now are things like AWS machine learning services.