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Comment by deivid | Hacker News Reader

I've not yet gone down that path, in which other ways does your workload need to adapt? I understand that you may want to get more value out of logs, and include side-cars, you may want inter-pod encryption and include service meshes, etc; but that'd be something that requires extra complexity in any setup

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OIDC integration, RBAC, data persistence/replication across nodes, observability, mTLS.

And yes, you're right, all these things are complex in any situation, except when you simply use a load balancer and two servers. There are companies estimated to be worth close to US$2B using with sub 30 servers using a service you may have heard of: Stack Overflow (https://nickcraver.com/blog/2016/03/29/stack-overflow-the-ha... && https://nickcraver.com/blog/2016/05/03/stack-overflow-how-we...).

(As an aside: K8s does not free you from your Cloud vendor - after floating around my city working on various "platforms", all locked in due to IAM, for example.)

None of those things are specific to Kubernetes, though. If anything it's a great forcing function to do the things you aught to for non-k8s deployments. It's far easier to write, say, a systems unit for a service that is properly configurable, has health checks, etc.

> And yes, you're right, all these things are complex in any situation, except when you simply use a load balancer and two servers.

How does that simplify or solve any of the problems you mention? As far as I can see they're just as present and just as complex when you have two servers as when you have hundreds.

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