There's a common conversation that goes on around AI: some people swear its a complete waste of time and total boondoggle, some that its a good tool when used correctly, and others that its the future and nothing else matters. I see the same thing happen with Kubernetes. I've run clusters from various sizes for about half a decade now. I've never once had an incident that wasn't caused by the product itself. I recall…
The complaints I see about Kubernetes are typically more about one of two things: (a) this looks complex to learn, and I don't have a need for it - existing deployment patterns solve my use case, or (b) Kubernetes is much less inefficient than running software on bare-metal (energy or cost.) Usually they go hand in hand.
It's up to the individual to choose how much knowledge they want to trade away for convenience. All the containers are just forms of that trade.