DISCLAIMER: I work for Red Hat Consulting as an OpenShift/k8s consultant.
This is such a bad idea. And I get that they're point is to reduce latency. But the point of k8s is describe your workload accurately and allow it to make decisions on your behalf. The no-brainer way fix this is to set the CPU Requests and Limits to the same value and add an HPA. Setting CPU Requests and Limits to the same value usually gives people the behavior they're expecting. Having more pods in can also reduce latency. But, taking away the Limits hides information about the workload while working around the issue at low to medium workloads. If they were ever to get Black Friday or other 2.5x workload peaks, I'd worry that the Limits removal would cause k8s not to be able to schedule the workload appropriately even if they had enough resources on paper. Remember, the idea of k8s is to scale atomically and horizontally while ensuring availability. If you're making something vertically scale, you'd likely want to re-evaluate that workload.
This is such a bad idea. And I get that they're point is to reduce latency. But the point of k8s is describe your workload accurately and allow it to make decisions on your behalf. The no-brainer way fix this is to set the CPU Requests and Limits to the same value and add an HPA. Setting CPU Requests and Limits to the same value usually gives people the behavior they're expecting. Having more pods in can also reduce latency. But, taking away the Limits hides information about the workload while working around the issue at low to medium workloads. If they were ever to get Black Friday or other 2.5x workload peaks, I'd worry that the Limits removal would cause k8s not to be able to schedule the workload appropriately even if they had enough resources on paper. Remember, the idea of k8s is to scale atomically and horizontally while ensuring availability. If you're making something vertically scale, you'd likely want to re-evaluate that workload.