Kubernetes 1.36: Breaking Free from Container-Level Resource Constraints

The Real Cost of One-Size-Fits-All Resource Allocation You're running a machine learning training job in Kubernetes. Your main container needs exclusive CPU cores, NUMA alignment, and guaranteed memory—every microsecond counts. But your pod also runs three sidecars: a Prometheus exporter using 50m CPU, a log shipper, and a service mesh proxy. Before Kubernetes 1.36, you had two painful options: Allocate exclusive CPUs to every container , wasting resources on lightweight sidecars Give up on Guar