kubernetes

See the GPU-instance and compute-instance boundaries, budget a small slice, and distinguish memory capacity controls from bandwidth isolation.

Walk a single-GPU vLLM Deployment from pod scheduling to the first token, then show the three settings that turn a working manifest into restart loops and stuck rollouts.

Follow a four-GPU request from advertised capacity to concrete devices, and see why free GPUs across nodes cannot satisfy one pod.

Compare the resource promises of MIG, time-slicing and MPS, then test peak memory and simultaneous demand before packing workloads.

Choose the control plane from job admission, placement, recovery and service needs, with a concrete partial-allocation failure.

See how partial allocation can strand two training jobs. Separate group admission, real placement, readiness and recovery instead of assuming atomic pod startup.

Design fractional GPU admission around explicit shapes and enforceable guarantees, then reconcile reservations with the runtime.

Diagnose GPU pod failures by scheduling, container startup and execution boundaries, without treating Allocatable as a health certificate.

Separate discovery labels, GPU resource advertisement and validation, and understand the operator as a reconciler with configurable components.

Trace Kubernetes pod placement and Ray bundle reservation as separate layers, including logical GPU limits and autoscaling delay.

DRA gives the scheduler device claims and attributes to work with. Compare that with extended-resource counts, then check the deployed driver and controller support before promising sharing, partitioning or gang placement.

Make readiness mean that the engine can serve, scale from measured demand and ready capacity, and drain streams before termination. Kubernetes can implement these controls; an operator packages and reconciles them.

A fabric address, an RDMA device and a working GPU-memory registration path are separate requirements. Verify each inside the pod, then test the actual GPU-to-NIC placement and collective behavior.