AI Infra Interviews logo
← Kubernetes, Slurm & GPU Scheduling / 26
hardAnyscaleCrusoe

We have GPUs in two clouds. Can we run one training job across both, and what would you do instead?

Calculate traffic across the actual inter-cloud boundary before deciding. Whole-job placement often avoids repeated transfers, but communication volume, overlap, convergence requirements and available links determine whether a split job is viable.

Updated Oct 2026 · Learn how AI infrastructure works through explanations, worked examples and diagrams, then practise applying it to interview questions.

Calculate traffic across the actual inter-cloud boundary before deciding. Whole-job placement often avoids repeated transfers, but communication volume, overlap, convergence requirements and available links determine whether a split job is viable.

The full answer is part of Premium. A free account includes more answers in each topic, but does not unlock this one.

20 answers per topic instead of 10, plus saved progress and bookmarks · no cardor unlock all 316 remaining answers · ₹2,000 / $25
UP NEXT ON YOUR JOURNEY
FEDITOR'S NOTE

State bytes, bandwidth, directions and overlap assumptions. Compare equivalent training work, distinguish optimizer changes from scheduling, and include replication lag and destination capacity in recovery.

DISCUSSION · 0

No comments yet — be the first to share your approach.