A municipal AI inference cluster needs fabric congestion visibility per queue. Which telemetry focus best matches that requirement?
Select an answer to reveal the explanation.
Short Explanation
AI east-west bursts pile up in switch queues like cars at a too-short on-ramp. Per-queue congestion telemetry shows which ramps are jammed before jobs time out. Empty RU placeholders and lunch lines will not explain fabric drops.
Full Explanation
Modern DC fabrics serving AI/RDMA-style loads benefit from queue-depth and congestion telemetry on interfaces so operators can see buffer pressure and hot spots. That visibility is distinct from facilities housekeeping metrics or unrelated human workflows. Disabling queue counters removes the very signal the use case needs.