Latency Mitigation in Multi-Tenant Environments
Balancing Concurrency and Response Time
In a multi-tenant Inference As A Service environment, the primary challenge is the "noisy neighbor" effect, where high-demand users consume shared GPU or TPU resources, causing latency spikes for others. Mitigation strategies focus on spatial and temporal sharing.
Spatial sharing involves partitioning the hardware’s compute units so that multiple tenants run concurrently on different sections of the same chip. Temporal sharing uses high-frequency context switching to interleave requests.
To maintain sub-second response times, IaaS providers implement advanced request queuing and priority scheduling. Techniques like "continuous batching" allow the system to insert new requests into the processing pipeline as soon as a previous request completes a single iteration, rather than waiting for an entire batch to finish. This ensures that the hardware remains at peak utilization while individual users experience consistent, low-latency performance regardless of total system load.