Advanced

Serverless GPU Platforms

A serverless GPU platform hides allocation and startup from its users. The design balances cold-start latency, tenant isolation and the cost of idle capacity.

This concept is part of Premium, which includes all concepts, course lessons and answers.

Get Premium · ₹2,000 / $256 months of access · one payment · no auto-renew

RELATED CONCEPTS

Containers, Images and GPU Cold Starts Inference Autoscaling and Cold Starts Multi-Tenancy, Quotas and Fair Share MIG, MPS and Time-Slicing Capacity and Backpressure Inference Platform Architecture

PRACTICE THIS IN REAL QUESTIONS

AI Infrastructure System DesignDesign a serverless GPU platform: a customer deploys a function with a model and pays per second. Where does the cold start budget go?→Kubernetes, Slurm & GPU SchedulingDesign a serverless GPU platform where a function that loads a 7B model cold-starts in under a second. Where does every second go today?→Kubernetes, Slurm & GPU SchedulingRun untrusted user code at 50,000 concurrent sessions, some on GPUs. Pick the isolation boundary and defend the density you lose.→LLM Inference & ServingA new replica has to load a 70B model and serve traffic in under a minute. Where do the seconds go, and how do you get there?→AI Infrastructure System DesignDesign autoscaling for an LLM service whose traffic triples within a minute. What signal, what cold-start budget, what warm pool?→Hardware, Cabling & Cluster Build-OutDesign the physical layer for a multi-tenant GPU cloud. What changes versus a single-tenant cluster?→