tldr - powered by Generative AI

• Notebooks attached to GPUs waste expensive resources when idle
• Real-time applications like chat box, vision product search, and product recommendation require latency-sensitive and business-critical solutions
• Kubernetes allows fractional utilization of CPUs but not GPUs, leading to inefficient allocation
• Time sharing allows multiple containers to run on a single GPU by allocating time slices fairly to all containers
• Multi-instance GPU allows multiple containers to share a single GPU by creating multiple virtual GPUs
• Both solutions address most use cases and workload needs
• The solution is fully managed by GKE and can be configured through API calls or UI/UX