GPU autoscaling
Lower idle GPU capacity
Validate GPU-aware, event-driven scaling for inference or fine-tuning while keeping P95 latency predictable.
Target: 30-40% lower GPU spend
The POC focuses on measurable autoscaling outcomes: cost, latency, utilization, and operational effort on a real workload.
GPU autoscaling
Validate GPU-aware, event-driven scaling for inference or fine-tuning while keeping P95 latency predictable.
Target: 30-40% lower GPU spend
Kubernetes autoscaling
Exercise predictive policies that scale Kubernetes clusters dynamically across cloud environments.
Evidence: cost and performance deltas
HTTP/gRPC endpoints
Scale services from request pressure and bursty traffic while preserving latency SLOs.
Evidence: latency and replica behavior
Built-in visibility
Use Prometheus/OTel metrics, long-term storage, dashboards, and readouts to show the impact clearly.
Output: readout and rollout plan