Data Science Platform (Managed)

Managed data science on Kubernetes: MLflow tracking, model registry, managed feature store, KServe/Seldon inference, model CI/CD, GPU scheduling. Batch + real-time inference.

• MLflow experiment tracking + model registry
• Managed feature store (Feast) auto-provisioned
• KServe/Seldon batch + real-time inference
• Model CI/CD per training run + gate before prod
• GPU scheduling per experiment, no queue

• Ship ML models in days not weeks
• Track every experiment without losing results
• Feature store serves sub-10ms at 10k QPS
• Model versioning + canary rollout, no manual deploy