Model Serving on Kubernetes

Production ML model serving with KServe and Triton — canary deployments, autoscaling, and GPU-aware scheduling.

When to Use This Skill

Use this skill when:

• Serving scikit-learn, PyTorch, TensorFlow, or ONNX models at scale
• Implementing canary deployments and A/B testing for ML models
• Autoscaling inference pods based on request rate or GPU metrics
• Deploying LLMs with Triton or KServe on Kubernetes
• Managing multiple model versions with traffic splitting

Prerequisites

• Kubernetes 1.28+ with GPU nodes
• KServe installed (or Triton standalone)
• kubectl and helm configured
• NVIDIA GPU Operator installed on cluster