KServe

Kubernetes-native model serving with autoscaling and canary deployments.

Maturity level: L3 — Can Deploy

Six perspectives on KServe

Roadmap

Advanced MLOps — after Kubernetes and MLflow.

Architecture

Model serving layer on Kubernetes in enterprise MLOps stacks.

Company

Seen in Kubernetes-heavy MLOps and platform roles.

Projects

Serve models from your MLflow registry via KServe.

Interview

Model serving patterns and autoscaling on K8s.

Career

Senior MLOps and AI infrastructure differentiator.

What & Why

What: Kubernetes CRD-based model serving framework built on Knative.

Why: Standardizes model deployment on K8s with scale-to-zero and traffic splitting.

Build this

Deploy sklearn and ONNX models with KServe on Kubernetes.

Production reality

  • ! Cold start latency
  • ! Knative complexity
  • ! Custom runtime debugging

Interview preparation

  • KServe vs raw Deployment for models
  • Canary deployment strategies

Connected skills

KubernetesDockerMLflow

Explore KServe in the interactive universe or train with live cohorts.

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