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KServe

Free

Kubernetes-native serverless model serving platform.

Open SourceAPISelf-hostedEnterprisePython SDK

Tool Info

Categories
Deployment · Serving
Official Website
kserve.github.io/website
Repository
kserve/kserve
Official Docs

Overview

KServe provides serverless model inference on Kubernetes.

Supports TensorFlow, PyTorch, XGBoost, and custom predictors.

Pricing

Free tier available
Free (open source)

Pros

  • K8s-native
  • CNCF project
  • Canary deployments

Best For

K8s model servingServerless inferenceMulti-framework deployment

When NOT to Use

  • Requires Kubernetes
  • Steep ops learning curve

Related Tools

BentoML
Unified framework for packaging and deploying ML models as APIs.
Modal
Serverless cloud platform for running ML models and data pipelines.
RunPod
GPU cloud for running AI workloads with serverless and pod options.

Alternatives

Ray Serve
Scalable model serving library built on the Ray distributed framework.
BentoML
Unified framework for packaging and deploying ML models as APIs.

Often Compared With

Ray Serve
Scalable model serving library built on the Ray distributed framework.
BentoML
Unified framework for packaging and deploying ML models as APIs.

Compare With

Compare with Ray ServeCompare with BentoML

Tags

#kubernetes#serving#serverless

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