Seldon Core
Kubernetes-native open-source platform for deploying, scaling, and monitoring ML models in production.
Seldon Core deploys ML models as Kubernetes microservices with native A/B testing, canary deployments, and explainability.
Explanation
Seldon Core uses Kubernetes custom resources (SeldonDeployment) to deploy ML models as microservices. It natively supports A/B testing, canary deployments, explainability, and multi-armed bandits.
Marketing Relevance
Seldon Core is ideal for Kubernetes-centric enterprises with complex ML deployment requirements.
Common Pitfalls
Requires Kubernetes expertise. Complex CRD configuration. Overhead for simple deployments.
Origin & History
Seldon Technologies was founded in London in 2014. Seldon Core was released as an open-source project in 2018 and became the standard for Kubernetes-based ML serving. Seldon Deploy offers enterprise features.
Comparisons & Differences
Seldon Core vs. KServe
KServe (formerly KFServing) is more lightweight and Kubeflow-integrated; Seldon Core offers more enterprise features like explainability and MAB.
Seldon Core vs. BentoML
BentoML focuses on developer experience and packaging; Seldon Core on Kubernetes-native governance and monitoring.