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An open-source Kubernetes platform for deploying, routing, explaining, and monitoring machine learning models at scale.
DESCRIPTION
Seldon Core provides Kubernetes-native deployment of ML models as microservices, supporting canaries, AB tests, and inference graphs. It integrates with service meshes and supports standardized model server protocols. Built-in explainers, drift detectors, and metrics enable observability and responsible AI practices. The platform scales across clusters and supports multi-language models with custom containers. It is widely used for enterprise-grade model serving and governance.
ALTERNATIVE DEFINITIONS
Seldon Core Docs
Seldon Core is an open-source platform to deploy, scale and manage thousands of machine learning models on Kubernetes.
Emphasizes Kubernetes-native scale and operational management.
Seldon
Seldon Core is a Kubernetes-native MLOps framework for deploying, monitoring, and explaining machine learning models.
Highlights explainability and monitoring features as first-class.
RELATED TERMS
Kubernetes Istio Canary Release A/B Testing Model Monitoring Model Explainers Inference Graphs
COMPETING TERMS
KNOWLEDGE AREAS
MLOps AI Infrastructure Platform & Tooling Data Services
TARGET AUDIENCE
MLOps Engineer DevOps Engineer AI Engineer Cloud Architect Data Engineer
EXTERNAL SOURCES
TOP QUESTIONS
What problems does Seldon Core solve?
It standardizes model serving on Kubernetes with routing, scaling, and monitoring. The statement: it is an MLOps backbone for inference.
Category: Purpose
How does Seldon Core compare to KServe?
Both are K8s-native; Seldon emphasizes inference graphs and built-in explainers, while KServe focuses on standard model server interfaces.
Category: Comparison
Can Seldon Core do canary releases?
Yes, traffic-splitting and routing rules support canaries and A/B tests to de-risk deployments.
Category: Features
How is monitoring handled in Seldon Core?
It exposes metrics, integrates with Prometheus/Grafana, and offers drift detection and explainers.
Category: Operations
What are common mistakes with Seldon Core?
Underprovisioned resources, missing autoscaling configs, and lack of TLS. Proper Kubernetes hygiene is essential.
Category: Mistakes
How does Seldon Core integrate with CI/CD?
Use YAML manifests or Helm charts within pipelines. Declarative configs enable reproducible deployments.
Category: HowTo
Does Seldon Core support multi-model serving?
Yes, through inference graphs and routers that compose multiple models or steps.
Category: Features
What security features are recommended with Seldon Core?
mTLS via service mesh, RBAC, secrets management, and image signing. Security must be layered.
Category: Security
When should I pick Seldon Core over BentoML?
If your org standardizes on Kubernetes and needs rich routing, explainability, and drift detection out of the box.
Category: Advice