SeldonIO/seldon-core

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

4778 stars · 867 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Seldon Core 2 is an MLOps and LLMOps framework for deploying, managing, and scaling machine learning models and modular AI applications on Kubernetes. It provides pipelines with Kafka-based streaming, autoscaling, multi-model serving, and experiment routing for A/B tests and shadow deployments.

Use cases

• deploy machine learning models to production on kubernetes
• serve thousands of models with shared inference servers
• run A/B tests and shadow deployments between model versions
• build composable real-time AI pipelines with kafka
• autoscale model inference based on custom metrics
• deploy and serve LLMs in production
• detect drift and outliers on production models

When to choose

• you need production-grade model serving on kubernetes at scale
• you want to consolidate many models on shared infrastructure to cut costs
• you need pipeline orchestration with realtime streaming between ML components
• you require A/B testing, shadow deployments, or experiment routing for models

When to avoid

• you deploy only a handful of models without kubernetes
• you need a fully permissive open-source license since it uses the Business Source License
• you want a simple serverless inference endpoint without cluster operations
• your team has no kubernetes expertise

Facets

framework · maturity active

machine-learning deployment monitoring streaming llm-inference microservices container-orchestration machine-learning large-language-models artificial-intelligence cloud self-hosted go mlops model-serving llmops inference autoscaling ab-testing kafka multi-model-serving kubernetes devops docker

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markdown · JSON · MCP: product_card(name="SeldonIO/seldon-core")