
Data-centric MLOps: Seldon Core 2
Deploy machine learning locally with Docker or to a Kubernetes cluster. Scale to 1000s of models. Run data pipelines for models containing outlier and drift detection along with model explainers. Comes with tracing, metrics and a CLI. Supports tensorflow, pytorch, sklearn, ONNX, custom python models and many more ML artifacts. Run experiments to test new models and combine with any Kubernetes service mesh. Create synchronous and asynchronous inference pipelines backed by Kafka.