Audience
Who should use Seldon deploy?
Seldon Deploy provides oversight and governance for machine learning deployments.
Easily deploy your models in an audited way with gitops. Leverage advanced monitoring and perform alibi-powered explanations on requests.
Seldon Deploy is an enterprise product to accelerate deployment management on top of the open source tools Seldon Core, KFServing and Seldon Alibi.
Seldon Core is an open source platform for deploying machine learning models on a Kubernetes cluster.
Seldon Core fits into the stack alongside Seldon Deploy and your existing training pipelines as shown below:
See the Seldon Core documentation for further details.
KFServing provides a Kubernetes Custom Resource Definition for serving machine learning (ML) models on arbitrary frameworks. It aims to solve production model serving use cases by providing performant, high abstraction interfaces for common ML frameworks like Tensorflow, XGBoost, ScikitLearn, PyTorch, and ONNX.
It encapsulates the complexity of autoscaling, networking, health checking, and server configuration to bring cutting edge serving features like GPU Autoscaling, Scale to Zero, and Canary Rollouts to your ML deployments. It enables a simple, pluggable, and complete story for Production ML Serving including prediction, pre-processing, post-processing and explainability.
Alibi is an open source Python library aimed at machine learning model inspection and interpretation. The initial focus on the library is on black-box, instance based model explanations.
Its goals are:
Who should use Seldon deploy?
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