Seldon Enterprise Platform

Seldon Enterprise Platform provides oversight and governance for machine learning (ML) deployments.

It is built atop leading open-source tools including Seldon Core and Alibi.

• Deploy ML models easily using industry-leading, open-source projects

• Ensure reproducible deployments and rollbacks with GitOps

• Release models with confidence via canaries and shadows

• Inspect model predictions using Alibi explainers

• Apply advanced monitoring to model inferences

Seldon Core

Seldon Core is a cloud-agnostic, open-source platform for deploying machine learning models.

• Deploy models in the cloud or on-premise

• Create powerful inference graphs

• Unify heterogeneous ML toolkits under one serving layer

See the Seldon Core documentation for further details.

Technology Stack

seldon

Architecture Overview

For further information, please refer to the detailed Architecture pages.

seldon-ecosystem

Alibi

Alibi is an open-source Python toolkit for understanding models. Alibi Detect offers drift and outlier detection, while Alibi Explain provides model inspection and interpretation.

• Provide high quality reference implementations of black-box ML model explanation algorithms

• Define a consistent API for interpretable ML methods

• Support multiple use cases (e.g. tabular, text and image data classification, regression)

• Implement the latest model explanation, concept drift, algorithmic bias detection and other ML model monitoring and interpretation methods

Who is Seldon Enterprise Platform for?

Seldon Enterprise Platform provides benefits for a range of different roles involved in machine learning operations. These span from operational concerns to ML performance to management and compliance.

Data Scientists

Data scientists can benefit from Seldon Enterprise Platform while iteratively developing their models and when these are in production.

They can take advantage of the following features in particular:

• Catalog of model versions, including model metadata

• Model performance monitoring, including drift and outlier detection

• Explanations of model predictions, to understand and improve models

• Traffic mirroring, to safely experiment with new models

Operations

Operational aspects are key to productionising ML pipelines. Seldon Enterprise Platform enables engineers to deploy safely and easily.

The key benefits that Seldon Enterprise Platform offers are:

• GitOps for reliable, reproducible, auditable deployments

• Canary rollouts for mitigating risk, with explicit canary promotion

• Real-time monitoring of metrics including model latency, resource consumption, and error rates

• Management of secrets for model artifacts and image registries

• API and Python SDK for automation of common and complex workflows, such as CI/CD tasks

Managers

Managing your ML estate is no easy task, especially as new model versions are developed and your team's scope increases.

Seldon Enterprise Platform helps managers keep on top of their estates:

• Projects keep groups of related models together

• Namespaces provide strong resource isolation, for example to separate development and production workloads

• Access controls mitigate risk by defining who can do what and where

• Catalog of model versions, including model metadata

Auditors

ML systems are complex and powerful tools that need to be fair and unbiased for many real-world applications. They are often subject to regulatory and compliance checks to ensure this.

Seldon Enterprise Platform assists auditors with the following features:

• Audit logs to know who did what and when

• GitOps for deployments, to ensure the system state is what it's meant to be

• Explanations for model predictions, to understand why a model did what it did and to check for bias

• Access controls, so that only authorized parties are allowed to see sensitive data or make changes