Introducing Model URI Support in Seldon's Enterprise Platform - Take Control of ML and AI Complexity
Blog post from Seldon
Seldon has announced significant updates to its technology, enhancing the Seldon Enterprise Platform and Seldon Core v1 and v2, aimed at improving model deployment, error management, and overall user experience in machine learning operations (MLOps). The Seldon Enterprise Platform now offers improved authentication configurability, support for Model URI in the UI, detailed error messages for model deployment failures, and differentiation between users and machines via OIDC configuration. It also introduces configurable resource allocation for batch job pods and UI support for folder-based batch jobs. Seldon Core v1 and v2 have been updated to include optional user ID requirements for Helm chart management, OAuth 2 SASL mechanism for Confluent Kafka, enhanced error handling, and Kafka configurability. Additionally, Seldon Core v2 supports the deployment of HuggingFace models, offering a new runtime for experimentation and efficiency. The platform has also focused on security and usability improvements to tools like Alibi Detect and Alibi Explain, and important bug fixes and dependency upgrades have been implemented across the system to ensure seamless integration with the latest technologies, delivering a robust framework for scalable and efficient MLOps.