November 2024 Summaries

Baseten introduces custom environments for ML model deployments, allowing developers to create production-ready environments with auto-scaling settings and persistent endpoints. Custom environments enable seamless rollback to previous model versions and streamlined model promotions between testing, staging, and production stages. This feature enhances the reliability of models in production, speeds up development cycles, and ensures a smooth promotion flow. Baseten's custom environments stand out for their developer-first experience and setting new standards for ML deployment workflows.

Baseten introduces canary deployments, allowing developers to gradually shift traffic to a new deployment over customizable time windows with seamless rollback if issues arise. This feature minimizes risk by initially exposing only a small subset of users to the new deployment, which gradually increases over time. Canary deployments are designed to help engineers move swiftly from testing to deployment, ensuring more stability and a delightful developer experience.