February release overview

As we continue to iterate on our core capabilities, we are pleased to announce the following product improvements in our February 2022 product release:

• Advanced observability:
  • Model prediction assays. Data Scientists can now create and manage validation checks that allow monitoring their ML model predictions and proactively identify data drifts.
• Self-Service toolkit for ML Model deployment:
  • Role-Based-Access-Control groups. This new security feature allows Data Scientists to manage access to ML model artifacts they own. Model artifacts can be private, public, or shared with a particular group of users.
  • Artifact management. As part of allowing users to easily retrieve their model artifacts, Data Scientists can now search model files and pipelines within a registry in the Wallaroo platform.
  • ML pipeline management. As part of this new release, we have simplified ML model deployment. In the Wallaroo platform, Data Scientists can now place their ML models into pipelines. To deploy their ML models, Data Scientists will only need to deploy the pipelines in which they placed their ML models. This capability allows Data Scientists to easily run, stop or check on the status of their model deployment activities.

For more information about this release, please contact us at deployML@wallaroo.ai.