Performance Improvements for Open-Source Model Execution in SAS Model Manager

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SAS Model Manager is a model repository where SAS, Python, and R models can be registered, tested, deployed, and monitored side-by-side. To meet rising user expectation for model execution speed, the SAS Model Manager team continues to add performance enhancements. As of 2025.01, SAS Model Manager has released two enhancements for improving the performance and execution speeds for Python and R models. The first is an updated R base container and the second is the adoption of CAS Gateway.

CAS Gateway Adoption

SAS Model Manager has multiple execution environments, from batch execution within SAS Viya to transactional REST-API endpoints hosted on SAS Viya or outside of it via containers. The SAS Cloud Analytic Services, also known as CAS, is an execution environment that is optimized for batch. It is not just a publishing destination, but also the engine behind score testing and performance monitoring in SAS Model Manager.

Last year, the CAS Gateway action was released. This action provides a way to submit code written in Python and R in a parallel manner to increase processing speeds for large datasets. As of 2025.01, SAS Model Manager had adopted CAS Gateway in our scoring tests and performance monitoring. This has drastically decreased the time it takes to score Python and R models within SAS Viya. In our performance testing, our team is seeing a 7x improvement for scoring 1 million records in SAS Viya.

To get started using the updated score testing and performance monitoring, your administrator may need to update their configuration for External Language Access Control. This may include updating or adding pyarrow and pandas within the Python environment.

Updated R Base Container

SAS Model Manager can build and deploy containers for SAS, Python, and R models using a technology called SAS Container Runtime. SAS Container Runtime allows models to run in any OCI-compliant system using a lightweight and scalable container that manages the dependencies required by that model. These containers are executed outside of SAS Viya without needed to pay any additional fees to SAS.

The SAS Model Manager team has already updated our Python base container to be smaller and faster. With the 2025.01 release, we have made similar improvements to our R base container. To leverage the new R base container, simply deploy a R model from SAS Model Manager on 2025.01. Now, your container will be lighter and faster!

To learn more about open-source and SAS Model Manager, check out the following resources: