What's New with SAS Model Manager? SAS Runtime Container

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Big news...SAS Model Manger now publishes SAS models as containers. Now you can execute SAS models ANYWHERE!

With the SAS Model Manager 2021.1.3 stable release, you can now publish SAS models using a lightweight OCI (Open Container Initiative) compliant Docker container for executing SAS models. This will greatly simplify efforts to move code from your Dev system to your Prod system using immutable containers. Simply register your SAS containerized model to your favorite cloud or docker location. Create an app or use restAPIs to score new data against your published model leveraging SAS Container Runtime. This provides a modern, bullet proof, reliable, non-proprietary system for transferring and executing runtime code.

The following video walks through how easy it is to publish SAS models to the new SAS Runtime Container.

(view in My Videos)

Now that your SAS model is published using SAS Container Runtime to any container registry, you can easily take advantage of the cloud infrastructure, or local installation, to deploy applications with small footprint and are highly scalable and highly available. This ensures resources can be fully utilized to quickly execute the largest number of models and reduce the effort that is required to manage the environment.

Why did SAS create SAS Container Runtime?

Customers consistently ask for a light weight runtime environment. They want to reduce their hardware and administration costs, focus their staff on general purpose IT skills, and minimize data movement. Run time containers fill all these needs.

In a nutshell, a container is a complete package of software that can be stored, moved, and executed in any container run time environment. The SAS container runtime combines a base layer of essential system files provided by SAS with the model or decision run time code files developed by the SAS Model Manager (MM) and/or SAS Intelligent Decisioning (ID) user.

Ultimately, runtime containers produced by SAS run in private Docker or Kubernetes systems or cloud service providers such as Microsoft Azure, Google Cloud Platform, or Amazon Web Services. The publish and deploy process is depicted below. SAS software will publish the complete container image to a user-defined Docker registry. This repository will serve as a staging area for containers ready to be deployed into a runtime environment.

MM and ID can run a publish validation test; however, users are responsible for deploying the container into the runtime. The following image shows one of many possible runtime systems. In this case, a common pool of SCR containers is serving both batch processes through Kafka integration and online event processes through the same REST API. The number of active containers is managed by a runtime system such as Kubernetes according to demand.

Example SAS Viya scoring environment using SCR containers

Bottom Line:

Use containers when you want to:

score in Docker and Kubernetes environments
use cloud-based systems for resource management and availability
implement modern CI/CD based workflows
integrate with cloud-based resources such as Kafka or CamelK
integrate with cloud-based data services such as S3 or BigTable
move into Software as a Service implementations
support batch and real time with one service type

Summary

SAS Container Runtime (SCR) hits all the marks:

Modern – industry standard tools for cloud enterprises
Bulletproof – completely self contained with minimal requirements
Reliable – runs the same in every environment
Non-proprietary – users only need common skills for transfer and execution

For more information about using SAS Model Manager publishing destinations, the SAS Model Manager: User’s Guide documentation. For more information about SAS Container Runtime, see the SAS Container Runtime. Looking for helpful "how-to" use the SAS Container Runtime for publishing SAS models to Kubernetes on the Azure cloud, check out this blog.

Needing help to determine which publishing destination is best for you, check out this SAS Communities blog entitled "ModelOps and DecisionOps for the Modern World" written by David_Duling.