Red Hat and SAS collaborate to bring advanced analytic capabilities to the hybrid cloud

Data and analytics are changing the way we do business -- enabling organizations to better serve their customers and get more done quicker. However, to obtain value from AI and data science efforts, organizations need to deploy, operationalize and put these analytical assets into production. To help put analytical insights into action quicker, we are pleased to announce the general availability of SAS Viya on Red Hat OpenShift. ​​Initially available on VMWare, Viya will support other infrastructure variations in subsequent releases.

SAS Viya is a cloud-native AI, analytic and data management platform designed to transform raw data into operational insights. When delivered on Red Hat OpenShift, the industry’s leading enterprise Kubernetes platform, SAS Viya supports analytics anywhere including on premises,  public and private cloud environments, and at the edge. With SAS Viya on Red Hat OpenShift, developers are able to build and deploy analytical models once and deploy with consistency across the entirety of the hybrid cloud.

An intelligent advantage

Today, organizations across geographies and industries are innovating digitally and creating more customer value and differentiation while helping to level the competitive playing field. The ability to capture and analyze big data and apply context-based visibility and control into actionable information is what creates an intelligent enterprise. It entails using data to get real-time insights across the lines of business - which can then drive improved operations, innovation, new areas of growth and deliver enhanced customer and end user experiences.

The collaboration between Red Hat and SAS helps enable organizations to use open hybrid cloud technologies and analytical capabilities to drive business-level intelligence. With SAS Viya on Red Hat OpenShift, model developers are able to build and deploy models with portability and consistency across environments of their choosing. This helps accelerate the adoption of analytics across the hybrid cloud. Regardless of where they are in their cloud journey, with Red Hat and SAS, users can build and scale analytics on a more consistent and  stable infrastructure. This allows them to operationalize analytics and shift models into production quickly.

Accelerate data-driven workloads with Red Hat OpenShift 

Red Hat OpenShift provides a host of features aimed at enabling Kubernetes clusters to more effectively run, accelerate and scale AI/ML workloads across hybrid cloud environments. These features include:

• Develop and deploy a combination of SAS and open source modeling techniques to deliver more accurate AI/ML modes for production and governed with a common interface. 

• AI for IT operations (AIOps) to automate the identification and resolution of common information technology (IT) for the use of big data analytics, machine learning (ML) and other artificial intelligence (AI) technologies.

• Device plugins for access to GPUs and other specialized hardware to applications running in containers.

• Huge Pages support to enable containers with large memory requirements to run more efficiently.

• Multi-network support to allow more than one network interface per container for better traffic management.

With Red Hat and SAS, enterprises can gain real intelligence by using their accumulated knowledge to create new knowledge—new intelligence—so that they can better respond to changes and challenges in evolving business environments. Additionally, SAS is completing Red Hat OpenShift certification giving customers the additional benefit of interoperability, security features and life cycle management of SAS Viya on OpenShift. We are excited to fully bring Red Hat OpenShift support to SAS Viya, helping to enable organizations to use open hybrid cloud technologies and analytical capabilities for greater business intelligence. To learn more about the collaboration and get started with SAS Viya on Red Hat OpenShift, visit www.sas.com/openshift.