Get the most out of your cloud infrastructure spending while ensuring the best experience across your entire analytics platform.
Balance cost with agility.
Optimize Kubernetes compute resources through resource-based load balancing and job prioritization. With SAS Workload Management, you can define priorities for different types of workloads, ensuring that the most important work gets done first – and without interrupting interactive sessions.
Improve throughput, availability and productivity.
SAS Workload Management lets you maximize workload processing efficiency, delivering greater throughput through parallel job processing. Your data scientists spend less time waiting for failed jobs to restart, so they can stay focused on producing the best models.
SAS Workload Management is powerful, yet easy to use. A graphical interface lets you centrally manage policies, programs, queues and priorities of SAS jobs running on Kubernetes. With centralized management of all resources, administrators spend less time learning new tools and bouncing between different applications for analytic workloads.
Extending the power of Kubernetes by optimizing and prioritizing SAS workloads within a Kubernetes cluster.
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