SAS^® Workload Management

SAS^® Workload Management Features

Optimize & prioritize analytic computing on Kubernetes

Improves efficiency of program distribution and CPU utilization through dynamic, resource-based load balancing.
Makes computing resources available to multiple users and multiple applications for running larger or more complex analysis.
Provides job, queue, host and user management across your enterprise.
Enables job prioritization by rules-based job queues to govern the use of computing resources.
Provides automatic identification, allocation, management and optimization of computing resources and program flows.
Simplifies administration of SAS environment through centralized policies.

Provides high-availability capabilities for critical analytic workloads running on Kubernetes.
Detects Kubernetes failures and recovers appropriately.
Ensures that SAS jobs will be completed optimally.
Restarts SAS jobs automatically from the last successful checkpoint when used with the SAS checkpoint/restart feature.

Balances the load of many SAS Viya users through easy code submission.
Provides load balancing for all SAS SPRE servers to improve throughput and response time of all SAS clients.
Uses SAS Code Analyzer to analyze job dependencies in SAS programs and generates code ready for parallel processing.
Provides automated session spawning and distributed processing of analytic programs across a set of diverse Kubernetes computing resources.
Speeds up processing of applicable analytic programs and applications and provides more efficient computing resource utilization.
Enables scheduling of production workflows to be executed across grid resources.
Provides a process flow diagram to create process flows of one or more analytic jobs that can be simple or complex to meet your needs.
Enables many SAS solutions and user-written programs to be easily configured for submission to a cluster of shared resources.
Provides greater resilience for mission-critical applications and high availability for the SAS Viya environment.
Includes command-line batch submission utility called SASGSUB:
- Allows you to submit and forget and reconnect later to retrieve results.
- Enables integration with other standard enterprise schedulers.
Enables batch submission to leverage checkpoint and automatically restart jobs.
Applies grid policies to SAS SPRE servers when they are launched through SAS applications.

Provides a web-based tool for monitoring and administering multiple SAS clusters, including:
- Visuals for tracking resource usage, users and jobs running on Kubernetes.
- A GUI for modifying configurations and defining alerts when critical thresholds are crossed.
- A GUI for configuring and managing critical services for high availability.
- Support for filtering and role definitions for customizing displays and activities that can be performed.

Allows you to add computing resources incrementally to cost-effectively accommodate a growing number of users, as well as meet increased business needs.
Decouples the computing infrastructure requirements from applications to allow business users to focus on their processes.
Creates a shared environment for easily and dynamically allocating resources to meet peak needs of different business users over time.
Eases infrastructure maintenance needs by allowing machines to be taken offline without disrupting the business.
Improves performance and scalability through the use of Kubernetes running on supported cloud infrastructures.