Learn more about workload balancing.
You need a flexible IT infrastructure that meets peak computing demands reliably and cost-effectively. Now you can create a managed, shared grid computing environment with workload balancing, high availability and faster processing.
As your organization's use of business analytics grows, so does the need for a flexible IT infrastructure that can scale to increasingly diverse workloads. Easily reassign computing resources to meet peak demand. A central point of control lets you queue and prioritize jobs across multiple users and applications. High-priority jobs run immediately and computing resources are fully utilized.
Having multiple servers in a grid environment means that if a server fails, its jobs transition seamlessly to another server. With a highly available, shared grid environment, you're always on and always connected. You can perform maintenance on specific servers without interrupting jobs. And add computing resources without disrupting the business.
Now you can get faster results and scale cost-effectively. Divide individual jobs into subtasks that are run in parallel on the best available hardware. Programs with large data sets and long run times, and those with replicate runs of independent tasks running against large data sets, are best-suited for multiprocessing. Make the most of all your available computing resources now, then add single-processing units as needed to keep IT spending in check.
Catalina, a digital media company, turned to SAS Grid Manager to help them process large amounts of information without constraints. The end result? More insights – and happier customers.
Using SAS Grid Manager, data scientists at Humana can run more models with faster turnaround times. And since the technology delivers almost instant answers, they're able to make a difference in people's lives.
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