atsu empowers media and entertainment customers to reduce pipeline interruptions, increase throughput, and easily scale their large-scale production environments. Are you having predictability, efficiency, or agility challenges with your render and post-production workflows? Do bad jobs, overwhelmed NFS mounts, or errant user activities consume your precious operator cycles, cause you to over-provision resources, and disrupt delivery schedules? Are you struggling to manage the myriad of digital processes and projects in your pipeline, overworking your wranglers, and starving other projects to get things in on time? atsu delivers breakthrough personalization for media and entertainment digital workflows, resulting in simplified understanding, increased utilization, and automated improvements. atsu includes lightweight, always-on agents, combined with a hybrid cloud service, which continually leverages ML to optimize your digital pipeline. atsu streamlines IO, compute system management, and your unique combination of software, infrastructure, and processes.
Or, why you'll learn to stop over-provisioning and free the creative humans
Predictable utilization of existing resources results in capital savings — and better provisioning fit.
An automagically efficient infrastructure frees up talented engineers to deliver better products.
Give your compute environment the agility to adapt to your rapidly changing business priorities.
AKA, the Digital Pipeline Band
Render and post-production workflows have regular challenges with predictability, efficiency, and agility at the intersection of the human and machine boundary. A large production environment has several critical actors (the creatives, the operators, the technical directors, and the developers) leveraging a unique and complex set of software and processes to build amazing content.
With atsu's machine learning for media technology, you can free up talented humans so they can focus on revenue generating tasks.
I want my apps to be responsive, and I want my jobs to get through.
I don't want to have to chase down bad jobs, or figure out why storage is breaking.
I need to know if my queue is going to clear; if it's not, which jobs should I pull?
Should I use 4 or 8 cores? how well does my app scale over NFS?
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