Idle and over-provisioned resource can lead to substantial costs. To avoid waste being built in to your cloud solution, it is essential you understand where to execute your workloads.
With YellowDog Optima, you can predict workload runtime, so you know when and how long to provision resource, and you can proactively respond if workloads fail – especially if they fail “silently”. In addition, you can determine how to optimally fit workloads of different priority and SLA types, to help reduce wait times, priority conflicts and delays.Book a Demo
With advanced machine learning you can understand the predictability of your workloads and adapt to any complex variations that may occur from time to time. This enables you to schedule workloads with greater insight, avoiding potential conflicts and ensuring SLAs are met and exceeded.
Improve execution efficiency by running more workloads on the same resources.
Reduce priority conflict between workload tasks with optimal scheduling.
Mitigate risk and drive performance by planning workload execution costs and overheads in advance.
Reduce opportunity cost and priority conflict with predictive workload scheduling.
Improve adherence to SLAs with automated proactive alerting so issues are highlighted and resolved quicker.
Predict the cost and operational impact of expanding workload processing through precise workload scheduling.
VP and Global Head of Solution Architecture Leading Global Risk & Analytics Business
“YellowDog have created functionality that we have wanted for over a decade. This can transform how we run our infrastructure.”
Read how models were able to deliver predicted time for workloads with 96% confidence for CPU Time. Reducing costs, boosting end-client satisfaction, and optimising hardware utilisation.
Learn more about the challenges businesses face in avoiding cloud waste and the business impact of using YellowDog Optima.
To book a demo of YellowDog Optima, or to ask our team for further information, you're just a click away!
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