YellowDog Optima

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Optimal Predictive Scheduling for Compute-Intensive Workloads

As cloud usage grows, so does cloud “waste”. In fact, devops.com calculates that cloud waste will cost businesses $17.6 billion in 2020. Waste comes from idle and over-provisioned resource, therefore, it is essential to know more about where you execute your workloads to avoid waste being built in from the outset. Key insights include knowing the predicted runtime to understand when and how long to provision resource, and being proactive if workloads fail – especially if they fail “silently”.

In addition, determining how to optimally fit workloads of different priority and SLA types helps reduce wait times, priority conflicts and delays.

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What YellowDog Optima Delivers

YellowDog Optima leverages advanced machine learning so 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.

Reduce Compute Costs

Improve workload execution efficiency by running more workloads on the same resources.

Streamline Workloads

Reduce priority conflict between workload tasks with optimal scheduling.

Gain Competitive Advantage

Mitigate risk and drive performance by planning workload execution costs and overheads in advance.

YellowDog Optima Features

  • Accurate prediction of workload run times using advanced machine learning.
  • Model Training and query REST APIs which support inclusion of seasonal data, decay parameters and validation of model fit.
  • Automated proactive alerting if workloads exceed predicted run times.

YellowDog Optima Use Cases

Predictive Scheduling

Reduce opportunity cost and priority conflict with optimal workload scheduling.

Proactive alerting

Improve adherence to SLAs with automated proactive alerting so that issues are highlighted and resolved quicker.

Cost prediction

Accurately predict the cost and operational impact of expanding workload processing through precise, predictive workload scheduling.

“YellowDog have created functionality that we have wanted for over a decade. This can transform how we run our infrastructure.”

VP and Global Head of Solution Architecture Leading Global Risk & Analytics Business

YellowDog Optima Case Study

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.

Optimising Workload Scheduling

Learn more about the challenges businesses face in avoiding cloud waste and the business impact of using YellowDog Optima.

Optimise and Predict Performance with 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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