This invention describes a software system that helps manage computer resources in a large network of computers (a distributed system). It works by constantly looking at how resources are being used, first identifying and removing long-term trends using linear regression, then building statistical models from the remaining data. When it needs to predict future resource needs, it combines the trend with the best-fitting model to forecast usage, allowing the system to automatically adjust how virtual parts of the network use resources.
Why it matters: Filed in 2018, the complexity and scale of distributed systems, especially with the rise of AI/ML workloads and serverless computing, have made precise resource forecasting even more critical. Modern observability platforms now provide the high-fidelity metric data required for this statistical modeling approach.
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