Shell Builds 10,000 AI Models on Kubernetes in Less than a Day
Published in
Dec 17, 2021
As Shell, an oil and gas giant, launched its Renewable and Energy Solutions initiative, the company needed an agile control system to efficiently distribute electrical power. The organization relied on an MLOps platform to build a Kubeflow-driven solution that allocates and manages computational resources. As a result, Shell was able to reduce time on building 10,000 machine learning models on Kubernetes to 2 hours instead of 4 weeks, while facilitating the writing of the underlying code to 4 hours instead of 2 weeks.
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