Case Study: a Fortune 500 fintech company achieves scalable machine learning with Canonical Kubeflow on AWS

Fortune 500 fintech company goes from constant troubleshooting to scalable machine learning by switching to Canonical Kubeflow on AWS

A fortune 500 fintech company, a leader in the US financial services sector, was facing significant stability issues and high maintenance overhead with its proprietary Kubeflow platform. The instability was blocking its data scientists and the platform team was spending too much time troubleshooting, hindering their machine learning operations.

Canonical provided a solution by implementing its fully open source, enterprise-supported Canonical Kubeflow on AWS. The switch resulted in a highly stable and automated environment, which drastically improved data scientist productivity. The solution also enhanced security by remediating at least 60 high and critical CVEs, allowing the company to meet its strict compliance requirements while scaling its ML capabilities.