Case Study: Michelin cuts costs and boosts flow monitoring with MongoDB Atlas

Michelin cuts project costs by 30% with MongoDB

Michelin, a global industrial manufacturer, faced challenges with its on-premises E2E monitoring application, which was crashing under the strain of end-of-month billing spikes. The company needed to upgrade this mission-critical system without any downtime and required a solution that could handle massive, fluctuating data volumes.

By migrating to MongoDB Atlas, Michelin implemented a scalable, managed solution. MongoDB's autoscaling capabilities handled peak loads seamlessly, and Atlas Search replaced a complex custom search mechanism. This resulted in a 30% reduction in total project costs, a 70% reduction in message sizes, and a drastic simplification of their database from 26 indexes down to just six.

Michelin