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Case Study: Michelin cuts costs 35% and gains 8-9 months time to market with Confluent Cloud

Michelin Case StudySourced & dated by Case Study Desk
Key facts · TL;DR
Company
Michelin
Industry
Manufacturing
Challenge
Reduce the operational burden and cost of self-managed Kafka.
Headline result
Offloading self-managed Kafka to accelerate a data-first transformation

Key results

35%
Cost savings vs on-premises operations
estimated, using Confluent Cloud
8-9 mo
Gained in time to market
99.99%
Uptime
resilient, highly available architecture
10TB/day
Throughput supported
elastic scalability

The challenge

Michelin, a tire manufacturer founded in 1889, needed to accelerate its shift to a data-first, digital business. The company had employed three full-time employees to manage its self-operated Apache Kafka clusters.

The solution

Michelin adopted Confluent Cloud as a core part of its data infrastructure to stream data in real time and offload the operational burden of running Kafka. The managed platform provided elastic scalability supporting 10TB/day of throughput.

We use Confluent Cloud as an essential piece of our data infrastructure to unlock data and stream it in real time.

YC
Yves Caseau
Group Chief Digital & Information Officer, Michelin

The results, in context

Michelin estimated 35% in cost savings from using Confluent Cloud compared to on-premises operations, with a resilient architecture delivering 99.99% uptime. The company also reported gaining eight or nine months in time to market.

Products used

Confluent Confluent Cloud