Confluent × Michelin
Confluent x Michelin, 35% Kafka cost cut on the path to cloud
35% cost savings vs. on-premises Kafka operations
Operational burden to engineering velocity
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Why it works
The headline number is a cost reduction, which anchors this squarely as Efficiency despite the story also touching reliability and future capability. The case study earns credibility by pairing the cost claim with a concrete operational explanation: three FTEs freed from infrastructure babysitting and eight to nine months recovered in time to market. The multi-voice structure, drawing quotes from the CIO, an IT architect, and an integration architect, gives the story depth without inflating a single claim.
Steal this
The three-tier quote sourcing: CIO for strategic framing, IT architect for technical detail, and integration architect for operational reality. It makes the story feel independently verified from inside the same company.
Click to enlarge ↗ This is editorial commentary and curation. The case study, screenshot, and all metrics are Confluent's published work; we link to the source and lead with our analysis.