How a Leading Commercial Vehicle OEM Achieved Kafka-Native Sovereignty with Condense 

As the OEM’s connected vehicle program scaled, its existing data infrastructure began to constrain growth across multiple dimensions. The incumbent streaming platform was tightly coupled to a single cloud provider, limiting flexibility in deployment, inflating regional cloud costs, and making performance tuning nearly impossible. More critically, the platform lacked domain-native capabilities. Basic needs like parsing multi-protocol telematics payloads, evaluating geofences, or integrating with Fleet Management Systems (FMS) required building custom code from scratch, diverting focus from core mobility problems.

Development was further slowed by a fragmented model where application logic had to be managed as standalone microservices outside the core pipeline. This not only increased complexity and slowed time-to-market but also made scaling more difficult as vehicle volumes grew. Meanwhile, the platform lacked elastic scaling, forcing engineers to manually provision and balance resources during traffic bursts, resulting in either performance issues or overprovisioning waste.

Each of these limitations compounded into a broader issue:

The platform had become a barrier to innovation. Just as real-time applications like driver scoring, predictive maintenance, and dynamic routing were becoming critical, the underlying infrastructure was failing to support the pace and scale the OEM required.