Scaling Data Campaign Services for Rivian EV Fleets with MongoDB

Vehicle data campaigns at Rivian are designed to efficiently address specific, high-impact questions regarding vehicles in the field without increasing baseline telemetry volumes permanently. These campaigns must cater to a broad cohort, navigate various gateway paths for different vehicle models, and produce results accessible to operational applications with predictable latency while adhering to privacy regulations and regional data governance. Rivian addresses scalability challenges using MongoDB, which supports high availability, high throughput, and multi-region operations. The data campaign service acts as a control layer orchestrating data collection across fleets, ensuring that targeted investigations can be conducted swiftly and efficiently. By employing MongoDB's sharding and replica sets, Rivian ensures that campaign data can scale with fleet size and campaign intensity while maintaining regional data governance and availability. This system allows Rivian to balance the growth of connected vehicle data with the need for rapid investigation of anomalies, enabling efficient data collection specific to each campaign's needs. Furthermore, Rivian is exploring the use of semantic search to improve the efficiency of data triage and facilitate the reuse of past campaign outcomes, potentially transforming historical campaign data into a valuable resource for future analyses.

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