Blueprint for designing ultra-high-throughput streaming pipelines that transform connected vehicle noise into actionable safety intelligence.
A modern software-defined connected car produces up to 25 gigabytes of internal telemetry per hour. When multiplied across a municipal fleet of 100,000 vehicles, central data pipelines face unprecedented ingestion volume.
V2XTelemetry compresses high-frequency vehicle CAN data using Protocol Buffers and transmits it over persistent gRPC connections to distributed Apache Kafka clusters. Apache Flink workers compute tumbling and sliding window statistics—identifying rapid decelerations and traction control activations within 250 milliseconds. ``` +-----------------------+ gRPC / Protobuf +-----------------------+ | 100,000 Vehicles | --------------------------------> | Distributed Kafka | | (5M Events / Sec) | | Partitioned Ingest | +-----------------------+ +-----------------------+ | v Apache Flink Workers Sub-250ms Alert: Accident Ahead! | v ClickHouse Columnar Store Instant Historical Queries ```
By organizing time-series data into ClickHouse columnar storage with ZSTD compression, analytical queries over 10 billion historical data points complete in under 420 milliseconds.