Formula 1 telemetry processing using Kafka Streams

on YouTube ↗25m

" summary

Pipeline ingests UDP telemetry from F1 2020 into Kafka via Apache Camel, decodes packets into per-driver records, computes per-driver average speed in five-second tumbling windows using Kafka Streams, materializes state in RocksDB-backed KTables, then exports metrics to InfluxDB and Grafana. Deployment uses the Strimzi operator on OpenShift; a Python recorder replays recorded sessions so dashboards update in real time. The demo works live and shows spikes from the tumbling-window aggregation.

AI-written summary · about

" chapters (8)

1. 0:00Introduction and goals
2. 1:16Data pipeline architecture
3. 9:24Stream processing concepts
4. 12:12Aggregations and KTables
5. 14:31Scaling and fault tolerance
6. 17:00Deployment on Kubernetes
7. 18:36Demo and dashboard showcase
8. 21:00Resources and Q&A

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