GCP: Real-Time Truck Tracking Architecture! #shorts To build a real-time logistics dashboard that tracks thousands of delivery trucks every 10 seconds and refreshes within a strict 30-second SLA, the definitive GCP pipeline is Pub/Sub → Dataflow → BigQuery → Looker Studio. This architecture utilizes Pub/Sub to ingest the high-frequency stream, Dataflow to process the incoming data on the fly, and BigQuery’s streaming inserts to ensure coordinates are queryable within seconds so Looker Studio can display live updates instantly. Trying to write directly to Cloud SQL will fail because relational databases cannot sustain that volume of concurrent streaming inserts, while landing data in Cloud Storage first introduces too much file-loading latency, and Cloud Scheduler is strictly a batch tool that cannot handle continuous data streams. For the GCP exam, remember that when sub-minute end-to-end data freshness is non-negotiable, Dataflow combined with BigQuery streaming inserts is your gold standard architectural pattern. 🚀 #GCP #DataEngineering #GoogleCloud #Dataflow #BigQuery #PubSub #LookerStudio #StreamingAnalytics #RealTimeData #GCPCertification #CloudArchitecture #LogisticsTech #TechTips
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Why couldn’t Cloud SQL handle the incoming data? It should be able to handle the writes right? Maybe just not any transformations if needed
Cloud SQL is by far capable of handling this load. Every 10s even for tens of thousands of trucks is easily possible.