GCP PCA · Question 11 · Business Requirements
CASE STUDY: AeroMech
Overview: Aviation manufacturer, 5000 employees, $2B revenue. 100 engines, 10k sensors/engine, 1GB data/flight. On-prem Hadoop.
Business Req: Predictive maintenance, secure data sharing with airlines, monetize data.
Execs: CEO wants new revenue; CFO demands ML ROI; CTO says on-prem storage unfeasible.
Tech Req: High-throughput ingestion, PB-scale storage, train ML on historical data, deploy ML to edge (aircraft).
Constraints: Intermittent low-bandwidth flight connectivity, aviation data compliance, data scientists use Python/Jupyter.
QUESTION:
How should you design the ingestion pipeline to handle the intermittent connectivity and high data volume from the aircraft engines?
Answer options:
Stream data directly to Cloud SQL using a continuous VPN connection.
Buffer data locally on the aircraft edge device, then publish to Cloud Pub/Sub when connectivity is restored.
Write data to a local CSV file and email it to a Cloud Function upon landing.
Use Cloud Interconnect to establish a dedicated link to the aircraft.
50 questions · hints · full answers · grading
Expert