Google Cloud Digital LeaderInfrastructure modernization with Google CloudMedium
A logistics company wants to modernize its fleet management system. They need to collect real-time telemetry data (GPS coordinates, speed, fuel levels) from thousands of vehicles, process this data as it arrives to detect anomalies, and then store it for historical analysis. The data stream is continuous and high-volume. Which Google Cloud service combination should they use for ingesting and processing this real-time data?
- APub/Sub and Dataflow
- BCloud SQL and Dataflow
- CCloud Storage and Dataflow
- DPub/Sub and Cloud Functions
Show answer & explanationAnswer & explanation
Correct answer: A. Pub/Sub and Dataflow
Pub/Sub is an ideal messaging service for ingesting high-volume, real-time data streams, and Dataflow is perfect for stream processing this data to detect anomalies and prepare it for storage.
Why the other options are wrong
- B. Cloud SQL is a relational database for transactional data, not suitable for high-volume real-time ingestion and stream processing.
- C. Cloud Storage is for static data storage, not real-time ingestion or stream processing.
- D. Cloud Functions are for short, event-driven tasks, not typically for continuous, high-volume stream processing like Dataflow.
Pub/Sub and Dataflow
Pub/Sub is a global, real-time messaging service for ingesting data streams, and Dataflow is a fully managed service for executing Apache Beam pipelines for stream or batch data processing.
- Pub/Sub: Scalable, asynchronous messaging for event ingestion
- Dataflow: Unified programming model for batch and stream processing
- Together, they form a robust real-time data pipeline
Memory trick: Pub/Sub takes the stream, Dataflow processes the dream.