Question 1

CASE STUDY: ManuIoT

Overview:
Industry: Manufacturing
Size: 100 factories globally

Environment:
- 100,000 sensors
- Local SCADA
- Fragmented SQL Server DBs
- No central analytics

Requirements:
- Predictive maintenance
- Real-time global dashboards
- Edge computing

Exec Statements:
- CEO: Monetize telemetry.
- CFO: Costs must scale linearly.
- VP Ops: Factory lines need local control if internet drops.

Tech Reqs:
- Ingest 1M msgs/sec
- Stream processing
- Offline factory capabilities
- Train ML centrally, deploy to edge

Constraints:
- Low bandwidth/high latency at factories
- Legacy MQTT protocol
- Zero IT staff at factories

QUESTION: Which service should you use to perform real-time anomaly detection on the streaming sensor data before it is stored?

Accepted Answer

Identify the GCP service designed for complex, serverless stream processing.

Question 2

What mistakes do candidates make on this GCP PCA question?

Accepted Answer

Choosing Cloud Functions (C) for stream processing. While functions can trigger on Pub/Sub, they lack the stateful windowing capabilities needed for anomaly detection.

How to approach this question

Full Answer

Common mistakes

Practice the full GCP Professional Cloud Architect Practice Exam 6

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