Question 1

CASE STUDY: AutoIoT

Overview: Connected car manufacturer. 1M vehicles sending telemetry every 5 seconds.
Business: Predictive maintenance alerts, real-time fleet tracking, monetize anonymized data.
Executives:
- CEO: "Leverage AI to predict failures."
- CTO: "Current MQTT brokers crashing. Need fully managed, scalable ingestion."
- DPO: "Vehicle location is sensitive. Strip PII before analytics."
Tech: Ingest millions of msgs/sec, real-time stream processing for anomalies, store raw data for ML, sub-second queries for dashboards.
Constraints: Vehicles lose connection and send late batch data. ML models updated weekly. Strict analytics budget.

Which database should you use to serve the real-time fleet tracking dashboard requiring sub-second queries on massive time-series data?

Accepted Answer

Identify the GCP database designed specifically for high-throughput, low-latency time-series data.

Question 2

What mistakes do candidates make on this GCP PCA question?

Accepted Answer

Choosing Cloud SQL (A). Relational databases will quickly bottleneck on write operations at IoT scale.

How to approach this question

Full Answer

Common mistakes

Practice the full GCP Professional Cloud Architect Practice Exam 4

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