Question 1

**CASE STUDY: AutoMakers Inc**

**Company Overview:**
AutoMakers Inc is a global vehicle manufacturer. They have recently launched a line of connected cars.

**Current Technical Environment:**
- 1 million connected cars currently on the road
- Cars send telemetry data (speed, engine temp, location) every 5 seconds
- Current on-premises MQTT brokers are crashing under the load

**Business Requirements:**
- Enable predictive maintenance to alert drivers before parts fail
- Provide real-time fleet tracking for commercial customers
- Support over-the-air (OTA) software updates

**Executive Statements:**
- CEO: "Data is our new revenue stream. We need to monetize this telemetry data."
- CTO: "We expect to have 10 million connected cars in 3 years. The architecture must scale infinitely without manual intervention."
- CFO: "The cost of ingesting and storing this data must be strictly controlled. We cannot pay for idle capacity."

**Technical Requirements:**
- Ingest up to 100,000 messages per second
- Low-latency processing for real-time alerts
- Time-series data storage for historical analysis
- Handle variable network connectivity (cars driving through tunnels)

**Constraints:**
- Strict budget for data ingestion
- Small data engineering team

**QUESTION:**
To address the CFO's concern about the cost of ingesting millions of messages, how should you optimize the data transmission from the cars to Cloud Pub/Sub?

Accepted Answer

Understand Pub/Sub pricing. It is billed by data volume, but with a minimum of 1KB per request. Sending tiny payloads frequently wastes money. Batching at the edge is the solution.

Question 2

What mistakes do candidates make on this GCP PCA question?

Accepted Answer

Choosing compression (A). Compression is good, but if the message is already under 1KB, compressing it further doesn't save any money in Pub/Sub.

How to approach this question

Full Answer

Common mistakes

Practice the full GCP Professional Cloud Architect Practice Exam 3

More questions from this exam