Easy1 markMultiple Choice
Domain 4: Analyzing and Optimizing Technical and Business ProcessesDomain 4Cloud MonitoringCloud Pub/SubAlerting
This question is part of a case study — click to read the full scenario(Case 16)

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 meet the CTO's requirement for infinite scaling and the technical requirement to ingest 100,000 messages per second, which ingestion and processing pipeline should you design?

GCP PCA · Question 19 · Domain 4: Analyzing and Optimizing Technical and Business Processes

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:
The operations team needs to be alerted if the number of unacknowledged messages in the Pub/Sub subscription exceeds 500,000, indicating a processing bottleneck. How should you configure this?

Answer options:

A.

Write a Cloud Function that queries the Pub/Sub API every minute and sends an email if the count is high.

B.

Create an alerting policy in Cloud Monitoring based on the pubsub.googleapis.com/subscription/num_undelivered_messages metric.

C.

Configure Cloud Logging to search for 'bottleneck' errors in the Dataflow logs.

D.

Enable Pub/Sub dead-letter topics and alert when messages are sent there.

How to approach this question

Identify the need: alert on a specific GCP resource metric (Pub/Sub backlog). Cloud Monitoring is the native tool for metric-based alerting.

Full Answer

B.Create an alerting policy in Cloud Monitoring based on the `pubsub.googleapis.com/subscription/num_undelivered_messages` metric.✓ Correct
Cloud Monitoring automatically collects metrics from Cloud Pub/Sub. The `num_undelivered_messages` metric represents the backlog of messages waiting to be processed. Setting up an alerting policy on this metric is the best practice for ensuring streaming pipelines are keeping up with ingestion rates.

Common mistakes

Choosing dead-letter topics (D). Dead-letter topics handle poison pill messages (bad data), not processing latency or backlogs.

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