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Google Associate Data Practitioner Exam - Topic 1 Question 28 Discussion

You manage data at an ecommerce company. You have a Dataflow pipeline that processes order data from Pub/Sub, enriches the data with product information from Bigtable, and writes the processed data to BigQuery for analysis. The pipeline runs continuously and processes thousands of orders every minute. You need to monitor the pipeline's performance and be alerted if errors occur. What should you do?
A) Use Cloud Monitoring to track key metrics. Create alerting policies in Cloud Monitoring to trigger notifications when metrics exceed thresholds or when errors occur.
B) Use the Dataflow job monitoring interface to visually inspect the pipeline graph, check for errors, and configure notifications when critical errors occur.
C) Use BigQuery to analyze the processed data in Cloud Storage and identify anomalies or inconsistencies. Set up scheduled alerts based when anomalies or inconsistencies occur.
D) Use Cloud Logging to view the pipeline logs and check for errors. Set up alerts based on specific keywords in the logs.

Google Associate Data Practitioner Exam - Topic 1 Question 28 Discussion

Actual exam question for Google's Associate Data Practitioner exam
Question #: 28
Topic #: 1
[All Associate Data Practitioner Questions]

You manage data at an ecommerce company. You have a Dataflow pipeline that processes order data from Pub/Sub, enriches the data with product information from Bigtable, and writes the processed data to BigQuery for analysis. The pipeline runs continuously and processes thousands of orders every minute. You need to monitor the pipeline's performance and be alerted if errors occur. What should you do?

Show Suggested Answer Hide Answer
Suggested Answer: A

Comprehensive and Detailed in Depth

Why A is correct:Cloud Monitoring is the recommended service for monitoring Google Cloud services, including Dataflow.

It allows you to track key metrics like system lag, element throughput, and error rates.

Alerting policies in Cloud Monitoring can trigger notifications based on metric thresholds.

Why other options are incorrect:B: The Dataflow job monitoring interface is useful for visualization, but Cloud Monitoring provides more comprehensive alerting.

C: BigQuery is for analyzing the processed data, not monitoring the pipeline itself. Also Cloud Storage is not where the data resides during processing.

D: Cloud Logging is useful for viewing logs, but Cloud Monitoring is better for metric-based alerting.


Cloud Monitoring for Dataflow: https://cloud.google.com/dataflow/docs/guides/using-monitoring

Cloud Monitoring: https://cloud.google.com/monitoring/docs

by Sylvia at Jun 26, 2026, 01:53 AM

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Norah
1 day ago
Totally agree with A), metrics are key for performance tracking.
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Long
7 days ago
Surprised that D) is even an option, logs can be overwhelming!
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Launa
12 days ago
C) seems a bit indirect for immediate error alerts.
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Marlon
17 days ago
I think B) is more hands-on and effective.
upvoted 0 times
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Jarod
22 days ago
A) is the best option for real-time monitoring!
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Gail
27 days ago
I recall we talked about Cloud Logging, but I’m uncertain if setting alerts based on keywords is effective for all types of errors.
upvoted 0 times
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Gary
1 month ago
I feel like using BigQuery for anomaly detection is a bit off-topic here. We focused more on monitoring tools, right?
upvoted 0 times
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Roslyn
1 month ago
I think option B sounds familiar; we practiced checking the Dataflow job monitoring interface in class. It seems like a good way to catch errors visually.
upvoted 0 times
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Leonie
1 month ago
I remember we discussed using Cloud Monitoring for tracking metrics, but I'm not sure if it's the best option for real-time alerts.
upvoted 0 times
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