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Google Exam Professional Data Engineer Topic 1 Question 101 Discussion

Actual exam question for Google's Professional Data Engineer exam
Question #: 101
Topic #: 1
[All Professional Data Engineer Questions]

Your car factory is pushing machine measurements as messages into a Pub/Sub topic in your Google Cloud project. A Dataflow streaming job. that you wrote with the Apache Beam SDK, reads these messages, sends acknowledgment lo Pub/Sub. applies some custom business logic in a Doffs instance, and writes the result to BigQuery. You want to ensure that if your business logic fails on a message, the message will be sent to a Pub/Sub topic that you want to monitor for alerting purposes. What should you do?

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Suggested Answer: C

To ensure that messages failing to process in your Dataflow job are sent to a Pub/Sub topic for monitoring and alerting, the best approach is to use Pub/Sub's dead-letter topic feature. Here's why option C is the best choice:

Dead-Letter Topic:

Pub/Sub's dead-letter topic feature allows messages that fail to be processed successfully to be redirected to a specified topic. This ensures that these messages are not lost and can be reviewed for debugging and alerting purposes.

Monitoring and Alerting:

By specifying a new Pub/Sub topic as the dead-letter topic, you can use Cloud Monitoring to track metrics such as subscription/dead_letter_message_count, providing visibility into the number of failed messages.

This allows you to set up alerts based on these metrics to notify the appropriate teams when failures occur.

Steps to Implement:

Enable Dead-Letter Topic:

Configure your Pub/Sub pull subscription to enable dead lettering and specify the new Pub/Sub topic for dead-letter messages.

Set Up Monitoring:

Use Cloud Monitoring to monitor the subscription/dead_letter_message_count metric on your pull subscription.

Configure alerts based on this metric to notify the team of any processing failures.


Pub/Sub Dead Letter Policy

Cloud Monitoring with Pub/Sub

by Arthur at Jan 10, 2025, 12:51 PM

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Malcom
2 months ago
Haha, I bet the folks who wrote this question thought they were being clever. But I'm going with C - dead lettering is the way to go, in my opinion.
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Christene
7 days ago
Dead lettering seems like the most reliable option to ensure that no messages are lost in case of failures.
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Leatha
8 days ago
I would go with C as well. It's always better to have a designated place for failed messages.
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Doyle
9 days ago
Yeah, I agree. It's important to have a mechanism in place to deal with messages that couldn't be processed.
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Cordelia
12 days ago
I think C is the best option too. Dead lettering is a good way to handle failed messages.
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Ligia
2 months ago
I'm torn between A and C. Both seem viable, but I think C might be a bit more straightforward and easier to implement.
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Reena
14 days ago
True, A could be a good solution as well. It's a tough decision.
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Alease
16 days ago
But A also seems like a good choice, with the side output feature.
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Temeka
21 days ago
I agree, C does seem like a straightforward option.
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Janessa
25 days ago
I think C might be the way to go. It sounds simpler.
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Danica
3 months ago
C looks good to me. Dead lettering is a common approach for handling failed messages, and monitoring the dead letter topic is a smart move.
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Cecil
1 months ago
I agree with A. It's important to handle failed messages at the code level to ensure proper processing and monitoring.
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Deeanna
1 months ago
I think A might be a better option. Using exception handling in the Data Flow's DoFn code seems like a more direct way to handle failed messages.
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Rodrigo
1 months ago
C looks good to me. Dead lettering is a common approach for handling failed messages, and monitoring the dead letter topic is a smart move.
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Deandrea
3 months ago
I'm not sure, but maybe enabling dead lettering in the Pub/Sub pull subscription could also be a good option for monitoring failed messages.
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Ria
3 months ago
I agree with Tequila. It's important to monitor the messages that fail to be transformed and handle them accordingly.
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Letha
3 months ago
Option A seems like the way to go. I like the idea of using a side output to handle failed messages and monitor them separately.
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Tu
2 months ago
User 3: I agree. Monitoring and handling failed messages in a separate topic can help with troubleshooting and alerting.
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Ezekiel
2 months ago
User 2: Yes, that sounds like a good approach. It's important to have a way to track and handle failed messages effectively.
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Shay
3 months ago
User 1: Option A seems like the way to go. I like the idea of using a side output to handle failed messages and monitor them separately.
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Tequila
3 months ago
I think we should use an exception handling block in the Data Flow's DoFn code to push failed messages to a new Pub/Sub topic for monitoring.
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