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Google Exam Associate Cloud Engineer Topic 3 Question 100 Discussion

Actual exam question for Google's Associate Cloud Engineer exam
Question #: 100
Topic #: 3
[All Associate Cloud Engineer Questions]

You use Cloud Logging lo capture application logs. You now need to use SOL to analyze the application logs in Cloud Logging, and you want to follow Google-recommended practices. What should you do?

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Suggested Answer: B

by Stephaine at Jan 14, 2025, 01:01 AM

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Lamar
4 months ago
Option D sounds like a lot of work, and I'm not a fan of extra steps. I'm with Delfina - let's keep it simple and go with option B. It's the way to go, no matter how you slice it.
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Lindsey
4 months ago
I'm going with option B. It's the Google-recommended practice, and who doesn't love a good linked dataset in BigQuery? Plus, it's probably the easiest way to avoid getting lost in a sea of storage buckets and external views.
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Cecilia
2 months ago
Yeah, option B definitely sounds like the way to go to efficiently analyze application logs in Cloud Logging.
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Jonell
3 months ago
I think I'll go with option B too. It just makes sense to enable Log Analytics and create a linked dataset in BigQuery.
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Tatum
3 months ago
That's true, option B does seem like the most straightforward way to analyze logs in Cloud Logging.
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Son
3 months ago
I'm going with option B. It's the Google-recommended practice, and who doesn't love a good linked dataset in BigQuery?
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Ellsworth
4 months ago
You know, I bet the person who came up with option C has never actually used Google Cloud before. Creating a schema for a storage bucket and running SQL queries? Sounds like a recipe for disaster.
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Mariko
3 months ago
D) Export logs to a storage bucket and create an external view in BigQuery.
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Dominga
3 months ago
B) Enable Log Analytics for the log bucket and create a linked dataset in BigQuery.
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Markus
3 months ago
A) Develop SQL queries by using Gemini for Google Cloud.
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Delfina
4 months ago
Option A? Seriously? Developing SQL queries using Gemini? That's like trying to use a calculator to do brain surgery. Let's keep it simple and go with option B.
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Lai
4 months ago
Hmm, I'm not sure. Option D seems like a viable choice too - exporting logs to a storage bucket and creating an external view in BigQuery could work. But I'll have to think about this one a bit more.
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Eric
3 months ago
User2: Option D could also work, exporting logs to a storage bucket and creating an external view in BigQuery.
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Ashton
4 months ago
User1: I think option B is the way to go - enabling Log Analytics for the log bucket and creating a linked dataset in BigQuery.
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Levi
4 months ago
I'm not sure, but I think option D) Export logs to a storage bucket and create an external view in BigQuery could also work.
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Theresia
4 months ago
I agree with Suzi, enabling Log Analytics and creating a linked dataset in BigQuery seems like the right approach.
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Suzi
5 months ago
I think the answer is B) Enable Log Analytics for the log bucket and create a linked dataset in BigQuery.
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Lindsey
5 months ago
I think option B is the way to go. Enabling Log Analytics and creating a linked dataset in BigQuery sounds like the most efficient approach here.
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Shalon
4 months ago
Definitely, option B is the way to go for analyzing application logs in Cloud Logging. It's the recommended practice by Google.
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Erinn
5 months ago
I think so too. Enabling Log Analytics and creating a linked dataset in BigQuery will make analyzing the logs easier.
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Odelia
5 months ago
I agree, option B seems like the best choice. It's efficient and follows Google-recommended practices.
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