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Google Associate Cloud Engineer Exam - Topic 3 Question 100 Discussion

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?
B) Enable Log Analytics for the log bucket and create a linked dataset in BigQuery.
A) Develop SQL queries by using Gemini for Google Cloud.
C) Create a schema for the storage bucket and run SQL queries for the data in the bucket.
D) Export logs to a storage bucket and create an external view in BigQuery.

Google Associate Cloud Engineer Exam - 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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Peggie
7 months ago
B is the Google-recommended approach, no doubt about it!
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Laurel
8 months ago
A seems a bit off, I don't see how that fits in.
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Fidelia
8 months ago
Wait, can you really use Gemini for SQL queries? Sounds interesting!
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Malissa
8 months ago
I think D could work too, but not sure it's the best practice.
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Hermila
8 months ago
B is definitely the way to go!
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Gladys
9 months ago
Enabling Log Analytics sounds familiar, but I wonder if creating a linked dataset in BigQuery is necessary for analyzing logs effectively.
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Cheryl
9 months ago
I feel like developing SQL queries with Gemini could be useful, but I don't know if that's the best approach for this scenario.
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Corinne
9 months ago
I think exporting logs to a storage bucket and creating an external view in BigQuery was mentioned in a practice question, but I can't recall the details.
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Stevie
9 months ago
I remember we discussed using BigQuery for analyzing logs, but I'm not sure if enabling Log Analytics is the right step.
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Eladia
9 months ago
Okay, I think I've got it. Option B is the way to go - enabling Log Analytics and creating a linked dataset in BigQuery. That seems to be the most direct way to analyze the logs using SQL, just as the question asks.
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Alishia
9 months ago
Option A with Gemini for Google Cloud sounds interesting, but I'm not sure if that's the recommended approach here. I'll need to double-check the details on that.
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Ilene
9 months ago
Hmm, I'm a bit unsure about this one. I'm torn between options B and D. I'll need to review the details of each approach to decide which one is better.
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Ernestine
9 months ago
This seems straightforward - I think option B is the way to go, as it aligns with the Google-recommended practices mentioned in the question.
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Lamar
1 year 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
1 year 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
1 year ago
Yeah, option B definitely sounds like the way to go to efficiently analyze application logs in Cloud Logging.
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Jonell
1 year 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
1 year ago
That's true, option B does seem like the most straightforward way to analyze logs in Cloud Logging.
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Son
1 year 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
1 year 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
1 year ago
D) Export logs to a storage bucket and create an external view in BigQuery.
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Dominga
1 year ago
B) Enable Log Analytics for the log bucket and create a linked dataset in BigQuery.
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Markus
1 year ago
A) Develop SQL queries by using Gemini for Google Cloud.
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Delfina
1 year 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
1 year 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
1 year 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
1 year 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
1 year 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
1 year 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
2 years 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
2 years 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
1 year 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
1 year 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
1 year ago
I agree, option B seems like the best choice. It's efficient and follows Google-recommended practices.
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