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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
9 months ago
B is the Google-recommended approach, no doubt about it!
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Laurel
9 months ago
A seems a bit off, I don't see how that fits in.
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Fidelia
10 months ago
Wait, can you really use Gemini for SQL queries? Sounds interesting!
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Malissa
10 months ago
I think D could work too, but not sure it's the best practice.
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Hermila
10 months ago
B is definitely the way to go!
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Gladys
10 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
11 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
11 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
11 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
11 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
11 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
11 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
11 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
2 years 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
2 years 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
2 years 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
2 years 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
2 years ago
B) Enable Log Analytics for the log bucket and create a linked dataset in BigQuery.
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Markus
2 years ago
A) Develop SQL queries by using Gemini for Google Cloud.
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Delfina
2 years 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
2 years 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
2 years 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
2 years 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
2 years 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
2 years 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
2 years 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
2 years 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
2 years ago
I agree, option B seems like the best choice. It's efficient and follows Google-recommended practices.
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