Exam AWS DevOps Engineer Professional topic 1 question 198 discussion

Exam question from Amazon's AWS DevOps Engineer Professional

Question #: 198
Topic #: 1

[All AWS DevOps Engineer Professional Questions]

A video-sharing company stores its videos in Amazon S3. The company has observed a sudden increase in video access requests, but the company does not know which videos are most popular. The company needs to identify the general access pattern for the video files. This pattern includes the number of users who access a certain file on a given day, as well as the number of pull requests for certain files.

How can the company meet these requirements with the LEAST amount of effort?

A. Activate S3 server access logging. Import the access logs into an Amazon Aurora database. Use an Aurora SQL query to analyze the access patterns.
B. Activate S3 server access logging. Use Amazon Athena to create an external table with the log files. Use Athena to create a SQL query to analyze the access patterns.
C. Invoke an AWS Lambda function for every S3 object access event. Configure the Lambda function to write the file access information, such as user, S3 bucket, and file key, to an Amazon Aurora database. Use an Aurora SQL query to analyze the access patterns.
D. Record an Amazon CloudWatch Logs log message for every S3 object access event. Configure a CloudWatch Logs log stream to write the file access information such as user. S3 bucket, and file key, to an Amazon Kinesis Data Analytics for SQL application. Perform a sliding window analysis.

Show Suggested Answer

Suggested Answer: B 🗳️

by CloudFloater at March 1, 2023, 5:48 p.m.

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Comments

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n_d1

1 year, 9 months ago

Selected Answer: B

https://docs.aws.amazon.com/AmazonS3/latest/userguide/using-s3-access-logs-to-identify-requests.html

upvoted 1 times

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easytoo

2 years ago

B for me.

upvoted 1 times

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saeidp

2 years, 3 months ago

Selected Answer: B

B is correct

upvoted 3 times

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CloudFloater

2 years, 3 months ago

Option A involves importing S3 server access logs into an Amazon Aurora database, which requires more effort than using Amazon Athena. Additionally, Aurora is a more complex and expensive option than Athena for this use case. Option C involves invoking an AWS Lambda function for every S3 object access event and storing the file access information in an Amazon Aurora database. This option requires more setup and ongoing management than using Amazon Athena, which is a simpler and more cost-effective solution. Option D involves recording a CloudWatch Logs log message for every S3 object access event and sending the log stream to an Amazon Kinesis Data Analytics for SQL application. This option requires additional setup and configuration, which makes it less straightforward and more time-consuming than using Amazon Athena. Additionally, using Kinesis Data Analytics for SQL may be overkill for this use case, as it is primarily designed for real-time streaming data analysis, which is not a requirement for the current scenario.

upvoted 4 times

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CloudFloater

2 years, 3 months ago

Selected Answer: B

Activating S3 server access logging and using Amazon Athena to create an external table with the log files is the easiest and most cost-effective way to analyze access patterns. This option requires minimal setup and allows for quick analysis of the access patterns with SQL queries. Additionally, Amazon Athena scales automatically to match the query load, so there is no need for additional infrastructure provisioning or management.

upvoted 4 times

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