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Question 809 - SAA-C03 discussion

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A company runs several websites on AWS for its different brands Each website generates tens of gigabytes of web traffic logs each day. A solutions architect needs to design a scalable solution to give the company's developers the ability to analyze traffic patterns across all the company's websites. This analysis by the developers will occur on demand once a week over the course of several months. The solution must support queries with standard SQL.

Which solution will meet these requirements MOST cost-effectively?

A.
Store the logs in Amazon S3. Use Amazon Athena for analysis.
Answers
A.
Store the logs in Amazon S3. Use Amazon Athena for analysis.
B.
Store the logs in Amazon RDS. Use a database client for analysis.
Answers
B.
Store the logs in Amazon RDS. Use a database client for analysis.
C.
Store the logs in Amazon OpenSearch Service. Use OpenSearch Service for analysis.
Answers
C.
Store the logs in Amazon OpenSearch Service. Use OpenSearch Service for analysis.
D.
Store the logs in an Amazon EMR cluster. Use a supported open-source framework for SQL-based analysis.
Answers
D.
Store the logs in an Amazon EMR cluster. Use a supported open-source framework for SQL-based analysis.
Suggested answer: A

Explanation:

This solution is the most cost-effective and scalable for analyzing large amounts of web traffic logs.

Amazon S3: Storing the logs in Amazon S3 is highly scalable, durable, and cost-effective. S3 is designed to handle large-scale data storage, which is ideal for storing tens of gigabytes of log data generated daily by multiple websites.

Amazon Athena: Athena is a serverless, interactive query service that allows you to analyze data in S3 using standard SQL. It works directly with the data stored in S3, so there's no need to load the data into a database, which saves on costs and reduces complexity. Athena charges based on the amount of data scanned by queries, making it a cost-effective solution for on-demand analysis that only occurs once a week.

Why Not Other Options?:

Option B (Amazon RDS): Storing logs in a relational database like Amazon RDS would be more expensive due to the storage and I/O costs associated with RDS. Additionally, it would require more management overhead.

Option C (Amazon OpenSearch Service): OpenSearch is a good option for full-text search and analytics on log data, but it might be more costly and complex to manage compared to the simplicity and cost-effectiveness of Athena for periodic SQL-based queries.

Option D (Amazon EMR): While EMR can handle large-scale data processing, it involves more operational overhead and might be overkill for the type of ad-hoc, SQL-based analysis required here. Additionally, EMR costs can be higher due to the need to maintain a cluster.

AWS

Reference:

Amazon S3 - Information on how to store and manage data in Amazon S3.

Amazon Athena - Documentation on using Amazon Athena for querying data stored in S3 using SQL.

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asked 16/09/2024
Martin Ng
43 questions
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