Answer: C https://docs.aws.amazon.com/athena/latest/ug/what-is.html Amazon Athena is an interactive query service that makes it easy to analyze data directly in Amazon Simple Storage Service (Amazon S3) using standard SQL. With a few actions in the AWS Management Console, you can point Athena at your data stored in Amazon S3 and begin using standard SQL to run ad-hoc queries and get results in seconds.

Keyword: - Queries will be simple and will run on-demand. - Minimal changes to the existing architecture. A: Incorrect - We have to do 2 step. load all content to Redshift and run SQL query (This is simple query so we can you Athena, for complex query we will apply Redshit) B: Incorrect - Our query will be run on-demand so we don't need to use CloudWatch Logs to store the logs. C: Correct - This is simple query we can apply Athena directly on S3 D: Incorrect - This take 2 step: use AWS Glue to catalog the logs and use Spark to run SQL query

A. S3 Transfer Acceleration will do the required job A is a valid answer AmazonExams.com

C is correct answer. I took this test last week with the help of Itexamslab.com

Certifiedumps To meet the requirements with the least amount of operational overhead, the solutions architect should: C. Use Amazon Athena directly with Amazon S3 to run the queries as needed. Amazon Athena allows you to run SQL queries directly on data stored in Amazon S3 without the need for complex infrastructure or data loading processes, minimizing operational overhead.

AmazonExams.com (no discussion A ;)

C for sure

Using Amazon Athena with Amazon S3 is direct and efficient way for querying JSON log files with minimum operational overhead.

A, B, D operational overhead. C accept all requirement

Option A is correct Amazon Athena is an interactive query service provided by Amazon Web Services (AWS) that enables you to analyze data stored in Amazon S3 (Simple Storage Service) using standard SQL queries.

Answer should be C, Simple approach, Store logs in S3 and use Athena to query. Redshift will be costly approach.Cloudwatch does not store any data. So A and B ruled out.

S3 + Athena is simples approach

C seems right.

A. Despite this option can be valid, it implies a bit of operational overhead compared with other options. Additionally, there is no need to aggregate that change to the existing architecture because we are already working in S3, and using other storage services incurs unnecessary costs. B. To collect the logs, we use CloudTrail over CloudWatch. Running SQL queries from the Amazon CloudWatch console is not recommended for this use case, since it is more used for filtering. C. Correct answer. Athena integrates seamlessly with S3 and allows you to run simple SQL queries in no time. When working with Apache Spark or with SQL in S3, using this service is the best option. D. This option incurs elevated operational overhead. Glue is not used to catalog the logs. Analyzing logs with Spark on an EMR cluster is very common, but you can do it faster with the Athena service integrated with S3 directly.

Amazon Athena, because it provides the easiest way to run simple SQL service on a on-demand basis on an S3 bucket. The data is not complex so Redshift and EMR are a overhead or simply not suitable. CloudWatch does not have a console where you can run queries.

C seems to be fine

No need to build a server and it is on the fly