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Answer: Deploy the AWS Application Discovery Agent to each on-premises server. Configure Data Exploration in AWS Migration Hub. Use Amazon Athena to run predefined queries against the data in Amazon S3.
1. Explanation for Answer D: - Deploying the AWS Application Discovery Agent on each on-premises server is the correct approach because it automatically gathers detailed information about the servers, including CPU details, RAM usage, operating system information, and running processes. This agent is specifically designed for this purpose and is part of the AWS Application Discovery Service. - Configuring Data Exploration in AWS Migration Hub allows the company to analyze the collected data. Data Exploration enables users to visualize and analyze the data gathered by the Application Discovery Service. - Using Amazon Athena to run predefined queries against the data stored in Amazon S3 is the appropriate solution for querying and analyzing the data. Athena is a serverless, interactive query service that makes it easy to analyze data directly in S3 using standard SQL. This eliminates the need for complex ETL jobs and allows for direct querying of the data. 2. Other options are not suitable because: - Option A involves using the AWS Agentless Discovery Connector, which is not the best choice for gathering detailed server metrics as it is designed for agentless discovery and might not provide all the required information. - Option B suggests exporting only VM performance information and directly importing it into AWS Migration Hub, which might not cover all the necessary details and requires manual updates for missing information. - Option C proposes creating a custom script to gather server information and using the AWS CLI to store the data in AWS Migration Hub. This approach is less efficient and reliable compared to using the AWS Application Discovery Agent and might not provide the same level of detail and accuracy.
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A company is planning to migrate 1,000 on-premises servers to AWS. The servers run on several VMware clusters in the company’s data center. As part of the migration plan, the company wants to gather server metrics such as CPU details, RAM usage, operating system information, and running processes. The company then wants to query and analyze the data. Which solution will meet these requirements?
A
Deploy and configure the AWS Agentless Discovery Connector virtual appliance on the on-premises hosts. Configure Data Exploration in AWS Migration Hub. Use AWS Glue to perform an ETL job against the data. Query the data by using Amazon S3 Select.
B
Export only the VM performance information from the on-premises hosts. Directly import the required data into AWS Migration Hub. Update any missing information in Migration Hub. Query the data by using Amazon QuickSight.
C
Create a script to automatically gather the server information from the on- premises hosts. Use the AWS CLI to run the put-resource-attributes command to store the detailed server data in AWS Migration Hub. Query the data directly in the Migration Hub console.
D
Deploy the AWS Application Discovery Agent to each on-premises server. Configure Data Exploration in AWS Migration Hub. Use Amazon Athena to run predefined queries against the data in Amazon S3.