Exam AWS Certified Solutions Architect - Professional SAP-C02 topic 1 question 46 discussion

The correct answer is 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. Here is why the other choices are not correct: 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. - AWS Agentless Discovery Connector will help in discovering and inventory servers but it does not provide the same level of detailed metrics as the AWS Application Discovery Agent, it also does not cover process information.

Choosing between A and D. For A, how can S3 select query?

A is correct

If precise information about each running Process is required, it is necessary to consider using Agent-based Discovery.

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.

D for sure

see https://docs.aws.amazon.com/application-discovery/latest/userguide/what-is-appdiscovery.html for VMs hosted on VMware, you can use both the Agentless Collector and Discovery Agent to perform discovery simultaneously. Agentless Collector captures system performance information and resource utilization for each VM running in the vCenter, regardless of what operating system is in use. However, it cannot “look inside” each of the VMs, and as such, cannot figure out what processes are running on each VM nor what network connections exist. Therefore, if you need this level of detail and want to take a closer look at some of your existing VMs in order to assist in planning your migration, you can install the Discovery Agent on an as-needed basis.

D is correct

Definetely A https://docs.aws.amazon.com/application-discovery/latest/userguide/agentless-collector-data-collected-vmware.html Vmware supports agentless connector with AWS, and data can be imported ove Migration Hub

Option D is the most efficient and streamlined solution for the requirements. Deploying the AWS Application Discovery Agent on each on-premises server allows for detailed collection of server metrics, including CPU usage, RAM usage, operating system details, and running processes. By configuring Data Exploration in AWS Migration Hub, the collected data can be analyzed and queried effectively. Using Amazon Athena for querying enables powerful SQL-based exploration of the data stored in Amazon S3, offering a flexible and scalable way to analyze the migration readiness and planning data. It is not option C because, Option C involves creating a custom script to gather server information and using the AWS CLI to store data in AWS Migration Hub. While this approach could potentially work, it requires significant manual effort to develop, deploy, and maintain the scripts across 1,000 servers, which is not ideal for minimizing operational overhead.

Not A - as AWS Agentless Discovery Connector does not provide processes visibility Not B - as Migration Hub Import functionality does not support process datahttps://docs.aws.amazon.com/cli/latest/reference/mgh/put-resource-attributes.html, also I do not see how to query with QuickSight as there is not direct integration with Migration Hub to my knowledge Not C - as it seems that put-resource-attributes command does not support process data https://docs.aws.amazon.com/cli/latest/reference/mgh/put-resource-attributes.html D is correct as Discovery Agent collects the required data including processes, Data Exploration in Migration Hub allows to use Amazon Athena and comes with pre-defined queries as well. https://docs.aws.amazon.com/application-discovery/latest/userguide/explore-data.html

https://docs.aws.amazon.com/application-discovery/latest/userguide/explore-data.html

The agent-based collector can collect data related to running processes which is not available to the Agentless Collector. Check out for yourself in the FAQs: https://aws.amazon.com/application-discovery/faqs/

As far as i learned for VM based envs we can go with agentless. And we can use a OVA image via collect the metrics and so on. im going with A . https://docs.aws.amazon.com/application-discovery/latest/userguide/agentless-data-collected.html

Answer: D The requirement: "the company wants to gather server metrics such as CPU details, RAM usage, operating system information, and running processes." From https://aws.amazon.com/application-discovery/faqs/: === AWS Application Discovery Service Discovery Agent Q: What data does the AWS Application Discovery Service Discovery Agent capture? The Discovery Agent captures system configuration, system performance, running processes, and details of the network connections between systems.

I prefer D

Correct A. D uses agent-based discovery, which requires installing an agent on each on-premises server. This can be cumbersome and intrusive for a large number of servers. It also does not explain how to use AWS Glue to perform an ETL job against the data.