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NEW QUESTION 33
A company wants to host a global web application on AWS. It has the following design requirements.
* The access pattern must allow for latching data from multiple data sources.
* Minimize the of API calls.
* Keep page load times to within 50 ms.
* Provide user authentication and authorization and manage data access for different user personas (for example, administrator, manager, or engineer).
* Use a server less design
Which set of strategies should a solution architect use?

• A. Use Amazon CloudFront with Amazon S3 to host the web application Use Amazon API gateway to build the application APIs with AWS Lambda for the custom authorizer Authorize data access by performing user lookup in Simple AD.
• B. Use Amazon CloudFront with Amazon S3 to host the web application. Use AWS AppSync to build the application APIs. Use Amazon Cognito groups for each user persona Authorize data access by leveraging Amazon Cognito groups in AWS AppSync resolvers.
• C. Use Amazon CloudFront with AWS WAF to host the web application. Use AWS AppSync to build the application APIs. Use IAM groups for each user persona Authorize data access by leveraging IAM group in AWS AppSync resolvers.
• D. Use AWS Direct Connect with Amazon S3 to host the web application. Use Amazon API Gateway to build the application APIs. Use AWS Lambda for custom authentication and authorization. Authorize data access by leveraging IAM roles.

Answer: A

NEW QUESTION 34
A company is running a commercial Apache Hadoop cluster on Amazon EC2. This cluster is being used daily to query large files on Amazon S3. The data on Amazon S3 has been curated and does not require any additional transformations steps. The company is using a commercial business intelligence (BI) tool on Amazon EC2 to run queries against the Hadoop cluster and visualize the data.
The company wants to reduce or eliminate the overhead costs associated with managing the Hadoop cluster and the BI tool. The company would like to remove to a more cost-effective solution with minimal effort.
The visualization is simple and requires performing some basic aggregation steps only.
Which option will meet the company's requirements?

• A. Develop a script that uses Amazon Athena to query and analyze the files on Amazon S3. Then use Amazon QuickSight to connect to Athena and perform the visualization.
• B. Launch a transient Amazon EMR cluster daily and develop an Apache Hive script to analyze the files on Amazon S3. Shut down the Amazon EMR cluster when the job is complete. The use the Amazon QuickSight to connect to Amazon EMR and perform the visualization.
• C. Develop a stored procedure invoked from a MySQL database running on Amazon EC2 to analyze EC2 to analyze the files in Amazon S3. Then use a fast in-memory BL tool running on Amazon EC2 to visualize the data.
• D. Use a commercial extract, transform, load (ETL) tool that runs on Amazon EC2 to prepare the data for processing. Then switch to a faster and cheaper Bl tool that runs on Amazon EC2 to visualize the data from Amazon S3.

Answer: A

Explanation:
Explanation
https://docs.aws.amazon.com/quicksight/latest/user/create-a-data-set-athena.html
https://aws.amazon.com/athena/

NEW QUESTION 35
A company is moving a business-critical multi-tier application to AWS. The architecture consists of a desktop client application and server infrastructure. The server infrastructure resides in an on-premises data center that frequently fails to maintain the application uptime SLA of 99.95%. A solutions architect must re-architect the application to ensure that it can meet or exceed the SLA.
The application contains a PostgreSQL database running on a single virtual machine. The business logic and presentation layers are load balanced between multiple virtual machines. Remote users complain about slow load times while using this latency-sensitive application.
Which of the following will meet the availability requirements with little change to the application while improving user experience and minimizing costs?

• A. Migrate the database to a PostgreSQL database in Amazon EC2. Host the application and presentation layers in automatically scaled Amazon ECS containers behind an Application Load Balancer. Allocate an Amazon Workspaces Workspace for each end user to improve the user experience.
• B. Migrate the database to an Amazon RDS PostgreSQL Mulli-AZ configuration. Host the application and presentation layers in automatically scaled AWS Fargate containers behind a Network Load Balancer.
  Use Amazon ElastiCache to improve the user experience.
• C. Migrate the database to an Amazon RDS Aurora PostgreSQL configuration. Host the application and presentation layers in an Auto Scaling configuration on Amazon EC2 instances behind an Application Load Balancer. Use Amazon AppStream 2.0 to improve the user experience.
• D. Migrate the database to an Amazon Redshift cluster with at least two nodes. Combine and host the application and presentation layers in automatically scaled Amazon ECS containers behind an Application Load Balancer. Use Amazon CloudFront to improve the user experience.

Answer: B

NEW QUESTION 36
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