A developer needs to migrate an online retail application to AWS to handle an anticipated increase in traffic. The application currently runs on two servers: one server for the web application and another server for the database. The web server renders webpages and manages session state in memory. The database server hosts a MySQL database that contains order details. When traffic to the application is heavy, the memory usage for the web server approaches 100% and the application slows down considerably.

The developer has found that most of the memory increase and performance decrease is related to the load of managing additional user sessions. For the web server migration, the developer will use Amazon EC2 instances with an Auto Scaling group behind an Application Load Balancer.

Which additional set of changes should the developer make to the application to improve the application's performance?

A. Use an EC2 instance to host the MySQL database. Store the session data and the application data in the MySQL database.

B. Use Amazon ElastiCache for Memcached to store and manage the session data. Use an Amazon RDS for MySQL DB instance to store the application data.

C. Use Amazon ElastiCache for Memcached to store and manage the session data and the application data.

D. Use the EC2 instance store to manage the session data. Use an Amazon RDS for MySQL DB instance to store the application data.

A developer has written an AWS Lambda function. The function is CPU-bound. The developer wants to ensure that the function returns responses quickly. How can the developer improve the function's performance?

A. Increase the function's CPU core count.

B. Increase the function's memory.

C. Increase the function's reserved concurrency.

D. Increase the function's timeout.

A developer is creating an AWS Lambda function that searches for items from an Amazon DynamoDB table that contains customer contact information. The DynamoDB table items have the customer's email_address as the partition key and additional properties such as customer_type, name and job_title.

The Lambda function runs whenever a user types a new character into the customer_type text input. The developer wants the search to return partial matches of all the email_address property of a particular customer_type. The developer does not want to recreate the DynamoDB table.

What should the developer do to meet these requirements?

A. Add a global secondary index (GSI) to the DynamoDB table with customer_type as the partition key and email_address as the sort key. Perform a query operation on the GSI by using the begins_with key condition expression with the email_address property.

B. Add a global secondary index (GSI) to the DynamoDB table with email_address as the partition key and customer_type as the sort key. Perform a query operation on the GSI by using the begins_with key condition expression with the email_address property.

C. Add a local secondary index (LSI) to the DynamoDB table with customer_type as the partition key and email_address as the sort key. Perform a query operation on the LSI by using the begins_with key condition expression with the email_address property.

D. Add a local secondary index (LSI) to the DynamoDB table with job_title as the partition key and email_address as the sort key. Perform a query operation on the LSI by using the begins_with key condition expression with the email_address property.

An IT department uses Amazon S3 to store sensitive images. After more than 1 year, the company moves the images into archival storage. The company rarely accesses the images, but the company wants a storage solution that maximizes resiliency. The IT department needs access to the images that have been moved to archival storage within 24 hours.

Which solution will meet these requirements MOST cost-effectively?

A. Use S3 Standard-Infrequent Access (S3 Standard-IA) to store the images. Use S3 Glacier Deep Archive with standard retrieval to store and retrieve archived images.

B. Use S3 Standard-Infrequent Access (S3 Standard-IA) to store the images. Use S3 Glacier Deep Archive with bulk retrieval to store and retrieve archived images.

C. Use S3 Intelligent-Tiering to store the images. Use S3 Glacier Deep Archive with standard retrieval to store and retrieve archived images.

D. Use S3 One Zone-Infrequent Access (S3 One Zone-IA) to store the images. Use S3 Glacier Deep Archive with bulk retrieval to store and retrieve archived images.

A company runs an application on AWS. The company deployed the application on Amazon EC2 instances. The application stores data on Amazon Aurora.

The application recently logged multiple application-specific custom DECRYP_ERROR errors to Amazon CloudWatch logs. The company did not detect the issue until the automated tests that run every 30 minutes failed. A developer must

implement a solution that will monitor for the custom errors and alert a development team in real time when these errors occur in the production environment.

Which solution will meet these requirements with the LEAST operational overhead?

A. Configure the application to create a custom metric and to push the metric to CloudWatch. Create an AWS CloudTrail alarm. Configure the CloudTrail alarm to use an Amazon Simple Notification Service (Amazon SNS) topic to send notifications.

B. Create an AWS Lambda function to run every 5 minutes to scan the CloudWatch logs for the keyword DECRYP_ERROR. Configure the Lambda function to use Amazon Simple Notification Service (Amazon SNS) to send a notification.

C. Use Amazon CloudWatch Logs to create a metric filter that has a filter pattern for DECRYP_ERROR. Create a CloudWatch alarm on this metric for a threshold >=1. Configure the alarm to send Amazon Simple Notification Service (Amazon SNS) notifications.

D. Install the CloudWatch unified agent on the EC2 instance. Configure the application to generate a metric for the keyword DECRYP_ERROR errors. Configure the agent to send Amazon Simple Notification Service (Amazon SNS) notifications.