A company plans to use AWS Database Migration Service (AWS DMS) to migrate its database from one Amazon EC2 instance to another EC2 instance as a full load task. The company wants the database to be inactive during the migration. The company will use a dms.t3.medium instance to perform the migration and will use the default settings for the migration.
Which solution will MOST improve the performance of the data migration?

• A.Increase the number of tables that are loaded in parallel.
• B.Drop all indexes on the source tables.
• C.Change the processing mode from the batch optimized apply option to transactional mode.
• D.Enable Multi-AZ on the target database while the full load task is in progress.

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A database specialist needs to review and optimize an Amazon DynamoDB table that is experiencing performance issues. A thorough investigation by the database specialist reveals that the partition key is causing hot partitions, so a new partition key is created. The database specialist must effectively apply this new partition key to all existing and new data.
How can this solution be implemented?

• A.Use Amazon EMR to export the data from the current DynamoDB table to Amazon S3. Then use Amazon EMR again to import the data from Amazon S3 into a new DynamoDB table with the new partition key.
• B.Use AWS DMS to copy the data from the current DynamoDB table to Amazon S3. Then import the DynamoDB table to create a new DynamoDB table with the new partition key.
• C.Use the AWS CLI to update the DynamoDB table and modify the partition key.
• D.Use the AWS CLI to back up the DynamoDB table. Then use the restore-table-from-backup command and modify the partition key.

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A company has a production environment running on Amazon RDS for SQL Server with an in-house web application as the front end. During the last application maintenance window, new functionality was added to the web application to enhance the reporting capabilities for management. Since the update, the application is slow to respond to some reporting queries.
How should the company identify the source of the problem?

• A.Enable RDS Performance Insights and determine which query is creating the problem. Request changes to the query to address the problem.
• B.Use AWS X-Ray deployed with Amazon RDS to track query system traces.
• C.Create a support request and work with AWS Support to identify the source of the issue.
• D.Install and configure Amazon CloudWatch Application Insights for Microsoft .NET and Microsoft SQL Server. Use a CloudWatch dashboard to identify the root cause.

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A ride-hailing application uses an Amazon RDS for MySQL DB instance as persistent storage for bookings. This application is very popular and the company expects a tenfold increase in the user base in next few months. The application experiences more traffic during the morning and evening hours.
This application has two parts:
An in-house booking component that accepts online bookings that directly correspond to simultaneous requests from users.
A third-party customer relationship management (CRM) component used by customer care representatives. The CRM uses queries to access booking data.
A database specialist needs to design a cost-effective database solution to handle this workload. Which solution meets these requirements?

• A.Use Amazon ElastiCache for Redis to accept the bookings. Associate an AWS Lambda function to capture changes and push the booking data to the RDS for MySQL DB instance used by the CRM.
• B.Use Amazon DynamoDB to accept the bookings. Enable DynamoDB Streams and associate an AWS Lambda function to capture changes and push the booking data to Amazon Athena, which is used by the CRM.
• C.Use Amazon DynamoDB to accept the bookings. Enable DynamoDB Streams and associate an AWS Lambda function to capture changes and push the booking data to an Amazon SQS queue. This triggers another Lambda function that pulls data from Amazon SQS and writes it to the RDS for MySQL DB instance used by the CRM.
• D.Use Amazon ElastiCache for Redis to accept the bookings. Associate an AWS Lambda function to capture changes and push the booking data to an Amazon Redshift database used by the CRM.

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A large IT hardware manufacturing company wants to deploy a MySQL database solution in the AWS Cloud. The solution should quickly create copies of the company's production databases for test purposes. The solution must deploy the test databases in minutes, and the test data should match the latest production data as closely as possible. Developers must also be able to make changes in the test database and delete the instances afterward.
Which solution meets these requirements?

• A.Leverage Amazon Aurora MySQL. Restore previous production DB instance snapshots into new test copies of Aurora MySQL DB clusters to allow them to make changes.
• B.Leverage Amazon RDS for MySQL with write-enabled replicas running on Amazon EC2. Create the test copies using a mysqidump backup from the RDS for MySQL DB instances and importing them into the new EC2 instances.
• C.Leverage Amazon RDS for MySQL. Use database cloning to create multiple developer copies of the production DB instance.
• D.Leverage Amazon Aurora MySQL. Use database cloning to create multiple test copies of the production DB clusters.

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