A financial company has allocated an Amazon RDS MariaDB DB instance with large storage capacity to accommodate migration efforts. Post-migration, the company purged unwanted data from the instance. The company now want to downsize storage to save money. The solution must have the least impact on production and near-zero downtime.
Which solution would meet these requirements?

• A.Create a snapshot of the old databases and restore the snapshot with the required storage
• B.Create a new RDS DB instance with the required storage and move the databases from the old instances to the new instance using AWS DMS
• C.Create a new database using native backup and restore
• D.Create a new read replica and make it the primary by terminating the existing primary

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A company is about to launch a new product, and test databases must be re-created from production data. The company runs its production databases on an Amazon Aurora MySQL DB cluster. A Database Specialist needs to deploy a solution to create these test databases as quickly as possible with the least amount of administrative effort.
What should the Database Specialist do to meet these requirements?

• A.Restore a snapshot from the production cluster into test clusters
• B.Create logical dumps of the production cluster and restore them into new test clusters
• C.Use database cloning to create clones of the production cluster
• D.Add an additional read replica to the production cluster and use that node for testing

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An ecommerce company is using Amazon DynamoDB as the backend for its order-processing application.
The steady increase in the number of orders is resulting in increased DynamoDB costs. Order verification and reporting perform many repeated GetItem functions that pull similar datasets, and this read activity is contributing to the increased costs. The company wants to control these costs without significant development efforts.
How should a Database Specialist address these requirements?

• A.Use DynamoDB Accelerator to offload the reads
• B.Use an Amazon ElastiCache for Redis in front of DynamoDB to boost read performance
• C.Use AWS DMS to migrate data from DynamoDB to Amazon DocumentDB
• D.Use Amazon DynamoDB Streams and Amazon Kinesis Data Firehose to push the data into AmazonRedshift

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A company has a web-based survey application that uses Amazon DynamoDB. During peak usage, when survey responses are being collected, a Database Specialist sees the ProvisionedThroughputExceededException error.
What can the Database Specialist do to resolve this error? (Choose two.)

• A.Change the table to use Amazon DynamoDB Streams
• B.Change the table type to throughput optimized
• C.Purchase DynamoDB reserved capacity in the affected Region
• D.Change the table capacity mode to on-demand
• E.Increase the write capacity units for the specific table

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A company needs a data warehouse solution that keeps data in a consistent, highly structured format. The company requires fast responses for end-user queries when looking at data from the current year, and users must have access to the full 15-year dataset, when needed. This solution also needs to handle a fluctuating number incoming queries. Storage costs for the 100 TB of data must be kept low.
Which solution meets these requirements?

• A.Leverage an Amazon Redshift data warehouse solution using a dense storage instance type while keeping all the data on local Amazon Redshift storage. Provision enough instances to support high demand.
• B.Leverage an Amazon Redshift data warehouse solution using a dense storage instance to store the most recent data. Keep historical data on Amazon S3 and access it using the Amazon Redshift Spectrum layer. Provision enough instances to support high demand.
• C.Leverage an Amazon Redshift data warehouse solution using a dense storage instance to store the most recent data. Keep historical data on Amazon S3 and access it using the Amazon Redshift Spectrum layer. Enable Amazon Redshift Concurrency Scaling.
• D.Leverage an Amazon Redshift data warehouse solution using a dense storage instance to store the most recent data. Keep historical data on Amazon S3 and access it using the Amazon Redshift Spectrum layer. Leverage Amazon Redshift elastic resize.

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