A Database Specialist has migrated an on-premises Oracle database to Amazon Aurora PostgreSQL. The schema and the data have been migrated successfully. The on-premises database server was also being used to run database maintenance cron jobs written in Python to perform tasks including data purging and generating data exports. The logs for these jobs show that, most of the time, the jobs completed within 5 minutes, but a few jobs took up to 10 minutes to complete. These maintenance jobs need to be set up for Aurora PostgreSQL.
How can the Database Specialist schedule these jobs so the setup requires minimal maintenance and provides high availability?

1. A. Create cron jobs on an Amazon EC2 instance to run the maintenance jobs following the required schedule.
2. B. Connect to the Aurora host and create cron jobs to run the maintenance jobs following the required schedule.
3. C. Create AWS Lambda functions to run the maintenance jobs and schedule them with Amazon CloudWatch Events.
4. D. Create the maintenance job using the Amazon CloudWatch job scheduling plugin.

Correct Answer: C
https://docs.aws.amazon.com/AmazonCloudWatch/latest/events/Create-CloudWatch-Events-Scheduled-Rule.ht https://docs.aws.amazon.com/prescriptive-guidance/latest/patterns/schedule-jobs-for-amazon-rds-and-aurora-pos a job for data extraction or a job for data purging can easily be scheduled using cron. For these jobs, database credentials are typically either hard-coded or stored in a properties file. However, when you migrate to Amazon Relational Database Service (Amazon RDS) or Amazon Aurora PostgreSQL, you lose the ability to log in to the host instance to schedule cron jobs. This pattern describes how to use AWS Lambda and AWS Secrets Manager to schedule jobs for Amazon RDS and Aurora PostgreSQL databases after migration.
https://docs.aws.amazon.com/AmazonCloudWatch/latest/events/RunLambdaSchedule.html

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.)

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

Correct Answer: CD
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/switching.capacitymode.html

A company has an Amazon RDS Multi-AZ DB instances that is 200 GB in size with an RPO of 6 hours. To meet the company’s disaster recovery policies, the database backup needs to be copied into another Region. The company requires the solution to be cost-effective and operationally efficient.
What should a Database Specialist do to copy the database backup into a different Region?

1. A. Use Amazon RDS automated snapshots and use AWS Lambda to copy the snapshot into another Region
2. B. Use Amazon RDS automated snapshots every 6 hours and use Amazon S3 cross-Region replication to copy the snapshot into another Region
3. C. Create an AWS Lambda function to take an Amazon RDS snapshot every 6 hours and use a second Lambda function to copy the snapshot into another Region
4. D. Create a cross-Region read replica for Amazon RDS in another Region and take an automated snapshot of the read replica

Correct Answer: C
System snapshot can't fulfill 6 hours requirement. You need to control it by script https://aws.amazon.com/blogs/database/%C2%AD%C2%AD%C2%ADautomating-cross-region-cross-account

A single MySQL database was moved to Amazon Aurora by a business. The production data is stored in a database cluster in VPC PROD, whereas 12 testing environments are hosted in VPC TEST with the same AWS account. Testing has a negligible effect on the test data. The development team requires that each environment be updated nightly to ensure that each test database has daily production data.
Which migration strategy will be the quickest and least expensive to implement?

1. A. Run the master in Amazon Aurora MySQ
2. B. Create 12 clones in VPC_TEST, and script the clones to be deleted and re-created nightly.
3. C. Run the master in Amazon Aurora MySQ
4. D. Take a nightly snapshot, and restore it into 12 databases in VPC_TEST using Aurora Serverless.
5. E. Run the master in Amazon Aurora MySQ
6. F. Create 12 Aurora Replicas in VPC_TEST, and script the replicas to be deleted and re-created nightly.
7. G. Run the master in Amazon Aurora MySQL using Aurora Serverles
8. H. Create 12 clones in VPC_TEST, and script the clones to be deleted and re-created nightly.

Correct Answer: A
https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/Aurora.Managing.Clone.html

To meet new data compliance requirements, a company needs to keep critical data durably stored and readily accessible for 7 years. Data that is more than 1 year old is considered archival data and must automatically be moved out of the Amazon Aurora MySQL DB cluster every week. On average, around 10 GB of new data is added to the database every month. A database specialist must choose the most operationally efficient solution to migrate the archival data to Amazon S3.
Which solution meets these requirements?

1. A. Create a custom script that exports archival data from the DB cluster to Amazon S3 using a SQL view, then deletes the archival data from the DB cluste
2. B. Launch an Amazon EC2 instance with a weekly cron job to execute the custom script.
3. C. Configure an AWS Lambda function that exports archival data from the DB cluster to Amazon S3 using a SELECT INTO OUTFILE S3 statement, then deletes the archival data from the DB cluste
4. D. Schedule the Lambda function to run weekly using Amazon EventBridge (Amazon CloudWatch Events).
5. E. Configure two AWS Lambda functions: one that exports archival data from the DB cluster to Amazon S3 using the mysqldump utility, and another that deletes the archival data from the DB cluste
6. F. Schedule both Lambda functions to run weekly using Amazon EventBridge (Amazon CloudWatch Events).
7. G. Use AWS Database Migration Service (AWS DMS) to continually export the archival data from the DB cluster to Amazon S3. Configure an AWS Data Pipeline process to run weekly that executes a custom SQL script to delete the archival data from the DB cluster.

Correct Answer: B
https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/AuroraMySQL.Integrating.SaveIntoS3.htm