Amazon AWS Certified Database Specialist

1.

A company is using 5 TB Amazon RDS DB instances and needs to maintain 5 years of monthly database backups for compliance purposes. A Database Administrator must provide Auditors with data within 24 hours. Which
solution will meet these requirements and is the MOST operationally efficient?

Create an AWS Lambda function to run on the first day of every month to take a manual RDS snapshot. Move the snapshot to the company's Amazon S3 bucket. Create an AWS Lambda function to run on the first day of every month to take a manual RDS snapshot. Create an RDS snapshot schedule from the AWS Management Console to take a snapshot every 30 days. Create an AWS Lambda function to run on the first day of every month to create an automated RDS snapshot.

2.

A financial company wants to store sensitive user data in an Amazon Aurora PostgreSQL DB cluster. The database will be accessed by multiple applications across the company. The company has mandated that all communications to the database be encrypted and the server identity must be validated. Any non-SSL-based connections should be disallowed access to the database.
Which solution addresses these requirements?

Set the rds.force_ssl=0 parameter in DB parameter groups. Download and use the Amazon RDS certificate bundle and configure the PostgreSQL connection string with sslmode=allow. Set the rds.force_ssl=1 parameter in DB parameter groups. Download and use the Amazon RDS certificate bundle and configure the PostgreSQL connection string with sslmode=disable. Set the rds.force_ssl=0 parameter in DB parameter groups. Download and use the Amazon RDS certificate bundle and configure the PostgreSQL connection string with sslmode=verify-ca. Set the rds.force_ssl=1 parameter in DB parameter groups. Download and use the Amazon RDS certificate bundle and configure the PostgreSQL connection string with sslmode=verify-full.

3.

A Database Specialist is performing a proof of concept with Amazon Aurora using a small instance to confirm a simple database behavior. When loading a large dataset and creating the index, the Database Specialist encounters the following error message from Aurora:
ERROR: cloud not write block 7507718 of temporary file: No space left on device
What is the cause of this error and what should the Database Specialist do to resolve this issue?

The scaling of Aurora storage cannot catch up with the data loading. The Database Specialist needs to modify the workload to load the data slowly. The scaling of Aurora storage cannot catch up with the data loading. The Database Specialist needs to enable Aurora storage scaling. The local storage used to store temporary tables is full. The Database Specialist needs to scale up the instance. The local storage used to store temporary tables is full. The Database Specialist needs to enable local storage scaling.

Amazon AWS Certified Database Specialist

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