Amazon Web Services Updated SOA-C02 Exam Questions and Answers by orin

https://docs.aws.amazon.com/efs/latest/ug/encryption.html

Amazon EFS supports two forms of encryption for file systems, encryption of data in transit and encryption at rest. You can enable encryption of data at rest when creating an Amazon EFS file system. You can enable encryption of data in transit when you mount the file system.

A CloudFormation stack in the DELETE_FAILED state typically indicates that some resources could not be deleted. One common reason is that S3 buckets in the stack still contain objects.

Steps:

Identify the Failed Resources:

Open the AWS CloudFormation console.

Select the stack in the DELETE_FAILED state.

Check the "Events" tab to identify the resource(s) that caused the failure.

Delete S3 Objects:

Open the Amazon S3 console.

Navigate to the bucket(s) listed in the CloudFormation events.

Delete all objects in the bucket. You can use the S3 console, AWS CLI, or an S3 batch operation to delete the objects.

Retry Stack Deletion:

After clearing the S3 bucket(s), go back to the CloudFormation console.

Select the stack and choose "Delete" to retry the deletion process.

The VolumeQueueLength metric being high indicates the volume can’t process I/O operations fast enough, leading to performance degradation.

From Amazon EBS Performance Guide:

For gp3 volumes, performance can be adjusted by increasing IOPS or throughput independently of storage size.

The gp3 volume type allows provisioning up to:

16,000 IOPS

1,000 MB/s throughput

❌ Why the other options are incorrect:

A: ElastiCache is a caching layer and doesn't attach to EBS volumes.

B: Auto-Enabled IO is only relevant when IO is disabled due to volume-level issues, not performance.

D: Enhanced networking helps network performance, not disk I/O latency.

Aurora supports Auto Scaling of Aurora Replicas based on metrics like CPU utilization, which helps scale read capacity in read-heavy workloads.

From Aurora Auto Scaling documentation:

Aurora Auto Scaling automatically adds or removes Aurora Replicas based on CloudWatch metrics, such as CPU utilization.

Given that 95% of the workload is read, this is an ideal use case.