Free AWS-CERTIFIED-SOLUTIONS-ARCHITECT-ASSOCIATE-SAA-C03 Amazon AWS-CERTIFIED-SOLUTIONS-ARCHITECT-ASSOCIATE-SAA-C03 Practice Test Question - Page 18

Question 52 (Topic 1)

A company runs container applications by using Amazon Elastic Kubernetes Service (Amazon EKS). The company's workload is not consistent throughout the day. The company wants Amazon EKS to scale in and out according to the workload. Which combination of steps will meet these requirements with the LEAST operational overhead? (Choose two.)

Select an option, then click Submit answer.

○ Use an AWS Lambda function to resize the EKS cluster.
○ Use the Kubernetes Metrics Server to activate horizontal pod autoscaling.
○ Use the Kubernetes Cluster Autoscaler to manage the number of nodes in the cluster.
○ Use Amazon API Gateway and connect it to Amazon EKS.
○ Use AWS App Mesh to observe network activity.

Reference / correct answer:

Use the Kubernetes Metrics Server to activate horizontal pod autoscaling.

Most accepted answer: B. Use the Kubernetes Metrics Server to activate horizontal pod autoscaling.

Community votes: B=5, C=5

Selected Answer: BC B and C are the correct options. Using the Kubernetes Metrics Server (B) enables horizontal pod autoscaling to dynamically scale pods based on CPU/memory usage. This allows scaling at the application tier level. The Kubernetes Cluster Autoscaler (C) automatically adjusts the number of nodes in the EKS cluster in response to pod resource requirements and events. This allows scaling at the infrastructure level. upvoted 8 times

Selected Answer: BC This is pretty straight forward. Use the Kubernetes Metrics Server to activate horizontal pod autoscaling. Use the Kubernetes Cluster Autoscaler to manage the number of nodes in the cluster. upvoted 5 times

K8S Metrics Server and Autoscaler => B and C upvoted 4 times

Selected Answer: BC Kubernetes Metrics Server https://docs.aws.amazon.com/eks/latest/userguide/metrics-server.html AWS Autoscaler https://docs.aws.amazon.com/eks/latest/userguide/autoscaling.html and https://github.com/kubernetes/autoscaler/blob/master/cluster-autoscaler/cloudprovider/aws/README.md upvoted 4 times

Selected Answer: BC By combining the Kubernetes Cluster Autoscaler (option C) to manage the number of nodes in the cluster and enabling horizontal pod autoscaling (option B) with the Kubernetes Metrics Server, you can achieve automatic scaling of your EKS cluster and container applications based on workload demand. This approach minimizes operational overhead as it leverages built-in Kubernetes functionality and automation mechanisms. upvoted 5 times

Question 53 (Topic 1)

A company is migrating its workloads to AWS. The company has transactional and sensitive data in its databases. The company wants to use AWS Cloud solutions to increase security and reduce operational overhead for the databases. Which solution will meet these requirements?

Select an option, then click Submit answer.

○ Migrate the databases to Amazon EC2. Use an AWS Key Management Service (AWS KMS) AWS managed key for encryption.
○ Migrate the databases to Amazon RDS Configure encryption at rest.
○ Migrate the data to Amazon S3 Use Amazon Macie for data security and protection
○ Migrate the database to Amazon RDS. Use Amazon CloudWatch Logs for data security and protection.

Reference / correct answer:

Migrate the databases to Amazon RDS Configure encryption at rest.

Most accepted answer: B. Migrate the databases to Amazon RDS Configure encryption at rest.

Community votes: B=6

B is the answer Why not C - Option C suggests migrating the data to Amazon S3 and using Amazon Macie for data security and protection. While Amazon Macie provides advanced security features for data in S3, it may not be directly applicable or optimized for databases, especially for transactional and sensitive data. Amazon RDS provides a more suitable environment for managing databases. upvoted 11 times

Selected Answer: B B. Migrate the databases to Amazon RDS Configure encryption at rest. Looks like best option upvoted 5 times

Selected Answer: B S3 and Macie works too. However, the question mentioned about transactional data. RDS is much better for running transactional workloads. Thus, RDS is the correct answer here. upvoted 2 times

Selected Answer: B A: Operational overhead of EC2 and whatever DB is running on it C: Macie is not for data security, it's for identifying PII and sensitive data D: CloudWatch is for cloud events and does not secure databases B: RDS is managed so least operational overhead. Encryption at rest means security upvoted 3 times allanm 11 months, 3 weeks ago Macie is actually used to protect sensitive data. It's just that C cannot be used because the data resides in databases and unless you have a service to migrate from database to S3, this won'twork upvoted 1 times ...

Macie is actually used to protect sensitive data. It's just that C cannot be used because the data resides in databases and unless you have a service to migrate from database to S3, this won'twork upvoted 1 times

Question 54 (Topic 1)

A media company uses an Amazon CloudFront distribution to deliver content over the internet. The company wants only premium customers to have access to the media streams and file content. The company stores all content in an Amazon S3 bucket. The company also delivers content on demand to customers for a specific purpose, such as movie rentals or music downloads. Which solution will meet these requirements?

Select an option, then click Submit answer.

○ Generate and provide S3 signed cookies to premium customers.
○ Generate and provide CloudFront signed URLs to premium customers.
○ Use origin access control (OAC) to limit the access of non-premium customers.
○ Generate and activate field-level encryption to block non-premium customers.

Free AWS-CERTIFIED-SOLUTIONS-ARCHITECT-ASSOCIATE-SAA-C03 – Amazon AWS-CERTIFIED-SOLUTIONS-ARCHITECT-ASSOCIATE-SAA-C03 Practice Test Question