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SAA-C03 Practice Test

Whether you're a beginner or brushing up on skills, our SAA-C03 practice exam is your key to success. Our comprehensive question bank covers all key topics, ensuring you’re fully prepared.


Page 27 out of 193 Pages

Topic 4: Exam Pool D

A company hosts multiple applications on AWS for different product lines. The applications use different compute resources, including Amazon EC2 instances and Application Load Balancers. The applications run in different AWS accounts under the same organization in AWS Organizations across multiple AWS Regions. Teams for each product line have tagged each compute resource in the individual accounts. The company wants more details about the cost for each product line from the consolidated billing feature in Organizations. Which combination of steps will meet these requirements? (Select TWO.)


A. Select a specific AWS generated tag in the AWS Billing console.


B. Select a specific user-defined tag in the AWS Billing console.


C. Select a specific user-defined tag in the AWS Resource Groups console.


D. Activate the selected tag from each AWS account.


E. Activate the selected tag from the Organizations management account.





B.
  Select a specific user-defined tag in the AWS Billing console.

E.
  Activate the selected tag from the Organizations management account.

Explanation: User-defined tags are key-value pairs that can be applied to AWS resources to categorize and track them. User-defined tags can also be used to allocate costs and create detailed billing reports in the AWS Billing console. To use user-defined tags for cost allocation, the tags must be activated from the Organizations management account, which is the root account that has full control over all the member accounts in the organization. Once activated, the user-defined tags will appear as columns in the cost allocation report, and can be used to filter and group costs by product line. This solution will meet the requirements with the least operational overhead, as it leverages the existing tagging strategy and does not require any code development or manual intervention.

A company runs applications on AWS that connect to the company's Amazon RDS database. The applications scale on weekends and at peak times of the year. The company wants to scale the database more effectively for its applications that connect to the database. Which solution will meet these requirements with the LEAST operational overhead?


A. Use Amazon DynamoDB with connection pooling with a target group configuration for the database. Change the applications to use the DynamoDB endpoint.


B. Use Amazon RDS Proxy with a target group for the database. Change the applications to use the RDS Proxy endpoint.


C. Use a custom proxy that runs on Amazon EC2 as an intermediary to the database. Change the applications to use the custom proxy endpoint.


D. Use an AWS Lambda function to provide connection pooling with a target group configuration for the database. Change the applications to use the Lambda function.





B.
  Use Amazon RDS Proxy with a target group for the database. Change the applications to use the RDS Proxy endpoint.

Explanation: Amazon RDS Proxy is a fully managed, highly available database proxy for Amazon Relational Database Service (RDS) that makes applications more scalable, more resilient to database failures, and more secure1. RDS Proxy allows applications to pool and share connections established with the database, improving database efficiency and application scalability2. RDS Proxy also reduces failover times for Aurora and RDS databases by up to 66% and enables IAM authentication and Secrets Manager integration for database access1. RDS Proxy can be enabled for most applications with no code changes2.

A company has a data ingestion workflow that consists the following:

An Amazon Simple Notification Service (Amazon SNS) topic for notifications about new data deliveries
An AWS Lambda function to process the data and record metadata

The company observes that the ingestion workflow fails occasionally because of network connectivity issues. When such a failure occurs, the Lambda function does not ingest the corresponding data unless the company manually reruns the job.
Which combination of actions should a solutions architect take to ensure that the Lambda function ingests all data in the future? (Select TWO.)


A. Configure the Lambda function In multiple Availability Zones.


B. Create an Amazon Simple Queue Service (Amazon SQS) queue, and subscribe It to me SNS topic.


C. Increase the CPU and memory that are allocated to the Lambda function.


D. Increase provisioned throughput for the Lambda function.


E. Modify the Lambda function to read from an Amazon Simple Queue Service (Amazon SQS) queue





B.
  Create an Amazon Simple Queue Service (Amazon SQS) queue, and subscribe It to me SNS topic.

E.
  Modify the Lambda function to read from an Amazon Simple Queue Service (Amazon SQS) queue

Explanation: To ensure that the Lambda function ingests all data in the future despite occasional network connectivity issues, the following actions should be taken:
Create an Amazon Simple Queue Service (SQS) queue and subscribe it to the SNS topic. This allows for decoupling of the notification and processing, so that even if the processing Lambda function fails, the message remains in the queue for further processing later.
Modify the Lambda function to read from the SQS queue instead of directly from SNS. This decoupling allows for retries and fault tolerance and ensures that all messages are processed by the Lambda function.

A company has multiple AWS accounts that use consolidated billing. The company runs several active high performance Amazon RDS for Oracle On-Demand DB instances for 90 days. The company's finance team has access to AWS Trusted Advisor in the consolidated billing account and all other AWS accounts. The finance team needs to use the appropriate AWS account to access the Trusted Advisor check recommendations for RDS. The finance team must review the appropriate Trusted Advisor check to reduce RDS costs. Which combination of steps should the finance team take to meet these requirements? (Select TWO.)


A. Use the Trusted Advisor recommendations from the account where the RDS instances are running.


B. Use the Trusted Advisor recommendations from the consolidated billing account to see all RDS instance checks at the same time.


C. Review the Trusted Advisor check for Amazon RDS Reserved Instance Optimization.


D. Review the Trusted Advisor check for Amazon RDS Idle DB Instances.


E. Review the Trusted Advisor check for Amazon Redshift Reserved Node Optimization.





B.
  Use the Trusted Advisor recommendations from the consolidated billing account to see all RDS instance checks at the same time.

C.
  Review the Trusted Advisor check for Amazon RDS Reserved Instance Optimization.

Explanation: B. Use the Trusted Advisor recommendations from the consolidated billing account to see all RDS instance checks at the same time. The consolidated billing account has access to all the other AWS accounts that use consolidated billing. Using the Trusted Advisor recommendations from the consolidated billing account will allow the finance team to see all RDS instance checks for all accounts at the same time. Review the Trusted Advisor check for Amazon RDS Reserved Instance Optimization. The Trusted Advisor check for Amazon RDS Reserved Instance Optimization provides recommendations for purchasing reserved instances to reduce RDS costs. By reviewing this check, the finance team can identify which RDS instances can be converted to reserved instances to save costs.

A company is running a popular social media website. The website gives users the ability to upload images to share with other users. The company wants to make sure that the images do not contain inappropriate content. The company needs a solution that minimizes development effort.
What should a solutions architect do to meet these requirements?


A. Use Amazon Comprehend to detect inappropriate content. Use human review for low- confidence predictions.


B. Use Amazon Rekognition to detect inappropriate content. Use human review for low- confidence predictions.


C. Use Amazon SageMaker to detect inappropriate content. Use ground truth to label low- confidence predictions.


D. Use AWS Fargate to deploy a custom machine learning model to detect inappropriate content. Use ground truth to label low-confidence predictions.





B.
  Use Amazon Rekognition to detect inappropriate content. Use human review for low- confidence predictions.


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