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SAA-C03 Practice Test


Page 9 out of 193 Pages

Topic 4: Exam Pool D

A company recently announced the deployment of its retail website to a global audience. The website runs on multiple Amazon EC2 instances behind an Elastic Load Balancer. The instances run in an Auto Scaling group across multiple Availability Zones. The company wants to provide its customers with different versions of content based on the devices that the customers use to access the website. Which combination of actions should a solutions architect take to meet these requirements? (Choose two.)


A. Configure Amazon CloudFront to cache multiple versions of the content.


B. Configure a host header in a Network Load Balancer to forward traffic to different instances.


C. Configure a Lambda@Edge function to send specific objects to users based on the User-Agent header.


D. Configure AWS Global Accelerator. Forward requests to a Network Load Balancer (NLB). Configure the NLB to set up host-based routing to different EC2 instances.


E. Configure AWS Global Accelerator. Forward requests to a Network Load Balancer (NLB). Configure the NLB to set up path-based routing to different EC2 instances.





A.
  Configure Amazon CloudFront to cache multiple versions of the content.

C.
  Configure a Lambda@Edge function to send specific objects to users based on the User-Agent header.

Explanation: For C: IMPROVED USER EXPERIENCE Lambda@Edge can help improve your users' experience with your websites and web applications across the world, by letting you personalize content for them without sacrificing performance. Real-time Image Transformation You can customize your users' experience by transforming images on the fly based on the user characteristics. For example, you can resize images based on the viewer's device type—mobile, desktop, or tablet. You can also cache the transformed images at CloudFront Edge locations to further improve performance when delivering images. https://aws.amazon.com/lambda/edge/

A company needs to store its accounting records in Amazon S3. The records must be immediately accessible for 1 year and then must be archived for an additional 9 years. No one at the company, including administrative users and root users, can be able to delete the records during the entire 10-year period. The records must be stored with maximum resiliency.
Which solution will meet these requirements?


A. Store the records in S3 Glacier for the entire 10-year period. Use an access control policy to deny deletion of the records for a period of 10 years.


B. Store the records by using S3 Intelligent-Tiering. Use an IAM policy to deny deletion of the records. After 10 years, change the IAM policy to allow deletion.


C. Use an S3 Lifecycle policy to transition the records from S3 Standard to S3 Glacier Deep Archive after 1 year. Use S3 Object Lock in compliance mode for a period of 10 years.


D. Use an S3 Lifecycle policy to transition the records from S3 Standard to S3 One Zone- Infrequent Access (S3 One Zone-IA) after 1 year. Use S3 Object Lock in governance mode for a period of 10 years.





C.
  Use an S3 Lifecycle policy to transition the records from S3 Standard to S3 Glacier Deep Archive after 1 year. Use S3 Object Lock in compliance mode for a period of 10 years.

Explanation: To meet the requirements of immediately accessible records for 1 year and then archived for an additional 9 years with maximum resiliency, we can use S3 Lifecycle policy to transition records from S3 Standard to S3 Glacier Deep Archive after 1 year. And to ensure that the records cannot be deleted by anyone, including administrative and root users, we can use S3 Object Lock in compliance mode for a period of 10 years. Therefore, the correct answer is option C.

A company recently signed a contract with an AWS Managed Service Provider (MSP) Partner for help with an application migration initiative. A solutions architect needs to share an Amazon Machine Image (AMI) from an existing AWS account with the MSP Partner's AWS account. The AMI is backed by Amazon Elastic Block Store (Amazon EBS) and uses a customer managed customer master key (CMK) to encrypt EBS volume snapshots.
What is the MOST secure way for the solutions architect to share the AMI with the MSP Partner's AWS account?


A. Make the encrypted AMI and snapshots publicly available. Modify the CMK's key policy to allow the MSP Partner's AWS account to use the key


B. Modify the launchPermission property of the AMI. Share the AMI with the MSP Partner's AWS account only. Modify the CMK's key policy to allow the MSP Partner's AWS account to use the key.


C. Modify the launchPermission property of the AMI Share the AMI with the MSP Partner's AWS account only. Modify the CMK's key policy to trust a new CMK that is owned by the MSP Partner for encryption.


D. Export the AMI from the source account to an Amazon S3 bucket in the MSP Partner's AWS account. Encrypt the S3 bucket with a CMK that is owned by the MSP Partner Copy and launch the AMI in the MSP Partner's AWS account.





B.
  Modify the launchPermission property of the AMI. Share the AMI with the MSP Partner's AWS account only. Modify the CMK's key policy to allow the MSP Partner's AWS account to use the key.

A company has an on-premises server that uses an Oracle database to process and store customer information The company wants to use an AWS database service to achieve higher availability and to improve application performance. The company also wants to offload reporting from its primary database system. Which solution will meet these requirements in the MOST operationally efficient way?


A. Use AWS Database Migration Service (AWS DMS) to create an Amazon RDS DB instance in multiple AWS Regions Point the reporting functions toward a separate DB instance from the primary DB instance.


B. Use Amazon RDS in a Single-AZ deployment to create an Oracle database Create a read replica in the same zone as the primary DB instance. Direct the reporting functions to the read replica.


C. Use Amazon RDS deployed in a Multi-AZ cluster deployment to create an Oracle database Direct the reporting functions to use the reader instance in the cluster deployment.


D. Use Amazon RDS deployed in a Multi-AZ instance deployment to create an Amazon Aurora database. Direct the reporting functions to the reader instances.





D.
  Use Amazon RDS deployed in a Multi-AZ instance deployment to create an Amazon Aurora database. Direct the reporting functions to the reader instances.

Explanation: Amazon Aurora is a fully managed relational database that is compatible with MySQL and PostgreSQL. It provides up to five times better performance than MySQL and up to three times better performance than PostgreSQL. It also provides high availability and durability by replicating data across multiple Availability Zones and continuously backing up data to Amazon S31. By using Amazon RDS deployed in a Multi-AZ instance deployment to create an Amazon Aurora database, the solution can achieve higher availability and improve application performance. Amazon Aurora supports read replicas, which are separate instances that share the same underlying storage as the primary instance. Read replicas can be used to offload read-only queries from the primary instance and improve performance. Read replicas can also be used for reporting functions2. By directing the reporting functions to the reader instances, the solution can offload reporting from its primary database system. Use AWS Database Migration Service (AWS DMS) to create an Amazon RDS DB instance in multiple AWS Regions Point the reporting functions toward a separate DB instance from the pri-mary DB instance. This solution will not meet the requirement of using an AWS database service, as AWS DMS is a service that helps users migrate databases to AWS, not a database service itself. It also involves creating multiple DB instances in different Regions, which may increase complexity and cost. Use Amazon RDS in a Single-AZ deployment to create an Oracle database Create a read replica in the same zone as the primary DB instance. Direct the reporting functions to the read replica. This solution will not meet the requirement of achieving higher availability, as a Single-AZ deployment does not provide failover protection in case of an Availability Zone outage. It also involves using Oracle as the database engine, which may not provide better performance than Aurora. Use Amazon RDS deployed in a Multi-AZ cluster deployment to create an Oracle database Di-rect the reporting functions to use the reader instance in the cluster deployment. This solution will not meet the requirement of improving application performance, as Oracle may not provide better performance than Aurora. It also involves using a cluster deployment, which is only supported for Aurora, not for Oracle.

A company's applications run on Amazon EC2 instances in Auto Scaling groups. The company notices that its applications experience sudden traffic increases on random days of the week The company wants to maintain application performance during sudden traffic increases. Which solution will meet these requirements MOST cost-effectively?


A. Use manual scaling to change the size of the Auto Scaling group.


B. Use predictive scaling to change the size of the Auto Scaling group.


C. Use dynamic scaling to change the size of the Auto Scaling group.


D. Use schedule scaling to change the size of the Auto Scaling group





C.
  Use dynamic scaling to change the size of the Auto Scaling group.

Explanation: Dynamic scaling is a type of autoscaling that automatically adjusts the number of EC2 instances in an Auto Scaling group based on demand or load. It uses CloudWatch alarms to trigger scaling actions when a specified metric crosses a threshold. It can scale out (add instances) or scale in (remove instances) as needed1. By using dynamic scaling, the solution can maintain application performance during sudden traffic increases most cost-effectively. Use manual scaling to change the size of the Auto Scaling group. This solution will not meet the requirement of maintaining application performance during sudden traffic increases, as manual scaling requires users to manually increase or decrease the number of instances through a CLI or console. It does not respond automatically to changes in demand or load2. Use predictive scaling to change the size of the Auto Scaling group. This solution will not meet the requirement of most cost-effectiveness, as predictive scaling uses machine learning and artificial intelligence tools to evaluate traffic loads and anticipate when more or fewer resources are needed. It performs scheduled scaling actions based on the prediction, which may not match the actual demand or load at any given time. Predictive scaling is more suitable for scenarios where there are predictable traffic patterns or known changes in traffic loads3. D. Use schedule scaling to change the size of the Auto Scaling group. This solution will not meet the requirement of maintaining application performance during sudden traffic increases, as schedule scaling performs scaling actions at specific times that users schedule. It does not respond automatically to changes in demand or load. Schedule scaling is more suitable for scenarios where there are predictable traffic drops or spikes at specific times of the day.


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