AWS Certified Professional SAP-C02 Release Date

AWS Certified Solutions Architect - Professional Questions and Answers

Question 85

A company runs a highly available data collection application on Amazon EC2 in the eu-north-1 Region. The application collects data from end-user devices and writes records to an Amazon Kinesis data stream and a set of AWS Lambda functions that process the records. The company persists the output of the record processing to an Amazon S3 bucket in eu-north-1. The company uses the data in the S3 bucket as a data source for Amazon Athena.

The company wants to increase its global presence. A solutions architect must launch the data collection capabilities in the sa-east-1 and ap-northeast-1 Regions. The solutions architect deploys the application, the Kinesis data stream, and the Lambda functions in the two new Regions. The solutions architect keeps the S3 bucket in eu-north-1 to meet a requirement to centralize the data analysis.

During testing of the new setup, the solutions architect notices a significant lag on the arrival of data from the new Regions to the S3 bucket.

Which solution will improve this lag time the MOST?

Options:

In each of the two new Regions, set up the Lambda functions to run in a VPC. Set up an S3 gateway endpoint in that VPC.

Turn on S3 Transfer Acceleration on the S3 bucket in eu-north-1. Change the application to use the new S3 accelerated endpoint when the application uploads data to the S3 bucket.

Create an S3 bucket in each of the two new Regions. Set the application in each new Region to upload to its respective S3 bucket. Set up S3 Cross-Region Replication to replicate data to the S3 bucket in eu-north-1.

Increase the memory requirements of the Lambda functions to ensure that they have multiple cores available. Use the multipart upload feature when the application uploads data to Amazon S3 from Lambda.

Question 86

A company is moving a business-critical, multi-tier application to AWS. The architecture consists of a desktop client application and server infrastructure. The server infrastructure resides in an on-premises data center that frequently fails to maintain the application uptime SLA of 99.95%. A solutions architect must re-architect the application to ensure that it can meet or exceed the SLA.

The application contains a PostgreSQL database running on a single virtual machine. The business logic and presentation layers are load balanced between multiple virtual machines. Remote users complain about slow load times while using this latency-sensitive application.

Which of the following will meet the availability requirements with little change to the application while improving user experience and minimizing costs?

Options:

Migrate the database to a PostgreSQL database in Amazon EC2. Host the application and presentation layers in automatically scaled Amazon ECS containers behind an Application Load Balancer. Allocate an Amazon WorkSpaces Workspace for each end user to improve the user experience.

Migrate the database to an Amazon RDS Aurora PostgreSQL configuration. Host the application and presentation layers in an Auto Scaling configuration on Amazon EC2 instances behind an Application Load Balancer. Use Amazon AppStream 2.0 to improve the user experience.

Migrate the database to an Amazon RDS PostgreSQL Multi-AZ configuration. Host the application and presentation layers in automatically scaled AWS Fargate containers behind a Network Load Balancer. Use Amazon ElastiCache to improve the user experience.

Migrate the database to an Amazon Redshift cluster with at least two nodes. Combine and host the application and presentation layers in automatically scaled Amazon ECS containers behind an Application Load Balancer. Use Amazon CloudFront to improve the user experience.

Answer:

Explanation:

The application is business-critical with an SLA requirement of 99.95% uptime and is currently limited by an on-premises data center. The architecture includes a PostgreSQL database and separate business logic and presentation layers. Remote users experience high latency when accessing the application, which is latency-sensitive.

To meet or exceed a 99.95% SLA for the database while minimizing operational burden, a managed database service with built-in high availability is preferred. Amazon Aurora PostgreSQL-compatible editions provide high availability and durability by automatically replicating data across multiple Availability Zones in a Region. Aurora can offer higher availability and faster failover compared to self-managed databases on EC2, and offloads patching, backups, and maintenance.

For the application and presentation layers, running them on Amazon EC2 instances in an Auto Scaling group behind an Application Load Balancer preserves the basic architecture (stateless application servers behind a load balancer) while moving to a managed, highly available environment that can scale out and in automatically based on demand. This results in minimal changes to the application components and provides improved resilience compared to on-premises VMs.

Remote users experience slow load times because their desktop clients connect over higher-latency networks to the on-premises servers. By using Amazon AppStream 2.0, the application can be streamed from AWS to end users. AppStream 2.0 runs the desktop application close to the backend database and application servers within AWS, and streams only the display and input over the network. This significantly reduces the effect of latency between the user and the application backend, improving user experience, especially for latency-sensitive desktop applications, without requiring major changes to the application itself.

Option A uses a PostgreSQL database on EC2, which requires the customer to manage availability, backups, patching, and failover. This does not provide the same managed high-availability guarantees as Aurora or RDS Multi-AZ. It also suggests allocating a full Amazon WorkSpaces desktop per user, which can be more expensive and more complex than streaming only the application via AppStream 2.0.

Option C uses Amazon RDS for PostgreSQL with Multi-AZ configuration, which provides high availability and is a valid managed option. However, it runs the application and presentation layers on Fargate containers behind a Network Load Balancer. NLB is typically used for TCP-level load balancing and is better suited for protocols that require low-level handling, whereas HTTP/HTTPS web applications are commonly placed behind an Application Load Balancer, which provides advanced HTTP routing features. Also, ElastiCache can reduce database load and improve response times but does not directly solve the end-user network latency issue in a desktop client scenario.

Option D is incorrect because Amazon Redshift is a data warehouse service, not an operational PostgreSQL-compatible database for transaction processing. It is not appropriate for hosting the application’s primary relational database. CloudFront accelerates delivery of static and cached web content, not interactive desktop client-server traffic.

Therefore, migrating the database to Aurora PostgreSQL, running the application and presentation layers on EC2 Auto Scaling behind an Application Load Balancer, and using Amazon AppStream 2.0 to deliver the application to remote users (option B) meets the availability requirements, improves user experience, requires relatively little change to the application architecture, and minimizes operational costs compared to more complex or less-managed alternatives.

[References:AWS documentation on Amazon Aurora PostgreSQL for highly available, managed relational databases.AWS documentation on Amazon AppStream 2.0 for streaming desktop applications from AWS to end users to improve performance and reduce latency., , , , ]

Question 87

A financial company uses AWS Control Tower to govern multiple AWS accounts. The company must comply with data residency regulations. The regulations require customer data and backups to remain only in specific approved AWS Regions. Additionally, the company must retain control of the cryptographic root of trust. The company must use encryption keys in hardware security modules (HSMs) that the company operates in-country. The company needs a preventive control that blocks resource creation outside the approved Regions.

Which solution will meet these requirements with the LEAST operational overhead?

Options:

Use an AWS KMS external key store (XKS) backed by the company’s in-country HSMs for encryption. Apply an AWS Control Tower Region deny control to the relevant OUs to deny actions outside the approved Regions.

Use AWS KMS multi-Region keys for all encryption. Use AWS Config rules to detect resources that are created outside the approved Regions.

Use an AWS KMS custom key store backed by an AWS CloudHSM cluster deployed in one approved Region. Apply separate IAM policies in each account. Configure the policies to deny actions outside the approved Regions by using the aws:RequestedRegion condition key.

Use standard AWS KMS customer managed keys for encryption. Apply an AWS Control Tower Region deny control to the relevant OUs to deny actions outside the approved Regions.

Question 88

A video processing company has an application that downloads images from an Amazon S3 bucket, processes the images, stores a transformed image in a second S3 bucket, and updates metadata about the image in an Amazon DynamoDB table. The application is written in Node.js and runs by using an AWS Lambda function. The Lambda function is invoked when a new image is uploaded to Amazon S3.

The application ran without incident for a while. However, the size of the images has grown significantly. The Lambda function is now failing frequently with timeout errors. The function timeout is set to its maximum value. A solutions architect needs to refactor the application’s architecture to prevent invocation failures. The company does not want to manage the underlying infrastructure.

Which combination of steps should the solutions architect take to meet these requirements? (Choose two.)

Options:

Modify the application deployment by building a Docker image that contains the application code. Publish the image to Amazon Elastic Container Registry (Amazon ECR).

Create a new Amazon Elastic Container Service (Amazon ECS) task definition with a compatibility type of AWS Fargate. Configure the task definition to use the new image in Amazon Elastic Container Registry (Amazon ECR). Adjust the Lambda function to invoke an ECS task by using the ECS task definition when a new file arrives in Amazon S3.

Create an AWS Step Functions state machine with a Parallel state to invoke the Lambda function. Increase the provisioned concurrency of the Lambda function.

Create a new Amazon Elastic Container Service (Amazon ECS) task definition with a compatibility type of Amazon EC2. Configure the task definition to use the new image in Amazon Elastic Container Registry (Amazon ECR). Adjust the Lambda function to invoke an ECS task by using the ECS task definition when a new file arrives in Amazon S3.

Modify the application to store images on Amazon Elastic File System (Amazon EFS) and to store metadata on an Amazon RDS DB instance. Adjust the Lambda function to mount the EFS file share.

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AWS Certified Professional SAP-C02 Release Date

AWS Certified Solutions Architect - Professional Questions and Answers

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