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The AWS Certified Solutions Architect - Professional (SAP-C02) certification is a highly sought-after credential for professionals who work with AWS. It validates your expertise in designing and deploying complex AWS systems, and demonstrates your commitment to staying up-to-date with the latest AWS technologies and best practices. If you are an experienced AWS professional looking to take your skills to the next level, the SAP-C02 Exam is the perfect way to do so.

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The AWS Certified Solutions Architect - Professional (SAP-C02) certification exam is an advanced-level exam designed for experienced AWS Solutions Architects working towards architecting complex AWS applications. AWS Certified Solutions Architect - Professional (SAP-C02) certification exam validates the candidate's ability to design and deploy scalable, highly available, and fault-tolerant systems on AWS. SAP-C02 Exam covers a broad range of topics, including advanced networking, security, cost optimization, and application design.

Amazon AWS Certified Solutions Architect - Professional (SAP-C02) Sample Questions (Q877-Q882):

NEW QUESTION # 877
A company has a web application that securely uploads pictures and videos to an Amazon S3 bucket. The company requires that only authenticated users are allowed to post content. The application generates a presigned URL that is used to upload objects through a browser interface. Most users are reporting slow upload times for objects larger than 100 MB.
What can a Solutions Architect do to improve the performance of these uploads while ensuring only authenticated users are allowed to post content?

A. Enable an S3 Transfer Acceleration endpoint on the S3 bucket. Use the endpoint when generating the presigned URL. Have the browser interface upload the objects to this URL using the S3 multipart upload API.
B. Configure an Amazon CloudFront distribution for the destination S3 bucket. Enable PUT and POST methods for the CloudFront cache behavior. Update the CloudFront origin to use an origin access identity (OAI). Give the OAI user s3:PutObject permissions in the bucket policy. Have the browser interface upload objects using the CloudFront distribution.
C. Set up an Amazon API Gateway with a regional API endpoint that has a resource as an S3 service proxy. Configure the PUT method for this resource to expose the S3 PutObject operation. Secure the API Gateway using an AWS Lambda authorizer. Have the browser interface use API Gateway instead of the presigned URL to upload API objects.
D. Set up an Amazon API Gateway with an edge-optimized API endpoint that has a resource as an S3 service proxy. Configure the PUT method for this resource to expose the S3 PutObject operation. Secure the API Gateway using a COGNITO_USER_POOLS authorizer. Have the browser interface use API Gateway instead of the presigned URL to upload objects.

Answer: A

Explanation:
Explanation: S3 Transfer Acceleration is a feature that enables fast, easy, and secure transfers of files over long distances between your client and an S3 bucket1. It works by leveraging the CloudFront edge network to route your requests to S3 over an optimized network path1. By using a Transfer Acceleration endpoint when generating a presigned URL, you can allow authenticated users to upload objects faster and more reliably2. Additionally, using the S3 multipart upload API can improve the performance of large object uploads by breaking them into smaller parts and uploading them in parallel3.
References:
S3 Transfer Acceleration
Using Transfer Acceleration with presigned URLs
Uploading objects using multipart upload API

NEW QUESTION # 878
A solutions architect is responsible (or redesigning a legacy Java application to improve its availability, data durability, and scalability. Currently, the application runs on a single high-memory Amazon EC2 instance. It accepts HTTP requests from upstream clients, adds them to an in-memory queue, and responds with a 200 status. A separate application thread reads items from the queue, processes them, and persists the results to an Amazon RDS MySQL instance. The processing time for each item takes 90 seconds on average, most of which is spent waiting on external service calls, but the application is written to process multiple items in parallel.
Traffic to this service is unpredictable. During periods of high load, items may sit in the internal queue for over an hour while the application processes the backlog. In addition, the current system has issues with availability and data loss if the single application node fails.
Clients that access this service cannot be modified. They expect to receive a response to each HTTP request they send within 10 seconds before they will time out and retry the request.
Which approach would improve the availability and durability of (he system while decreasing the processing latency and minimizing costs?

A. Modify the application to use Amazon DynamoDB instead of Amazon RDS. Configure Auto Scaling for the DynamoDB table. Deploy the application within an Auto Scaling group with a scaling policy based on CPU utilization. Back the in-memory queue with a memory-mapped file to an instance store volume and periodically write that file to Amazon S3.
B. Create an Amazon API Gateway REST API that uses Lambda proxy integration to pass requests to an AWS Lambda function. Migrate the core processing code to a Lambda function and write a wrapper class that provides a handler method that converts the proxy events to the internal application data model and invokes the processing module.
C. Create an Amazon API Gateway REST API that uses a service proxy to put items in an Amazon SOS queue. Extract the core processing code from the existing application and update it to pull items from Amazon SOS instead of an in-memory queue. Deploy the new processing application to smaller EC2 instances within an Auto Scaling group that scales dynamically based on the approximate number of messages in the Amazon SOS queue.
D. Update the application to use a Redis task queue instead of the in-memory queue. 8uild a Docker container image for the application. Create an Amazon ECS task definition that includes the application container and a separate container to host Redis. Deploy the new task definition as an ECS service using AWS Fargate, and enable Auto Scaling.

Answer: C

NEW QUESTION # 879
A company is refactoring its on-premises order-processing platform in the AWS Cloud. The platform includes a web front end that is hosted on a fleet of VMs RabbitMQ to connect the front end to the backend, and a Kubernetes cluster to run a containerized backend system to process the orders. The company does not want to make any major changes to the application Which solution will meet these requirements with the LEAST operational overhead?

A. Create a custom AWS Lambda runtime to mimic the web server environment Create an Amazon API Gateway API to replace the front-end web servers Set up Amazon MQ to replace the on-premises messaging queue Configure Amazon Elastic Kubernetes Service (Amazon EKS) to host the order-processing backend
B. Create an AMI of the web server VM Create an Amazon EC2 Auto Scaling group that uses the AMI and an Application Load Balancer Set up an Amazon Simple Queue Service (Amazon SQS) queue to replace the on-premises messaging queue Configure Amazon Elastic Kubernetes Service (Amazon EKS) to host the order-processing backend
C. Create an AMI of the web server VM Create an Amazon EC2 Auto Scaling group that uses the AMI and an Application Load Balancer Set up Amazon MQ to replace the on-premises messaging queue Install Kubernetes on a fleet of different EC2 instances to host the order-processing backend
D. Create an AMI of the web server VM Create an Amazon EC2 Auto Scaling group that uses the AMI and an Application Load Balancer Set up Amazon MQ to replace the on-premises messaging queue Configure Amazon Elastic Kubernetes Service (Amazon EKS) to host the order-processing backend

Answer: D

Explanation:
Explanation
https://aws.amazon.com/about-aws/whats-new/2020/11/announcing-amazon-mq-rabbitmq/

NEW QUESTION # 880
A company recently started hosting new application workloads in the AWS Cloud. The company is using Amazon EC2 instances, Amazon Elastic File System (Amazon EFS) file systems, and Amazon RDS DB instances.
To meet regulatory and business requirements, the company must make the following changes for data backups:
* Backups must be retained based on custom daily, weekly, and monthly requirements.
* Backups must be replicated to at least one other AWS Region immediately after capture.
* The backup solution must provide a single source of backup status across the AWS environment.
* The backup solution must send immediate notifications upon failure of any resource backup.
Which combination of steps will meet this requirement with the LEAST amount of operational overhead? (Select THREE.)

A. Set up RDS snapshots on each database.
B. Add an Amazon Simple Notification Service (Amazon SNS) topic to the backup plan to send a notification for finished jobs that have any status except BACKUP- JOB- COMPLETED.
C. Create an AWS Backup plan with a backup rule for each of the retention requirements.
D. Create an AWS Lambda function to replicate backups to another Region and send notification if a failure occurs.
E. Configure an AWS backup plan to copy backups to another Region.
F. Create an Amazon Data Lifecycle Manager (Amazon DLM) snapshot lifecycle policy for each of the retention requirements.

Answer: B,C,E

Explanation:
Cross region with AWS Backup: https://docs.aws.amazon.com/aws-backup/latest/devguide/cross-region-backup.html

NEW QUESTION # 881
A company runs a simple Linux application on Amazon EKS by using nodes of the M6i (general purpose) instance type. The company has an EC2 Instance Savings Plan for the M6i family that will expire soon.
A solutions architect must minimize the EKS compute costs when the Savings Plan expires.
Which combination of steps will meet this requirement? (Choose three.)

A. Purchase a new EC2 Instance Savings Plan for the newly selected x86_64 instance family.
B. Rebuild the application container images to support containers.
C. Migrate the EKS nodes to the most recent generation of Graviton-based instances.
D. Purchase a new EC2 Instance Savings Plan for the newly selected Graviton instance family.
E. Rebuild the application container images to support ARM64 architecture.
F. Replace the EKS nodes with the most recent generation of x86_64 instances.

Answer: C,D,E

Explanation:
Graviton uses ARM64, so your container images must be built for (or multi-arch include) ARM64.
Latest-gen Graviton instances (e.g., m7g/c7g/r7g) deliver lower $/vCPU than comparable x86, cutting EKS compute cost.
Lock in the discounted Graviton rates after migration to keep costs minimized.

NEW QUESTION # 882
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