Free SAA-C03 Exam Braindumps (page: 3)

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A company is hosting a web application on AWS using a single Amazon EC2 instance that stores user-uploaded documents in an Amazon EBS volume. For better scalability and availability, the company duplicated the architecture and created a second EC2 instance and EBS volume in another Availability Zone, placing both behind an Application Load Balancer. After completing this change, users reported that, each time they refreshed the website, they could see one subset of their documents or the other, but never all of the documents at the same time.

What should a solutions architect propose to ensure users see all of their documents at once?

  1. Copy the data so both EBS volumes contain all the documents
  2. Configure the Application Load Balancer to direct a user to the server with the documents
  3. Copy the data from both EBS volumes to Amazon EFS. Modify the application to save new documents to Amazon EFS
  4. Configure the Application Load Balancer to send the request to both servers. Return each document from the correct server

Answer(s): C



A company uses NFS to store large video files in on-premises network attached storage. Each video file ranges in size from 1 MB to 500 GB. The total storage is 70 TB and is no longer growing. The company decides to migrate the video files to Amazon S3. The company must migrate the video files as soon as possible while using the least possible network bandwidth.

Which solution will meet these requirements?

  1. Create an S3 bucket. Create an IAM role that has permissions to write to the S3 bucket. Use the AWS CLI to copy all files locally to the S3 bucket.
  2. Create an AWS Snowball Edge job. Receive a Snowball Edge device on premises. Use the Snowball Edge client to transfer data to the device. Return the device so that AWS can import the data into Amazon S3.
  3. Deploy an S3 File Gateway on premises. Create a public service endpoint to connect to the S3 File Gateway. Create an S3 bucket. Create a new NFS file share on the S3 File Gateway. Point the new file share to the S3 bucket. Transfer the data from the existing NFS file share to the S3 File Gateway.
  4. Set up an AWS Direct Connect connection between the on-premises network and AWS. Deploy an S3 File Gateway on premises. Create a public virtual interface (VIF) to connect to the S3 File Gateway. Create an S3 bucket. Create a new NFS file share on the S3 File Gateway. Point the new file share to the S3 bucket. Transfer the data from the existing NFS file share to the S3 File Gateway.

Answer(s): B

Explanation:

Let's analyse this:

B: On a Snowball Edge device you can copy files with a speed of up to 100Gbps. 70TB will take around 5600 seconds, so very quickly, less than 2 hours. The downside is that it'll take between 4-6 working days to receive the device and then another 2-3 working days to send it back and for AWS to move the data onto S3 once it reaches them. Total time: 6-9 working days. Bandwidth used: 0.

C: File Gateway uses the Internet, so maximum speed will be at most 1Gbps, so it'll take a minimum of 6.5 days and you use 70TB of Internet bandwidth.

D: You can achieve speeds of up to 10Gbps with Direct Connect. Total time 15.5 hours and you will use 70TB of bandwidth. However, what's interesting is that the question does not specific what type of bandwidth? Direct Connect does not use your Internet bandwidth, as you will have a dedicate peer to peer connectivity between your on-prem and the AWS Cloud, so technically, you're not using your "public" bandwidth.

The requirements are a bit too vague but I think that B is the most appropriate answer, although D might also be correct if the bandwidth usage refers strictly to your public connectivity.



A company has an application that ingests incoming messages. Dozens of other applications and microservices then quickly consume these messages. The number of messages varies drastically and sometimes increases suddenly to 100,000 each second. The company wants to decouple the solution and increase scalability.

Which solution meets these requirements?

  1. Persist the messages to Amazon Kinesis Data Analytics. Configure the consumer applications to read and process the messages.
  2. Deploy the ingestion application on Amazon EC2 instances in an Auto Scaling group to scale the number of EC2 instances based on CPU metrics.
  3. Write the messages to Amazon Kinesis Data Streams with a single shard. Use an AWS Lambda function to preprocess messages and store them in Amazon DynamoDB. Configure the consumer applications to read from DynamoDB to process the messages.
  4. Publish the messages to an Amazon Simple Notification Service (Amazon SNS) topic with multiple Amazon Simple Queue Service (Amazon SOS) subscriptions. Configure the consumer applications to process the messages from the queues.

Answer(s): D



A company is migrating a distributed application to AWS. The application serves variable workloads. The legacy platform consists of a primary server that coordinates jobs across multiple compute nodes. The company wants to modernize the application with a solution that maximizes resiliency and scalability.

How should a solutions architect design the architecture to meet these requirements?

  1. Configure an Amazon Simple Queue Service (Amazon SQS) queue as a destination for the jobs. Implement the compute nodes with Amazon EC2 instances that are managed in an Auto Scaling group. Configure EC2 Auto Scaling to use scheduled scaling.
  2. Configure an Amazon Simple Queue Service (Amazon SQS) queue as a destination for the jobs. Implement the compute nodes with Amazon EC2 instances that are managed in an Auto Scaling group. Configure EC2 Auto Scaling based on the size of the queue.
  3. Implement the primary server and the compute nodes with Amazon EC2 instances that are managed in an Auto Scaling group. Configure AWS CloudTrail as a destination for the jobs. Configure EC2 Auto Scaling based on the load on the primary server.
  4. Implement the primary server and the compute nodes with Amazon EC2 instances that are managed in an Auto Scaling group. Configure Amazon EventBridge (Amazon CloudWatch Events) as a destination for the jobs. Configure EC2 Auto Scaling based on the load on the compute nodes.

Answer(s): B






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