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A company uses a service to collect metadata from applications that the company hosts on premises. Consumer devices such as TVs and internet radios access the applications. Many older devices do not support certain HTTP headers and exhibit errors when these headers are present in responses. The company has configured an on-premises load balancer to remove the unsupported headers from responses sent to older devices, which the company identified by the User-Agent headers. The company wants to migrate the service to AWS, adopt serverless technologies, and retain the ability to support the older devices. The company has already migrated the applications into a set of AWS Lambda functions. Which solution will meet these requirements?
A company is planning to store a large number of archived documents and make the documents available to employees through the corporate intranet. Employees will access the system by connecting through a client VPN service that is attached to a VPC. The data must not be accessible to the public. The documents that the company is storing are copies of data that is held on physical media elsewhere. The number of requests will be low. Availability and speed of retrieval are not concerns of the company. Which solution will meet these requirements at the LOWEST cost?
A financial services company runs a complex, multi-tier application on Amazon EC2 instances and AWS Lambda functions. The application stores temporary data in Amazon S3. The S3 objects are valid for only 45 minutes and are deleted after 24 hours. The company deploys each version of the application by launching an AWS CloudFormation stack. The stack creates all resources that are required to run the application. When the company deploys and validates a new application version, the company deletes the CloudFormation stack of the old version. The company recently tried to delete the CloudFormation stack of an old application version, but the operation failed. An analysis shows that CloudFormation failed to delete an existing S3 bucket. A solutions architect needs to resolve this issue without making major changes to the application's architecture. Which solution meets these requirements?
A company uses AWS Organizations for a multi-account setup in the AWS Cloud. The company's finance team has a data processing application that uses AWS Lambda and Amazon DynamoDB. The company's marketing team wants to access the data that is stored in the DynamoDB table. The DynamoDB table contains confidential data. The marketing team can have access to only specific attributes of data in the DynamoDB table. The fi-nance team and the marketing team have separate AWS accounts. What should a solutions architect do to provide the marketing team with the appropriate access to the DynamoDB table?
A company hosts a Git repository in an on-premises data center. The company uses webhooks to invoke functionality that runs in the AWS Cloud. The company hosts the webhook logic on a set of Amazon EC2 instances in an Auto Scaling group that the company set as a target for an Application Load Balancer (ALB). The Git server calls the ALB for the configured webhooks. The company wants to move the solution to a serverless architecture. Which solution will meet these requirements with the LEAST operational overhead?
A company is running an application on several Amazon EC2 instances in an Auto Scaling group behind an Application Load Balancer. The load on the application varies throughout the day, and EC2 instances are scaled in and out on a regular basis. Log files from the EC2 instances are copied to a central Amazon S3 bucket every 15 minutes. The security team discovers that log files are missing from some of the terminated EC2 instances. Which set of actions will ensure that log files are copied to the central S3 bucket from the terminated EC2 instances?
A company runs a new application as a static website in Amazon S3. The company has deployed the application to a production AWS account and uses Amazon CloudFront to deliver the website. The website calls an Amazon API Gateway REST API. An AWS Lambda function backs each API method. The company wants to create a CSV report every 2 weeks to show each API Lambda function’s recommended configured memory, recommended cost, and the price difference between current configurations and the recommendations. The company will store the reports in an S3 bucket. Which solution will meet these requirements with the LEAST development time?
An events company runs a ticketing platform on AWS. The company's customers configure and schedule their events on the platform The events result in large increases of traffic to the platform The company knows the date and time of each customer's events The company runs the platform on an Amazon Elastic Container Service (Amazon ECS) cluster The ECS cluster consists of Amazon EC2 On-Demand Instances that are in an Auto Scaling group. The Auto Scaling group uses a predictive scaling policy The ECS cluster makes frequent requests to an Amazon S3 bucket to download ticket assets The ECS cluster and the S3 bucket are in the same AWS Region and the same AWS account Traffic between the ECS cluster and the S3 bucket flows across a NAT gateway The company needs to optimize the cost of the platform without decreasing the platform's availability Which combination of steps will meet these requirements? (Select TWO)
A software as a service (SaaS) company has developed a multi-tenant environment. The company uses Amazon DynamoDB tables that the tenants share tor the storage layer. The company uses AWS Lambda functions for the application services. The company wants to offer a tiered subscription model that is based on resource consumption by each tenant Each tenant is identified by a unique tenant ID that is sent as part of each request to the Lambda functions The company has created an AWS Cost and Usage Report (AWS CUR) in an AWS account The company wants to allocate the DynamoDB costs to each tenant to match that tenant's resource consumption Which solution will provide a granular view of the DynamoDB cost for each tenant with the LEAST operational effort?
A company has a serverless application comprised of Amazon CloudFront, Amazon API Gateway, and AWS Lambda functions. The current deployment process of the application code is to create a new version number of the Lambda function and run an AWS CLI script to update. If the new function version has errors, another CLI script reverts by deploying the previous working version of the function. The company would like to decrease the time to deploy new versions of the application logic provided by the Lambda functions, and also reduce the time to detect and revert when errors are identified. How can this be accomplished?

Question 445 - SAP-C02 discussion

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A company has an application that analyzes and stores image data on premises The application receives millions of new image files every day Files are an average of 1 MB in size The files are analyzed in batches of 1 GB When the application analyzes a batch the application zips the images together The application then archives the images as a single file in an on-premises NFS server for long-term storage

The company has a Microsoft Hyper-V environment on premises and has compute capacity available The company does not have storage capacity and wants to archive the images on AWS The company needs the ability to retrieve archived data within t week of a request.

The company has a 10 Gbps AWS Direct Connect connection between its on-premises data center and AWS. The company needs to set bandwidth limits and schedule archived images to be copied to AWS dunng non-business hours.

Which solution will meet these requirements MOST cost-effectively?

A.
Deploy an AWS DataSync agent on a new GPU-based Amazon EC2 instance Configure the DataSync agent to copy the batch of files from the NFS on-premises server to Amazon S3 Glacier Instant Retrieval After the successful copy delete the data from the on-premises storage
Answers
A.
Deploy an AWS DataSync agent on a new GPU-based Amazon EC2 instance Configure the DataSync agent to copy the batch of files from the NFS on-premises server to Amazon S3 Glacier Instant Retrieval After the successful copy delete the data from the on-premises storage
B.
Deploy an AWS DataSync agent as a Hyper-V VM on premises Configure the DataSync agent to copy the batch of files from the NFS on-premises server to Amazon S3 Glacier Deep Archive After the successful copy delete the data from the on-premises storage
Answers
B.
Deploy an AWS DataSync agent as a Hyper-V VM on premises Configure the DataSync agent to copy the batch of files from the NFS on-premises server to Amazon S3 Glacier Deep Archive After the successful copy delete the data from the on-premises storage
C.
Deploy an AWS DataSync agent on a new general purpose Amazon EC2 instance Configure the DataSync agent to copy the batch of files from the NFS on-premises server to Amazon S3 Standard After the successful copy deletes the data from the on-premises storage Create an S3 Lifecycle rule to transition objects from S3 Standard to S3 Glacier Deep Archive after 1 day
Answers
C.
Deploy an AWS DataSync agent on a new general purpose Amazon EC2 instance Configure the DataSync agent to copy the batch of files from the NFS on-premises server to Amazon S3 Standard After the successful copy deletes the data from the on-premises storage Create an S3 Lifecycle rule to transition objects from S3 Standard to S3 Glacier Deep Archive after 1 day
D.
Deploy an AWS Storage Gateway Tape Gateway on premises in the Hyper-V environment Connect the Tape Gateway to AWS Use automatic tape creation Specify an Amazon S3 Glacier Deep Archive pool Eject the tape after the batch of images is copied
Answers
D.
Deploy an AWS Storage Gateway Tape Gateway on premises in the Hyper-V environment Connect the Tape Gateway to AWS Use automatic tape creation Specify an Amazon S3 Glacier Deep Archive pool Eject the tape after the batch of images is copied
Suggested answer: B

Explanation:

Deploy DataSync Agent:

Install the AWS DataSync agent as a VM in your Hyper-V environment. This agent facilitates the data transfer between your on-premises storage and AWS.

Configure Source and Destination:

Set up the source location to point to your on-premises NFS server where the image batches are stored.

Configure the destination location to be an Amazon S3 bucket with the Glacier Deep Archive storage class. This storage class is cost-effective for long-term storage with retrieval times of up to 12 hours.

Create DataSync Tasks:

Create and configure DataSync tasks to manage the data transfer. Schedule these tasks to run during non-business hours to minimize bandwidth usage during peak times. The tasks will handle the copying of data batches from the NFS server to the S3 bucket.

Set Bandwidth Limits:

In the DataSync configuration, set bandwidth limits to control the amount of data being transferred at any given time. This ensures that your network's performance is not adversely affected during business hours.

Delete On-Premises Data:

After successfully copying the data to S3 Glacier Deep Archive, configure the DataSync task to delete the data from your on-premises NFS server. This helps manage storage capacity on-premises and ensures data is securely archived on AWS.

This approach leverages AWS DataSync for efficient, secure, and automated data transfer, and S3 Glacier Deep Archive for cost-effective long-term storage.

Reference

AWS DataSync Overview41.

AWS Storage Blog on DataSync Migration40.

Amazon S3 Transfer Acceleration Documentation42.

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asked 16/09/2024
Sérgio Filipe Soares
43 questions
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