Amazon Web Services dumpspedia last Attempt Sap-c02 Questions by Zayyan q211 vce pdf

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Exam Name:	AWS Certified Solutions Architect - Professional
Exam Code:	SAP-C02 Dumps
Vendor:	Amazon Web Services	Certification:	AWS Certified Professional
Questions:	587 Q&A's	Shared By:	zayyan

Question 28

A company has an loT platform that runs in an on-premises environment. The platform consists of a server that connects to loT devices by using the MQTT protocol. The platform collects telemetry data from the devices at least once every 5 minutes The platform also stores device metadata in a MongoDB cluster

An application that is installed on an on-premises machine runs periodic jobs to aggregate and transform the telemetry and device metadata The application creates reports that users view by using another web application that runs on the same on-premises machine The periodic jobs take 120-600 seconds to run However, the web application is always running.

The company is moving the platform to AWS and must reduce the operational overhead of the stack.

Which combination of steps will meet these requirements with the LEAST operational overhead? (Select THREE.)

Options:

Use AWS Lambda functions to connect to the loT devices

Configure the loT devices to publish to AWS loT Core

Write the metadata to a self-managed MongoDB database on an Amazon EC2 instance

Write the metadata to Amazon DocumentDB (with MongoDB compatibility)

Use AWS Step Functions state machines with AWS Lambda tasks to prepare the reports and to write the reports to Amazon S3 Use Amazon CloudFront with an S3origin to serve the reports

Use an Amazon Elastic Kubernetes Service (Amazon EKS) cluster with Amazon EC2 instances to prepare the reports Use an ingress controller in the EKS cluster to serve the reports

Discussion

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Question 29

A manufacturing company is building an inspection solution for its factory. The company has IPcameras at the end of each assembly line. The company has used Amazon SageMaker to train a machine learning (ML) model to identify common defects from still images.

The company wants to provide local feedback to factory workers when a defect is detected. The company must be able to provide this feedback even if the factory’s internet connectivity is down. The company has a local Linux server that hosts an API that provides local feedback to the workers.

How should the company deploy the ML model to meet these requirements?

Options:

Set up an Amazon Kinesis video stream from each IP camera to AWS. Use Amazon EC2 instances to take still images of the streams. Upload the images to an Amazon S3 bucket. Deploy a SageMaker endpoint with the ML model. Invoke an AWS Lambda function to call the inference endpoint when new images are uploaded. Configure the Lambda function to call the local API when a defect is detected.

Deploy AWS IoT Greengrass on the local server. Deploy the ML model to the Greengrass server. Create a Greengrass component to take still images from the cameras and run inference. Configure the component to call the local API when a defect is detected.

Order an AWS Snowball device. Deploy a SageMaker endpoint the ML model and an Amazon EC2 instance on the Snowball device. Take still images from the cameras. Run inference from the EC2 instance. Configure the instance to call the local API when a defect is detected.

Deploy Amazon Monitron devices on each IP camera. Deploy an Amazon Monitron Gateway on premises. Deploy the ML model to the Amazon Monitron devices. Use Amazon Monitron health state alarms to call the local API from an AWS Lambda function when a defect is detected.

Discussion

Question 30

A company wants to optimize AWS data-transfer costs and compute costs across developer accounts within the company's organization in AWS Organizations Developers can configure VPCs and launch Amazon EC2 instances in a single AWS Region The EC2 instances retrieve approximately 1 TB of data each day from Amazon S3

The developer activity leads to excessive monthly data-transfer charges and NAT gateway processing charges between EC2 instances and S3 buckets, along with high compute costs The company wants to proactively enforce approved architectural patterns for any EC2 instance and VPC infrastructure that developers deploy within the AWS accounts The company does not wantthis enforcement to negatively affect the speed at which the developers can perform their tasks

Which solution will meet these requirements MOST cost-effectively?

Options:

Create SCPs to prevent developers from launching unapproved EC2 instance types Provide the developers with an AWS CloudFormation template to deploy an approved VPC configuration with S3 interface endpoints Scope the developers* IAM permissions so that the developers can launch VPC resources only with CloudFormation

Create a daily forecasted budget with AWS Budgets to monitor EC2 compute costs and S3 data-transfer costs across the developer accounts When the forecasted cost is 75% of the actual budget cost, send an alert to the developer teams If the actual budget cost is 100%. create a budget action to terminate the developers' EC2 instances and VPC infrastructure

Create an AWS Service Catalog portfolio that users can use to create an approved VPC configuration with S3 gateway endpoints and approved EC2 instances Share the portfolio with the developer accounts Configure an AWS Service Catalog launch constraint to use an approved IAM role Scope the developers' IAM permissions to allow access only to AWS Service Catalog

Create and deploy AWS Config rules to monitor the compliance of EC2 and VPC resources in the developer AWS accounts If developers launch unapproved EC2 instances or if developers create VPCs without S3 gateway endpoints perform a remediation action to terminate the unapproved resources

Discussion

Question 31

A company needs to optimize the cost of backups for Amazon Elastic File System (Amazon EFS). A solutions architect has already configured a backup plan in AWS Backup for the EFS backups. The backup plan contains a rule with a lifecycle configuration to transition EFS backups to cold storage after 7 days and to keep the backups for an additional 90 days.

After I month, the company reviews its EFS storage costs and notices an increase in the EFS backup costs. The EFS backup cold storage produces almost double the cost of the EFS warm backup storage.

What should the solutions architect do to optimize the cost?

Options:

Modify the backup rule's lifecycle configuration to move the EFS backups to cold storage after 1 day. Set the backup retention period to 30 days.

Modify the backup rule's lifecycle configuration to move the EFS backups to cold storage after 8 days. Set the backup retention period to 30 days.

Modify the backup rule's lifecycle configuration to move the EFS backups to cold storage after 1 day. Set the backup retention period to 90 days.

Modify the backup rule's lifecycle configuration to move the EFS backups to cold storage after 8 days. Set the backup retention period to 98 days.