Amazon Web Services SAP-C02 Exam With Confidence Using Practice Dumps

Register the customer-owned block of IP addresses in the company's AWS account. Create Elastic IP addresses from the address pool and assign them to an AWS Transfer for SFTP endpoint. Use AWS Transfer to store the files in Amazon S3.

Add a subnet containing the customer-owned block of IP addresses to a VPC Create Elastic IP addresses from the address pool and assign them to an Application Load Balancer (ALB). Launch EC2 instances hosting FTP services in an Auto Scaling group behind the ALB. Store the files in attached Amazon Elastic Block Store (Amazon EBS) volumes.

Register the customer-owned block of IP addresses with Amazon Route 53. Create alias records in Route 53 that point to a Network Load Balancer (NLB). Launch EC2 instances hosting FTP services in an Auto Scaling group behind the NLB. Store the files in Amazon S3.

Register the customer-owned block of IP addresses in the company's AWS account. Create Elastic IP addresses from the address pool and assign them to an Amazon S3 VPC endpoint. Enable SFTP support on the S3 bucket.

Upload the AWS CloudFormation template to Amazon S3. Give users in the QA department permission to assume the manager's role, restricts the permissions to the template and the resources it creates. Train users to launch the template from the CloudFormation console.

Create an AWS Service Catalog product from the environment template. Add a launch constraint to the product with the existing manager's department permission to use AWS Service Catalog APIs only. Train users to launch the template from the AWS Service Catalog console.

Upload the AWS CloudFormation template to Amazon S3. Give users in the QA department permission to use CloudFormation and restrict the permissions to the template and the resources it creates. Train users to launch the template from the CloudFormation console.

Create an AWS Elastic Beanstalk application from the environment template. Give users in the QA department permission to use Elastic Beanstalk only. Train users to launch Elastic Beanstalk environments with the Elastic Beanstalk CLI, passing the existing role to the environment.

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.