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NEW QUESTION 32
A start up company hosts a fleet of Amazon EC2 instances in private subnets using the latest Amazon Linux 2 AMI. The company’s engineers rely heavily on SSH access to the instances for troubleshooting.
The company’s existing architecture includes the following:
* A VPC with private and public subnets, and a NAT gateway
* Site-to-Site VPN for connectivity with the on-premises environment
* EC2 security groups with direct SSH access from the on-premises environment The company needs to increase security controls around SSH access and provide auditing of commands executed by the engineers.
Which strategy should a solutions architect use?

  • A. Create an IAM role with the Ama2onSSMManagedlnstanceCore managed policy attached. Attach the IAM role to all the EC2 instances. Remove all security group rules attached to the EC2
  • B. instances that allow inbound TCP on port 22. Have the engineers install the AWS Systems Manager Session Manager plugin for their devices and remotely access the instances by using the start-session API call from Systems Manager.
  • C. Update the EC2 security groups to only allow inbound TCP on port 22 to the IP addresses of the engineer’s devices. Enable AWS Config for EC2 security group resource changes. Enable AWS Firewall Manager and apply a security group policy that automatically remediates changes to rules.
  • D. Update the EC2 security groups to only allow inbound TCP on port 22 to the IP addresses of the engineer’s devices. Install the Amazon CloudWatch agent on all EC2 instances and send operating system audit logs to CloudWatch Logs.
  • E. Install and configure EC2 instance Connect on the fleet of EC2 instances. Remove all security group rules attached to EC2 instances that allow inbound TCP on port 22. Advise the engineers to remotely access the instances by using the EC2 Instance Connect CLI.

Answer: D

 

NEW QUESTION 33
A company is migrating its marketing website and content management system from an on-premises data center to AWS. The company wants the AWS application to be deployed in a VPC with Amazon EC2 instances used for the web servers and an Amazon RDS instance for the database.
The company has a runbook document that describes the installation process of the on-premises system. The company would like to base the AWS system on the processes referenced in the runbook document. The runbook document describes the installation and configuration of the operating systems, network settings, the website, and content management system software on the servers After the migration is complete, the company wants to be able to make changes quickly to take advantage of other AWS features.
How can the application and environment be deployed and automated m AWS. while allowing for future changes?

  • A. Write a Python script that uses the AWS API to create the VPC. the EC2 instances and the RDS instance for the application Write shell scripts that implement the rest of the steps in the runbook Have the Python script copy and run the shell scripts on the newly created instances to complete the installation
  • B. Write an AWS CloudFormation template that creates the VPC the EC2 instances, and the RDS instance for the application Include EC2 user data in the AWS Cloud Formation template to install and configure the software.
  • C. Write an AWS Cloud Formation template that creates the VPC, the EC2 instances, and the RDS instance for the application Ensure that the rest of the steps in the runbook are updated to reflect any changes that may come from the AWS migration
  • D. Update the runbook to describe how to create the VPC. the EC2 instances and the RDS instance for the application by using the AWS Console Make sure that the rest of the steps in the runbook are updated to reflect any changes that may come from the AWS migration

Answer: B

 

NEW QUESTION 34
A financial services company in North America plans to release a new online web application to its customers on AWS . The company will launch the application in the us-east-1 Region on Amazon EC2 instances. The application must be highly available and must dynamically scale to meet user traffic. The company also wants to implement a disaster recovery environment for the application in the us-west-1 Region by using active-passive failover.
Which solution will meet these requirements?

  • A. Create a VPC in us-east-1 and a VPC in us-west-1 Configure VPC peering In the us-east-1 VPC. create an Application Load Balancer (ALB) that extends across multiple Availability Zones in both VPCs Create an Auto Scaling group that deploys the EC2 instances across the multiple Availability Zones in both VPCs Place the Auto Scaling group behind the ALB.
  • B. Create a VPC in us-east-1 and a VPC in us-west-1 Configure VPC peering In the us-east-1 VPC. create an Application Load Balancer (ALB) that extends across multiple Availability Zones in Create an Auto Scaling group that deploys the EC2 instances across the multiple Availability Zones in both VPCs Place the Auto Scaling group behind the ALB Create an Amazon Route 53 host.. Create a record for the ALB.
  • C. Create a VPC in us-east-1 and a VPC in us-west-1 In the us-east-1 VPC. create an Application Load Balancer (ALB) that extends across multiple Availability Zones in that VPC Create an Auto Scaling group that deploys the EC2 instances across the multiple Availability Zones in the us-east-1 VPC Place the Auto Scaling group behind the ALB Set up the same configuration in the us-west-1 VPC Create an Amazon Route 53 hosted zone. Create separate records for each ALB Enable health checks and configure a failover routing policy for each record.
  • D. Create a VPC in us-east-1 and a VPC in us-west-1. In the us-east-1 VPC. create an Application Load Balancer (ALB) that extends across multiple Availability Zones in that VPC. Create an Auto Scaling group that deploys the EC2 instances across the multiple Availability Zones in the us-east-1 VPC Place the Auto Scaling group behind the ALB Set up the same configuration in the us-west-1 VPC. Create an Amazon Route 53 hosted zone Create separate records for each ALB Enable health checks to ensure high availability between Regions.

Answer: C

 

NEW QUESTION 35
A company has application services that have been containerized and deployed on multiple Amazon EC2 instances with public IPs. An Apache Kafka cluster has been deployed to the EC2 instances. A PostgreSQL database has been migrated to Amazon RDS lor PostgreSQL. The company expects a significant increase of orders on its platform when a new version of its flagship product is released.
What changes to the current architecture will reduce operational overhead and support the product release?

  • A. Create an EC2 Auto Scaling group behind an Application Load Balancer. Create additional read replicas for the DB instance. Create Amazon Kinesis data streams and configure the application services lo use the data streams. Store and serve static content directly from Amazon S3.
  • B. Deploy the application on a Kubernetes cluster created on the EC2 instances behind an Application Load Balancer. Deploy the DB instance in Multi-AZ mode and enable storage auto scaling. Create an Amazon Managed Streaming for Apache Kafka cluster and configure the application services to use the cluster. Store static content in Amazon S3 behind an Amazon CloudFront distribution.
  • C. Create an EC2 Auto Scaling group behind an Application Load Balancer. Deploy the DB instance in Multi-AZ mode and enable storage auto scaling. Create Amazon Kinesis data streams and configure the application services to use the data streams. Store and serve static content directly from Amazon S3.
  • D. Deploy the application on Amazon Elastic Kubernetes Service (Amazon EKS) with AWS Fargate and enable auto scaling behind an Application Load Balancer. Create additional read replicas for the DB instance. Create an Amazon Managed Streaming for Apache Kafka cluster and configure the application services to use the cluster. Store static content in Amazon S3 behind an Amazon CloudFront distribution.

Answer: D

Explanation:
Deploy the application on Amazon Elastic Kubernetes Service (Amazon EKS) with AWS Fargate and enable auto scaling behind an Application Load Balancer. Create additional read replicas for the DB instance. Create an Amazon Managed Streaming for Apache Kafka cluster and configure the application services to use the cluster. Store static content in Amazon S3 behind an Amazon CloudFront distribution.

 

NEW QUESTION 36
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. 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.
  • D. 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.

Answer: D

Explanation:
The obvious challenges here are long workloads, scalability based on queue load, and reliability. Almost always the defacto answer to queue related workload is SQS. Since the workloads are very long (90 minutes) Lambdas cannot be used (15 mins max timeout). So, autoscaled smaller EC2 nodes that wait on external services to complete the task makes more sense. If the task fails, the message is returned to the queue and retried.

 

NEW QUESTION 37
……

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