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Question#1

A company is hosting a three-tier web application in an on-premises environment. Due to a recent surge in traffic that resulted in downtime and a significant financial impact, company management has ordered that the application be moved to AWS. The application is written in .NET and has a dependency on a MySQL database A solutions architect must design a scalable and highly available solution to meet the demand of 200000 daily users.
Which steps should the solutions architect take to design an appropriate solution?

A. Use AWS Elastic Beanstalk to create a new application with a web server environment and an Amazon RDS MySQL Multi-AZ DB instance. The environment should launch a Network Load Balancer (NLB) in front of an Amazon EC2 Auto Scaling group in multiple Availability Zones Use an Amazon Route 53 alias record to route traffic from the company's domain to the NL

B. Use AWS CloudFormation to launch a stack containing an Application Load Balancer (ALB) in front of an Amazon EC2 Auto Scaling group spanning three Availability Zones. The stack should launch a Multi-AZ deployment of an Amazon Aurora MySQL DB cluster with a Retain deletion policy. Use an Amazon Route 53 alias record to route traffic from the company's domain to the ALB

C. Use AWS Elastic Beanstalk to create an automatically scaling web server environment that spans two separate Regions with an Application Load Balancer (ALB) in each Region. Create a Multi-AZ deployment of an Amazon Aurora MySQL DB cluster with a cross-Region read replica Use Amazon Route 53 with a geoproximity routing policy to route traffic between the two Regions.

D. Use AWS CloudFormation to launch a stack containing an Application Load Balancer (ALB) in front of an Amazon ECS cluster of Spot Instances spanning three Availability Zones. The stack should launch an Amazon RDS MySQL DB instance with a Snapshot deletion policy Use an Amazon Route 53 alias record to route traffic from the company's domain to the ALB

Explanation:
Using AWS CloudFormation to launch a stack with an Application Load Balancer (ALB) in front of an Amazon EC2 Auto Scaling group spanning three Availability Zones, a Multi-AZ deployment of an Amazon Aurora MySQL DB cluster with a Retain deletion policy, and an Amazon Route 53 alias record to route traffic from the company’s domain to the ALB will ensure that

Question#2

A company maintains a restaurant review website. The website is a single-page application where files are stored in Amazon S3 and delivered using Amazon CloudFront. The company receives several fake postings every day that are manually removed.
The security team has identified that most of the fake posts are from bots with IP addresses that have a bad reputation within the same global region. The team needs to create a solution to help restrict the bots from accessing the website.
Which strategy should a solutions architect use?

A. Use AWS Firewall Manager to control the CloudFront distribution security settings. Create a geographical block rule and associate it with Firewall Manager.

B. Associate an AWS WAF web ACL with the CloudFront distribution. Select the managed Amazon IP reputation rule group for the web ACL with a deny action.

C. Use AWS Firewall Manager to control the CloudFront distribution security settings. Select the managed Amazon IP reputation rule group and associate it with Firewall Manager with a deny action.

D. Associate an AWS WAF web ACL with the CloudFront distribution. Create a rule group for the web ACL with a geographical match statement with a deny action.

Explanation:
IP reputation rule groups allow you to block requests based on their source. Choose one or more of these rule groups if you want to reduce your exposure to BOTS!!!! traffic or exploitation attempts
The Amazon IP reputation list rule group contains rules that are based on Amazon internal threat intelligence. This is useful if you would like to block IP addresses typically associated with bots or other threats. Inspects for a list of IP addresses that have been identified as bots by Amazon threat intelligence.

Question#3

A company's solution architect is designing a diasaster recovery (DR) solution for an application that runs on AWS. The application uses PostgreSQL 11.7 as its database. The
company has an PRO of 30 seconds. The solutions architect must design a DR solution with the primary database in the us-east-1 Region and the database in the us-west-2 Region.
What should the solution architect do to meet these requirements with minimum application change?

A. Migrate the database to Amazon RDS for PostgreSQL in us-east-1. Set up a read replica up a read replica in us-west-2. Set the managed PRO for the RDS database to 30 seconds.

B. Migrate the database to Amazon for PostgreSQL in us-east-1. Set up a standby replica in an Availability Zone in us-west-2, Set the managed PRO for the RDS database to 30 seconds.

C. Migrate the database to an Amazon Aurora PostgreSQL global database with the primary Region as us-east-1 and the secondary Region as us-west-2. Set the managed PRO for the Aurora database to 30 seconds.

D. Migrate the database to Amazon DynamoDB in us-east-1. Set up global tables with replica tables that are created in us-west-2.

Question#4

A company built an application based on AWS Lambda deployed in an AWS CloudFormation stack. The last production release of the web application introduced an issue that resulted in an outage lasting several minutes. A solutions architect must adjust the deployment process to support a canary release.
Which solution will meet these requirements?

A. Create an alias for every new deployed version of the Lambda function. Use the AWS CLI update-alias command with the routing-config parameter to distribute the load.

B. Deploy the application into a new CloudFormation stack. Use an Amazon Route 53 weighted routing policy to distribute the load.

C. Create a version for every new deployed Lambda function. Use the AWS CLI update-function-configuration command with the routing-config parameter to distribute the load.

D. Configure AWS CodeDeploy and use CodeDeployDefault.OneAtATime in the Deployment configuration to distribute the load.

Explanation:
https://aws.amazon.com/blogs/compute/implementing-canary-deployments-of-aws-lambda-functions-with-alias-traffic-shifting/ https://docs.aws.amazon.com/lambda/latest/dg/configuration-aliases.html

Question#5

A company is running an event ticketing platform on AWS and wants to optimize the platform's cost-effectiveness. The platform is deployed on Amazon Elastic Kubernetes Service (Amazon EKS) with Amazon EC2 and is backed by an Amazon RDS for MySQL DB instance. The company is developing new application features to run on Amazon EKS with AWS Fargate.
The platform experiences infrequent high peaks in demand. The surges in demand depend on event dates.
Which solution will provide the MOST cost-effective setup for the platform?

A. Purchase Standard Reserved Instances for the EC2 instances that the EKS cluster uses in its baseline load. Scale the cluster with Spot Instances to handle peaks. Purchase 1-year All Upfront Reserved Instances for the database to meet predicted peak load for the year.

B. Purchase Compute Savings Plans for the predicted medium load of the EKS cluster. Scale the cluster with On-Demand Capacity Reservations based on event dates for peaks. Purchase 1-year No Upfront Reserved Instances for the database to meet the predicted base load. Temporarily scale out database read replicas during peaks.

C. Purchase EC2 Instance Savings Plans for the predicted base load of the EKS cluster. Scale the cluster with Spot Instances to handle peaks. Purchase 1-year All Upfront Reserved Instances for the database to meet the predicted base load. Temporarily scale up the DB instance manually during peaks.

D. Purchase Compute Savings Plans for the predicted base load of the EKS cluster. Scale the cluster with Spot Instances to handle peaks. Purchase 1-year All Upfront Reserved Instances for the database to meet the predicted base load. Temporarily scale up the DB instance manually during peaks.

Explanation:
Compute Savings Plans: Provides flexibility for EKS clusters across multiple compute services and instance families using Amazon EC2 and AWS Fargate.
Spot Instances: Used to handle infrequent spikes in demand, as they offer significant cost savings and are suitable for flexible and intermittent loads.
Reserved Instances: Provides cost-effectiveness for a stable database base load, as the forecasted load is unlikely to change significantly.
Temporary manual scaling of DB instances: This allows for on-the-fly adjustments to database performance during peak demand periods, rather than paying for higher capacity all the time.

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