A company is building a RESTful serverless web application on AWS by using Amazon API Gateway and AWS Lambd a. The users of this web application will be geographically distributed, and the company wants to reduce the latency of API requests to these users Which type of endpoint should a solutions architect use to meet these requirements?

• A.Private endpoint
• B.Regional endpoint
• C.Interface VPC endpoint
• D.Edge-optimzed endpoint

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A company has a three-tier web application that processes orders from customers. The web tier consists of Amazon EC2 instances behind an Application Load Balancer. The processing tier consists of EC2 instances. The company decoupled the web tier and processing tier by using Amazon Simple Queue Service (Amazon SQS). The storage layer uses Amazon DynamoDB.
At peak times some users report order processing delays and halts. The company has noticed that during these delays, the EC2 instances are running at 100% CPU usage, and the SQS queue fills up. The peak times are variable and unpredictable.
The company needs to improve the performance of the application
Which solution will meet these requirements?

• A.Use scheduled scaling for Amazon EC2 Auto Scaling to scale out the processing tier instances for the duration of peak usage times. Use the CPU Utilization metric to determine when to scale.
• B.Use Amazon ElastiCache for Redis in front of the DynamoDB backend tier. Use target utilization as a metric to determine when to scale.
• C.Add an Amazon CloudFront distribution to cache the responses for the web tier. Use HTTP latency as a metric to determine when to scale.
• D.Use an Amazon EC2 Auto Scaling target tracking policy to scale out the processing tier instances. Use the ApproximateNumberOfMessages attribute to determine when to scale.

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[Design High-Performing Architectures]
A company collects data from thousands of remote devices by using a RESTful web services application that runs on an Amazon EC2 instance. The EC2 instance receives the raw data, transforms the raw data, and stores all the data in an Amazon S3 bucket. The number of remote devices will increase into the millions soon. The company needs a highly scalable solution that minimizes operational overhead.
Which combination of steps should a solutions architect take to meet these requirements9 (Select TWO.)

• A.Use AWS Glue to process the raw data in Amazon S3.
• B.Use Amazon Route 53 to route traffic to different EC2 instances.
• C.Add more EC2 instances to accommodate the increasing amount of incoming data.
• D.Send the raw data to Amazon Simple Queue Service (Amazon SOS). Use EC2 instances to process the data.
• E.Use Amazon API Gateway to send the raw data to an Amazon Kinesis data stream. Configure Amazon Kinesis Data Firehose to use the data stream as a source to deliver the data to Amazon S3.

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A company is building an application that consists of several microservices. The company has decided to use container technologies to deploy its software on AWS. The company needs a solution that minimizes the amount of ongoing effort for maintenance and scaling. The company cannot manage additional infrastructure.
Which combination of actions should a solutions architect take to meet these requirements? (Choose two.)

• A.Deploy an Amazon Elastic Container Service (Amazon ECS) cluster.
• B.Deploy the Kubernetes control plane on Amazon EC2 instances that span multiple Availability Zones.
• C.Deploy an Amazon Elastic Container Service (Amazon ECS) service with an Amazon EC2 launch type.
  Specify a desired task number level of greater than or equal to 2.
• D.Deploy an Amazon Elastic Container Service (Amazon ECS) service with a Fargate launch type.
  Specify a desired task number level of greater than or equal to 2.
• E.Deploy Kubernetes worker nodes on Amazon EC2 instances that span multiple Availability Zones.Create a deployment that specifies two or more replicas for each microservice.

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A company is building a solution that will report Amazon EC2 Auto Scaling events across all the applications in an AWS account. The company needs to use a serverless solution to store the EC2 Auto Scaling status data in Amazon S3. The company then will use the data in Amazon S3 to provide near-real-time updates in a dashboard. The solution must not affect the speed of EC2 instance launches.
How should the company move the data to Amazon S3 to meet these requirements?

• A.Use an Amazon CloudWatch metric stream to send the EC2 Auto Scaling status data to Amazon Kinesis Data Firehose. Store the data in Amazon S3.
• B.Launch an Amazon EMR cluster to collect the EC2 Auto Scaling status data and send the data to Amazon Kinesis Data Firehose. Store the data in Amazon S3.
• C.Create an Amazon EventBridge rule to invoke an AWS Lambda function on a schedule. Configure the Lambda function to send the EC2 Auto Scaling status data directly to Amazon S3.
• D.Use a bootstrap script during the launch of an EC2 instance to install Amazon Kinesis Agent. Configure Kinesis Agent to collect the EC2 Auto Scaling status data and send the data to Amazon Kinesis Data Firehose. Store the data in Amazon S3.

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