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A company runs a processing engine in the AWS Cloud.

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A company runs a processing engine in the AWS Cloud. The engine processes environmental data from logistics centers to calculate a sustainability index. The company has millions of devices in logistics centers that are spread across Europe. The devices send information to the processing engine through a RESTful API. The API experiences unpredictable bursts of traffic. The company must implement a solution to process all data that the devices send to the processing engine. Data loss is unacceptable. Which solution will meet these requirements?

A.

Create an Application Load Balancer (ALB) for the RESTful API. Create an Amazon SQS queue. Create a listener and a target group for the ALB. Add the SQS queue as the target. Use a container that runs in Amazon ECS with the Fargate launch type to process messages in the queue.

B.

Create an Amazon API Gateway HTTP API that implements the RESTful API. Create an Amazon SQS queue. Create an API Gateway service integration with the SQS queue. Create an AWS Lambda function to process messages in the SQS queue.

C.

Create an Amazon API Gateway REST API that implements the RESTful API. Create a fleet of Amazon EC2 instances in an Auto Scaling group. Create an API Gateway Auto Scaling group proxy integration. Use the EC2 instances to process incoming data.

D.

Create an Amazon CloudFront distribution for the RESTful API. Create a data stream in Amazon Kinesis Data Streams. Set the data stream as the origin for the distribution. Create an AWS Lambda function to consume and process data in the data stream.

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