Which solution will meet these requirements?
Create an Application Load Balancer (ALB) for the RESTful API. Create an Amazon Simple Queue Service (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 Elastic Container Service (Amazon ECS) with the Fargate launch type to process messages in the queue.
Create an Amazon API Gateway HTTP API that implements the RESTful API. Create an Amazon Simple Queue Service (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.
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.
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.
Explanations:
While using an Application Load Balancer (ALB) with SQS and ECS can handle bursts of traffic, it may introduce complexities and latency due to the additional step of sending data through SQS before processing. Moreover, it does not natively handle the RESTful API integration as seamlessly as other options.
This option provides a robust solution by using Amazon API Gateway to implement the RESTful API, which can automatically scale to handle unpredictable bursts of traffic. The integration with SQS ensures that no data is lost, as it reliably queues incoming requests. AWS Lambda can then process the queued messages, allowing for efficient handling of the data without over-provisioning resources.
Although using API Gateway with an Auto Scaling group of EC2 instances can manage traffic, it does not inherently provide a mechanism to queue and process bursts of data reliably. If traffic spikes exceed the capacity of the EC2 instances, there is a risk of data loss, which is unacceptable for this scenario.
This option suggests using Amazon CloudFront with Kinesis Data Streams, which is more suitable for streaming data rather than handling RESTful API calls. The complexity of managing data through CloudFront and Kinesis may not effectively guarantee that all data is processed without loss, as it does not fit the requirement of a traditional RESTful API.
As I understand it, the answer is:
Create an Amazon API Gateway HTTP API that implements the RESTful API. Create an Amazon Simple Queue Service (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.