Topic 1 Question 611
A company has an application with a REST-based interface that allows data to be received in near-real time from a third-party vendor. Once received, the application processes and stores the data for further analysis. The application is running on Amazon EC2 instances.
The third-party vendor has received many 503 Service Unavailable Errors when sending data to the application. When the data volume spikes, the compute capacity reaches its maximum limit and the application is unable to process all requests.
Which design should a solutions architect recommend to provide a more scalable solution?
Use Amazon Kinesis Data Streams to ingest the data. Process the data using AWS Lambda functions.
Use Amazon API Gateway on top of the existing application. Create a usage plan with a quota limit for the third-party vendor.
Use Amazon Simple Notification Service (Amazon SNS) to ingest the data. Put the EC2 instances in an Auto Scaling group behind an Application Load Balancer.
Repackage the application as a container. Deploy the application using Amazon Elastic Container Service (Amazon ECS) using the EC2 launch type with an Auto Scaling group.
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コメント(4)
- 正解だと思う選択肢: A
The key reasons are:
Kinesis Data Streams provides an auto-scaling stream that can handle large amounts of streaming data ingestion and throughput. This removes the bottlenecks around receiving the data. AWS Lambda can process and store the data in a scalable serverless manner, avoiding EC2 capacity limits. API Gateway adds API management capabilities but does not improve the underlying scalability of the EC2 application. SNS is for event publishing/notifications, not large scale data ingestion. ECS still relies on EC2 capacity.
👍 5Guru4Cloud2023/09/23 - 正解だと思う選択肢: A
For near-real time data ingest and processing, Kinesis and Lambda are most scalable choice.
👍 4taustin22023/09/22 Only A is pure serverless which means scale. A for sure.
👍 1wsdasdasdqwdaw2023/10/29
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