Topic 1 Question 25
A company is designing an application. The application uses an AWS Lambda function to receive information through Amazon API Gateway and to store the information in an Amazon Aurora PostgreSQL database. During the proof-of-concept stage, the company has to increase the Lambda quotas significantly to handle the high volumes of data that the company needs to load into the database. A solutions architect must recommend a new design to improve scalability and minimize the configuration effort. Which solution will meet these requirements?
Refactor the Lambda function code to Apache Tomcat code that runs on Amazon EC2 instances. Connect the database by using native Java Database Connectivity (JDBC) drivers.
Change the platform from Aurora to Amazon DynamoDProvision a DynamoDB Accelerator (DAX) cluster. Use the DAX client SDK to point the existing DynamoDB API calls at the DAX cluster.
Set up two Lambda functions. Configure one function to receive the information. Configure the other function to load the information into the database. Integrate the Lambda functions by using Amazon Simple Notification Service (Amazon SNS).
Set up two Lambda functions. Configure one function to receive the information. Configure the other function to load the information into the database. Integrate the Lambda functions by using an Amazon Simple Queue Service (Amazon SQS) queue.
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コメント(17)
- 正解だと思う選択肢: D
A - refactoring can be a solution, BUT requires a LOT of effort - not the answer B - DynamoDB is NoSQL and Aurora is SQL, so it requires a DB migration... again a LOT of effort, so no the answer C and D are similar in structure, but... C uses SNS, which would notify the 2nd Lambda function... provoking the same bottleneck... not the solution D uses SQS, so the 2nd lambda function can go to the queue when responsive to keep with the DB load process. Usually the app decoupling helps with the performance improvement by distributing load. In this case, the bottleneck is solved by uses queues... so D is the answer.
👍 49123jhl02022/10/16 - 正解だと思う選択肢: D
Keywords:
- Company has to increase the Lambda quotas significantly to handle the high volumes of data that the company needs to load into the database.
- Improve scalability and minimize the configuration effort.
A: Incorrect - Lambda is Serverless and automatically scale - EC2 instance we have to create load balancer, auto scaling group,.. a lot of things. using native Java Database Connectivity (JDBC) drivers don't improve the performance. B: Incorrect - a lot of things to changes and DynamoDB Accelerator use for cache(read) not for write. C: Incorrect - SNS is use for send notification (e-mail, SMS). D: Correct - with SQS we can scale application well by queuing the data.
👍 8PhucVuu2023/04/07 - 正解だと思う選択肢: D
The solution that will meet these requirements is D: Set up two Lambda functions. Configure one function to receive the information. Configure the other function to load the information into the database. Integrate the Lambda functions by using an Amazon Simple Queue Service (Amazon SQS) queue.
Using separate Lambda functions for receiving and loading the information can help improve scalability and minimize the configuration effort. By using an Amazon SQS queue to integrate the Lambda functions, you can decouple the functions and allow them to scale independently. This can help reduce the burden on the receiving function, improving its performance and scalability.
👍 3Buruguduystunstugudunstuy2022/12/27
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