AWS Certified Data Engineer Associate · Free Practice Question Hard
Question 10
A gaming company is developing a mobile game that streams score updates to a backend processor and then publishes results on a leaderboard. The company has hired you as an AWS Certified Data Engineer Associate to design a solution that can handle major traffic spikes, process the mobile game updates in the order of receipt, and store the processed updates in a highly available database. The company wants to minimize the management overhead required to maintain the solution.
Which of the following will you recommend to meet these requirements?
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A
Push score updates to Amazon Kinesis Data Streams which uses an AWS Lambda function to process these updates and then store these processed updates in Amazon DynamoDB
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B
Push score updates to an Amazon Simple Queue Service (Amazon SQS) queue which uses a fleet of Amazon EC2 instances (with Auto Scaling) to process these updates in the Amazon SQS queue and then store these processed updates in an Amazon RDS MySQL database
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C
Push score updates to an Amazon Simple Notification Service (Amazon SNS) topic, subscribe an AWS Lambda function to this Amazon SNS topic to process the updates and then store these processed updates in a SQL database running on Amazon EC2 instance
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D
Push score updates to Amazon Kinesis Data Streams which uses a fleet of Amazon EC2 instances (with Auto Scaling) to process the updates in Amazon Kinesis Data Streams and then store these processed updates in Amazon DynamoDB
Reveal correct answer
Correct answer: A
Explanation
Correct option:
Push score updates to Amazon Kinesis Data Streams which uses an AWS Lambda function to process these updates and then store these processed updates in Amazon DynamoDB
To help ingest real-time data or streaming data at large scales, you can use Amazon Kinesis Data Streams (KDS). KDS can continuously capture gigabytes of data per second from hundreds of thousands of sources. The data collected is available in milliseconds, enabling real-time analytics. KDS provides ordering of records, as well as the ability to read and/or replay records in the same order to multiple Amazon Kinesis Applications.
AWS Lambda integrates natively with Kinesis Data Streams. The polling, checkpointing, and error-handling complexities are abstracted when you use this native integration. The processed data can then be configured to be saved in Amazon DynamoDB.
Incorrect options:
Push score updates to an Amazon Simple Queue Service (Amazon SQS) queue which uses a fleet of Amazon EC2 instances (with Auto Scaling) to process these updates in the Amazon SQS queue and then store these processed updates in an Amazon RDS MySQL database
Push score updates to Amazon Kinesis Data Streams which uses a fleet of Amazon EC2 instances (with Auto Scaling) to process the updates in Amazon Kinesis Data Streams and then store these processed updates in Amazon DynamoDB
Push score updates to an Amazon Simple Notification Service (Amazon SNS) topic, subscribe an AWS Lambda function to this Amazon SNS topic to process the updates and then store these processed updates in a SQL database running on Amazon EC2 instance
These three options use Amazon EC2 instances as part of the solution architecture. The use case seeks to minimize the management overhead required to maintain the solution. However, Amazon EC2 instances involve several maintenance activities such as managing the guest operating system and software deployed to the guest operating system, including updates and security patches, etc. Hence these options are incorrect.
Reference:
Discussion
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