AWS Certified Solutions Architect – Professional (SAP-C02) — Question 268

A company has more than 10,000 sensors that send data to an on-premises Apache Kafka server by using the Message Queuing Telemetry Transport (MQTT) protocol. The on-premises Kafka server transforms the data and then stores the results as objects in an Amazon S3 bucket.

Recently, the Kafka server crashed. The company lost sensor data while the server was being restored. A solutions architect must create a new design on AWS that is highly available and scalable to prevent a similar occurrence.

Which solution will meet these requirements?

Answer options

• A. Launch two Amazon EC2 instances to host the Kafka server in an active/standby configuration across two Availability Zones. Create a domain name in Amazon Route 53. Create a Route 53 failover policy. Route the sensors to send the data to the domain name.
• B. Migrate the on-premises Kafka server to Amazon Managed Streaming for Apache Kafka (Amazon MSK). Create a Network Load Balancer (NLB) that points to the Amazon MSK broker. Enable NLB health checks. Route the sensors to send the data to the NLB.
• C. Deploy AWS IoT Core, and connect it to an Amazon Kinesis Data Firehose delivery stream. Use an AWS Lambda function to handle data transformation. Route the sensors to send the data to AWS IoT Core.
• D. Deploy AWS IoT Core, and launch an Amazon EC2 instance to host the Kafka server. Configure AWS IoT Core to send the data to the EC2 instance. Route the sensors to send the data to AWS IoT Core.

Correct answer: C

Explanation

AWS IoT Core is a fully managed service that natively supports the MQTT protocol, making it the ideal choice for ingesting data from thousands of sensors without infrastructure management. Combining AWS IoT Core with Amazon Kinesis Data Firehose provides a serverless, highly available delivery pipeline to Amazon S3, utilizing AWS Lambda to transform the data on the fly. Other options involving self-managed EC2 instances or Amazon MSK introduce unnecessary administrative overhead and do not offer the same seamless, serverless scalability for MQTT ingestion.