SAP-C02 · Question #508
A company manufactures smart vehicles. The company uses a custom application to collect vehicle data. The vehicles use the MQTT protocol to connect to the application. The company processes the data i
The correct answer is B. Use AWS IoT Core to receive the vehicle data. Configure rules to route data to an Amazon. AWS IoT Core provides a good way to handle data from IoT devices like these smart vehicles, especially as the MQTT protocol is used. Amazon Kinesis Data Firehose can capture, transform, and load streaming data into data lakes, data stores, and analytics services. It can handle la
Question
A company manufactures smart vehicles. The company uses a custom application to collect vehicle data. The vehicles use the MQTT protocol to connect to the application. The company processes the data in 5-minute intervals. The company then copies vehicle telematics data to on- premises storage. Custom applications analyze this data to detect anomalies. The number of vehicles that send data grows constantly. Newer vehicles generate high volumes of data. The on-premises storage solution is not able to scale for peak traffic, which results in data loss. The company must modernize the solution and migrate the solution to AWS to resolve the scaling challenges. Which solution will meet these requirements with the LEAST operational overhead?
Options
- AUse AWS IoT Greengrass to send the vehicle data to Amazon Managed Streaming for Apache
- BUse AWS IoT Core to receive the vehicle data. Configure rules to route data to an Amazon
- CUse AWS IoT FleetWise to collect the vehicle data. Send the data to an Amazon Kinesis data
- DUse Amazon MQ for RabbitMQ to collect the vehicle data. Send the data to an Amazon Kinesis
How the community answered
(45 responses)- A2% (1)
- B82% (37)
- C11% (5)
- D4% (2)
Explanation
AWS IoT Core provides a good way to handle data from IoT devices like these smart vehicles, especially as the MQTT protocol is used. Amazon Kinesis Data Firehose can capture, transform, and load streaming data into data lakes, data stores, and analytics services. It can handle large volumes of data from hundreds of thousands of sources, and it can scale automatically. Amazon Kinesis Data Analytics makes it easy to analyze streaming data in real-time with Java, SQL, or Apache Flink, without having to learn new programming languages or processing frameworks. It could be used to analyze the streaming data and detect anomalies
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