Discover how to leverage AWS IoT FleetWise, Amazon Kinesis, and AWS Glue to efficiently collect, store, and analyze high-volume vehicle data with minimal operational overhead.
Table of Contents
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?
A. Use AWS IoT Greengrass to send the vehicle data to Amazon Managed Streaming for Apache Kafka (Amazon MSK). Create an Apache Kafka application to store the data in Amazon S3. Use a pretrained model in Amazon SageMaker to detect anomalies.
B. Use AWS IoT Core to receive the vehicle data. Configure rules to route data to an Amazon Kinesis Data Firehose delivery stream that stores the data in Amazon S3. Create an Amazon Kinesis Data Analytics application that reads from the delivery stream to detect anomalies.
C. Use AWS IoT FleetWise to collect the vehicle data. Send the data to an Amazon Kinesis data stream. Use an Amazon Kinesis Data Firehose delivery stream to store the data in Amazon S3. Use the built-in machine learning transforms in AWS Glue to detect anomalies.
D. Use Amazon MQ for RabbitMQ to collect the vehicle data. Send the data to an Amazon Kinesis Data Firehose delivery stream to store the data in Amazon S3. Use Amazon Lookout for Metrics to detect anomalies.
Answer
C. Use AWS IoT FleetWise to collect the vehicle data. Send the data to an Amazon Kinesis data stream. Use an Amazon Kinesis Data Firehose delivery stream to store the data in Amazon S3. Use the built-in machine learning transforms in AWS Glue to detect anomalies.
Explanation
The solution that meets the requirements with the LEAST operational overhead is:
C. Use AWS IoT FleetWise to collect the vehicle data. Send the data to an Amazon Kinesis data stream. Use an Amazon Kinesis Data Firehose delivery stream to store the data in Amazon S3. Use the built-in machine learning transforms in AWS Glue to detect anomalies.
AWS IoT FleetWise is a specialized service designed for collecting, transforming, and transferring vehicle data to the cloud. By using IoT FleetWise, the company can easily ingest and process the high volumes of data generated by the growing number of smart vehicles, without the operational overhead of managing custom applications or infrastructure.
Here’s a detailed explanation of how this solution addresses the requirements:
- AWS IoT FleetWise for Vehicle Data Collection: IoT FleetWise is purpose-built for ingesting and processing vehicle data, including MQTT protocol support. It simplifies the collection and transmission of data from vehicles, reducing operational overhead compared to custom applications.
- Amazon Kinesis Data Stream: IoT FleetWise can seamlessly integrate with Amazon Kinesis Data Streams, which provide scalable and durable ingestion of high-volume data streams. This addresses the scaling challenges faced by the on-premises storage solution.
- Amazon Kinesis Data Firehose: Kinesis Data Firehose can automatically store the vehicle data from the Kinesis Data Stream into Amazon S3, a highly scalable and durable object storage service. This ensures that the data is persisted reliably without the need for on-premises storage.
- AWS Glue Machine Learning Transforms: AWS Glue provides built-in machine learning transforms that can detect anomalies in the vehicle data stored in Amazon S3. This eliminates the need for custom anomaly detection applications or complex machine learning model deployment and management.
By leveraging AWS IoT FleetWise, Amazon Kinesis, and AWS Glue, this solution minimizes operational overhead by utilizing fully managed services designed for ingesting, storing, and analyzing high-volume data streams. The company can focus on their core business logic instead of managing underlying infrastructure or custom applications.
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