Question #651
A logistics company uses vehicles equipped with IoT sensors from multiple manufacturers. Each sensor transmits telemetry data in a unique proprietary format to an on-premises application that converts the data into XML. The application processes the XML files daily and stores them in a relational database for reporting. The company wants to modernize the system to enable real-time analytics while reducing operational costs.
Which solution meets these requirements?
Connect the IoT sensors to AWS IoT Core. Configure a rule to trigger an AWS Lambda function that transforms the data into Parquet format and stores it in Amazon S3. Use AWS Glue to catalog the data and Amazon Athena for querying, with Amazon QuickSight for visualization.
Deploy the legacy application on Amazon ECS with Fargate to process sensor data. Convert the XML files into a relational format and load them into Amazon Redshift for analysis.
Set up an Amazon Kinesis Data Firehose to ingest sensor data directly. Use Kinesis Data Analytics to convert the data into JSON and store it in Amazon DynamoDB. Use Amazon OpenSearch for dashboards.
Install AWS Snowcone devices in vehicles to collect sensor data locally. Periodically ship the devices to AWS and import the data into Amazon RDS for centralized analysis.
Explanation
Option A is correct because:
- AWS IoT Core supports diverse IoT devices and protocols, addressing the multi-manufacturer sensor setup.
- Lambda transforms data in real-time into Parquet, optimizing storage and query efficiency.
- S3 provides scalable, cost-effective storage.
- Glue catalogs data for easy discovery, Athena enables SQL-based analytics, and QuickSight offers visualization—all serverless, reducing operational costs.
Other options fail because:
- B relies on legacy batch processing (ECS/Fargate) and Amazon Redshift, which isn't real-time.
- C uses DynamoDB (costly for large datasets) and lacks efficient transformation for proprietary formats.
- D uses Snowcone and RDS, which are unsuitable for real-time analytics.
Key Points: Use serverless services (IoT Core, Lambda, Glue, Athena) for real-time processing, cost efficiency, and scalability. Parquet + S3 optimizes storage/analytics.
Answer
The correct answer is: A