A global logistics company is designing a tracking system. IoT devices on trucks send location updates every 5 seconds via MQTT. The data needs to be ingested, processed in real-time to detect route deviations, and then stored in a data lake. The architecture must handle millions of messages per second with high reliability. Which AWS architecture is MOST appropriate?

Answer options:

AWS IoT Core -> Amazon SQS -> AWS Lambda -> Amazon RDS.

AWS IoT Core -> Amazon Kinesis Data Streams -> Amazon Kinesis Data Analytics -> Amazon S3.

Amazon API Gateway -> AWS Step Functions -> Amazon DynamoDB.

AWS IoT Core -> Amazon SNS -> Amazon EC2 -> Amazon EBS.

How to approach this question

Identify the standard AWS streaming data pipeline components.

Full Answer

B.AWS IoT Core -> Amazon Kinesis Data Streams -> Amazon Kinesis Data Analytics -> Amazon S3.✓ Correct

The standard pattern for high-throughput IoT telemetry involves AWS IoT Core for device connectivity, Kinesis Data Streams for durable ingestion, Kinesis Data Analytics for real-time processing (like route deviation), and Amazon S3 for the data lake.

Common mistakes

Choosing SQS/Lambda, which is better for discrete tasks rather than continuous stream analytics.

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