SAA-C03 Question 454
Single answerA company processes large volumes of real-time sensor data from IoT devices deployed globally. The company needs to minimize latency for data processing and provide near-instant responses to users based on their geographical location. The processed data should also be sent to a central AWS Region for long-term analytics and storage. Which solution should the company implement to meet these requirements?
- A
Use AWS Lambda@Edge to process the data at edge locations and Amazon S3 to store the processed data in the central AWS Region.
- B
Deploy Amazon EC2 instances in multiple AWS Regions and use Auto Scaling to handle data processing.
- C
Use AWS IoT Greengrass for edge processing and configure it to send processed data to Amazon S3 in the central AWS Region.
- D
Configure Amazon CloudFront to cache the data at edge locations and use Amazon Redshift to analyze the data in the central AWS Region.
Show answer and explanation
Correct answer: C
Explanation
AWS IoT Greengrass is the ideal solution for this scenario because it allows edge devices to process IoT data locally, reducing latency and enabling near-instant responses. It also integrates seamlessly with AWS services like Amazon S3 for centralized storage and analytics. This makes it a perfect fit for distributed compute strategies in IoT use cases.
- A. Incorrect.
AWS Lambda@Edge is designed for use with Amazon CloudFront to customize web content delivery. While it can process data at edge locations, it is not suitable for processing IoT sensor data and managing the transfer of processed data to a central AWS Region.
- B. Incorrect.
Deploying Amazon EC2 instances across multiple AWS Regions can process data, but it requires significant operational overhead to manage instances, scaling, and transferring processed data to a central AWS Region.
- C. Correct.
AWS IoT Greengrass extends AWS services to edge devices, enabling them to locally process IoT data, respond in real time, and send processed data to the central AWS Region (e.g., Amazon S3). This approach minimizes latency and is optimal for distributed compute strategies.
- D. Incorrect.
Amazon CloudFront is a content delivery network (CDN) that caches data for faster delivery to users. It is not designed for processing IoT data, and Amazon Redshift is not intended for real-time edge processing but rather for analytics on structured data.