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Answer: Use Amazon API Gateway with AWS Lambda functions to receive the data from the sensors, process the data, and store the data in an Amazon DynamoDB table.
## Explanation **Correct Answer: A** **Why Option A is correct:** 1. **Managed Services**: API Gateway, Lambda, and DynamoDB are all fully managed AWS services, minimizing operational overhead. 2. **Serverless Architecture**: Lambda functions automatically scale and require no server management. 3. **HTTP Requests**: API Gateway is designed to handle HTTP requests from sensors efficiently. 4. **Data Aggregation**: Lambda can process and aggregate energy consumption data before storing in DynamoDB. 5. **Future Features**: The serverless architecture allows easy addition of independent components without managing infrastructure. 6. **Cost-Effective**: Pay-per-use pricing model for Lambda and DynamoDB. **Why other options are incorrect:** **Option B**: Uses EC2 instances (not fully managed) and S3 (object storage not ideal for database operations). Requires managing Auto Scaling groups and EC2 instances. **Option C**: Uses managed services (API Gateway, Lambda) but stores data in SQL Server on EC2 instance, which requires database administration and server management. **Option D**: Uses EC2 instances (not fully managed) and EFS (file storage not ideal for database operations). Requires managing both compute and storage infrastructure. **Key Requirements Met:** - ✅ Use managed services when possible - ✅ Handle HTTP requests from sensors - ✅ Store and aggregate hourly energy consumption - ✅ Support future independent components - ✅ LEAST operational overhead
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A solutions architect is designing a workload that will store hourly energy consumption by business tenants in a building. The sensors will feed a database through HTTP requests that will add up usage for each tenant. The solutions architect must use managed services when possible. The workload will receive more features in the future as the solutions architect adds independent components.
Which solution will meet these requirements with the LEAST operational overhead?
A
Use Amazon API Gateway with AWS Lambda functions to receive the data from the sensors, process the data, and store the data in an Amazon DynamoDB table.
B
Use an Elastic Load Balancer that is supported by an Auto Scaling group of Amazon EC2 instances to receive and process the data from the sensors. Use an Amazon S3 bucket to store the processed data.
C
Use Amazon API Gateway with AWS Lambda functions to receive the data from the sensors, process the data, and store the data in a Microsoft SQL Server Express database on an Amazon EC2 instance.
D
Use an Elastic Load Balancer that is supported by an Auto Scaling group of Amazon EC2 instances to receive and process the data from the sensors. Use an Amazon Elastic File System (Amazon EFS) shared file system to store the processed data.