Answer: Use Amazon API Gateway with AWS Lambda.

## Explanation **Correct Answer: B - Use Amazon API Gateway with AWS Lambda** **Why this is correct:** 1. **Real-time data processing**: The scenario describes tracking bicycle locations during peak operating hours, which implies real-time or near-real-time data processing requirements. 2. **REST API accessibility**: The requirement explicitly states that "data points must be accessible from the REST API." Amazon API Gateway is specifically designed to create, publish, maintain, monitor, and secure REST APIs. 3. **Serverless architecture**: AWS Lambda provides serverless compute that can process incoming location data, transform it, and store it in a suitable data store for analytics. 4. **Multi-tier architecture**: API Gateway + Lambda creates a clean separation between the API layer (Gateway) and the business logic layer (Lambda), which aligns with multi-tier architecture principles. 5. **Integration with analytics platform**: Lambda can write processed location data to various analytics-friendly storage solutions like Amazon S3, Amazon DynamoDB, or Amazon Kinesis Data Streams for further analysis. **Why other options are incorrect:** **A. Use Amazon Athena with Amazon S3**: - Athena is a query service for analyzing data in S3 using SQL - While S3 can store location data, this combination doesn't provide a REST API interface - Athena is better for batch analytics rather than real-time tracking **C. Use Amazon QuickSight with Amazon Redshift**: - QuickSight is a business intelligence/visualization tool - Redshift is a data warehouse for analytics - This combination is for data visualization and reporting, not for real-time tracking with REST API access **D. Use Amazon API Gateway with Amazon Kinesis Data Analytics**: - While API Gateway provides the REST API interface - Kinesis Data Analytics is for real-time analytics on streaming data - This misses the compute layer (like Lambda) to process and route the data appropriately - Kinesis Data Analytics is more about analyzing streaming data rather than storing and retrieving individual data points via REST API **Architecture Flow:** 1. Bicycle devices send location data → API Gateway (REST endpoint) 2. API Gateway triggers Lambda function 3. Lambda processes data and stores in appropriate storage (S3, DynamoDB, etc.) 4. Analytics platform can access stored data 5. REST API can retrieve stored data through same API Gateway + Lambda pattern This solution provides scalability during peak hours, cost-effectiveness through serverless pricing, and clean separation of concerns in a multi-tier architecture.

Author: LeetQuiz Editorial Team