AWS Certified Solutions Architect - Associate
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A bicycle sharing company is developing a multi-tier architecture to track the location of its bicycles during peak operating hours. The company wants to use these data points in its existing analytics platform. A solutions architect must determine the most viable multi-tier option to support this architecture. The data points must be accessible from the REST API.
Which action meets these requirements for storing and retrieving location data?
Other
Community
UAnonymous
A
Use Amazon Athena with Amazon S3.
B
Use Amazon API Gateway with AWS Lambda.
C
Use Amazon QuickSight with Amazon Redshift.
D
Use Amazon API Gateway with Amazon Kinesis Data Analytics.
Explanation:
Explanation
Correct Answer: B - Use Amazon API Gateway with AWS Lambda
Why this is correct:
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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.
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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.
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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.
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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.
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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:
- Bicycle devices send location data → API Gateway (REST endpoint)
- API Gateway triggers Lambda function
- Lambda processes data and stores in appropriate storage (S3, DynamoDB, etc.)
- Analytics platform can access stored data
- 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.
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