DVA-C02 Development with AWS Services Practice Question
Which TWO of the following are benefits of using Amazon API Gateway to manage APIs? (Choose two.)
⚠ Common exam trap
A common mix-up: candidates confuse API Gateway's integration capabilities (e.g., proxying to S3 or RDS) with built-in backend features like caching or connection pooling, leading them to select options that describe backend functionality rather than API management features.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Throttling and rate limiting of API requests
Option C is correct because API Gateway provides built-in throttling and rate limiting through usage plans and API keys, allowing you to control request rates per client and protect backend services from being overwhelmed. Option D is correct because API Gateway can automatically generate client SDKs for multiple programming languages (such as Java, JavaScript, Python, and iOS/Android) from an API's definition, simplifying client integration. Option A is not a feature of API Gateway, which does not cache database queries to Amazon RDS; it can cache API responses at the stage level, but not RDS queries. Option B is inaccurate as a benefit of API Gateway itself, since API Gateway can proxy to S3 but does not provide direct S3 file storage management as a core API management benefit. Option E is incorrect because automatic connection pooling for backend databases is handled by services like Amazon RDS Proxy, not API Gateway.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Built-in caching of database queries to Amazon RDS
Why it's wrong here
Amazon API Gateway offers a configurable caching mechanism to cache responses from your backend integrations, reducing the load on your backend services and improving latency for clients. However, this caching is at the API response level, not an intelligent, built-in cache specifically designed to optimize or store results of database queries directly against Amazon RDS. It caches the entire HTTP response body for a given request, not individual database query results.
- ✗
Direct integration with Amazon S3 for file storage
Why it's wrong here
While Amazon API Gateway can be configured to integrate with Amazon S3, allowing API requests to trigger S3 operations like GetObject or PutObject for file manipulation, it does not provide direct file storage capabilities itself. API Gateway acts as a front door for your backend services, including S3, but it is not a storage service where files are directly uploaded to or managed by API Gateway. Its role is to expose S3 actions as RESTful APIs.
- ✓
Throttling and rate limiting of API requests
Why this is correct
Amazon API Gateway provides robust capabilities for throttling and rate limiting API requests, which is crucial for protecting backend services from being overwhelmed and ensuring fair usage among consumers. You can configure global request limits, burst limits, and even define usage plans with specific quotas and throttles per API key. This prevents denial-of-service attacks and maintains API stability under high load.
- ✓
Generation of client SDKs for multiple programming languages
Why this is correct
Amazon API Gateway significantly simplifies client development by automatically generating client SDKs in various programming languages, such as Java, JavaScript, Python, Ruby, and Objective-C, directly from your API's OpenAPI (Swagger) definition. This feature allows developers to quickly integrate with your API without manually writing HTTP request logic, reducing development time and potential errors. The generated SDKs abstract away the complexities of signing requests and handling serialization.
- ✗
Automatic connection pooling for backend databases
Why it's wrong here
Amazon API Gateway operates as a front-end service for managing API requests and routing them to backend integrations, such as AWS Lambda functions or HTTP endpoints. It does not inherently provide automatic connection pooling for backend databases. Connection pooling is typically managed by the application code within the backend service itself or by a dedicated database proxy service like Amazon RDS Proxy, which sits between the application and the database.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
Go deeper
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DVA-C02 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DVA-C02 exam.