✅ STAR Method Explanation of Your Serverless REST API Project

🟠 S – Situation

In a project focused on building lightweight, cost-efficient APIs, there was a need to eliminate traditional server management and reduce hosting costs while maintaining high performance, scalability, and uptime.

🟡 T – Task

Your task was to build a serverless REST API using AWS Lambda and API Gateway, integrate it with DynamoDB for data storage, and secure it using IAM roles — all while ensuring minimal latency and high availability.

🔵 A – Action (Step-by-Step Breakdown)

Designed the API Structure
- Planned endpoints (GET, POST, PUT, DELETE) using REST principles.
- Decided on data to be stored in DynamoDB (e.g., userId, name, email).
Created Lambda Functions
- Used AWS Lambda to create backend logic for each API route.
- Wrote functions in Node.js or Python to handle input, process logic, and return JSON responses.
Configured API Gateway
- Set up a REST API in Amazon API Gateway.
- Created resource paths (/users, /users/{id}) and HTTP methods.
- Integrated each route with the corresponding Lambda function.
Connected DynamoDB
- Created a DynamoDB table with userId as the primary key.
- Lambda functions performed CRUD operations using the AWS SDK.
IAM Role Configuration
- Created IAM execution roles for Lambda with permission to access DynamoDB.
- Configured API Gateway to use IAM authentication for secure access.
Testing
- Tested API endpoints using Postman and curl.
- Ensured proper error handling, response formatting, and validation.
Deployment
- Deployed API to a public endpoint.
- Enabled CORS to allow frontend consumption.

🟢 R – Result

✅ Achievements:

Reduced infrastructure cost by ~90% compared to EC2-based hosting.
Achieved 99.99% uptime using AWS-managed infrastructure.
Improved API response time using DynamoDB’s millisecond-level latency.
No server maintenance required → Highly scalable and auto-healing.

💬 How to Say It in the Interview (Sample Answer)

“In one of my cloud projects, I developed a serverless REST API using AWS Lambda and API Gateway to eliminate the need for traditional servers. I created Lambda functions for each endpoint and integrated them with API Gateway routes. I used DynamoDB as the NoSQL database and configured IAM roles to securely enable Lambda access to the DB. The result was a fully serverless, cost-efficient, and highly available API with minimal latency, which reduced hosting costs by 90% and provided 99.99% uptime.”

❓ 10 Common Interview Follow-Up Questions with Sample Answers

1. Why did you choose serverless over EC2 or containers?

Answer:
Serverless provides automatic scaling, pay-per-invocation pricing, and no server management. It’s ideal for event-driven APIs or low to medium workloads. It drastically reduced infrastructure overhead and cost.

2. What programming language did you use for Lambda?

Answer:
I used Node.js (JavaScript) for Lambda due to its fast cold-start time and native support in AWS Lambda. It's also great for handling JSON responses and integrates easily with the AWS SDK.

3. How did you manage authentication and security?

Answer:
I used IAM roles for Lambda to securely access DynamoDB, and I also configured resource-based policies on API Gateway. Additionally, I enabled CORS and could have integrated Cognito for user-level authentication in future versions.

4. How does API Gateway connect to Lambda?

Answer:
Each API method in API Gateway is mapped to a Lambda function. When a client sends an HTTP request, API Gateway triggers the corresponding Lambda function and returns its response back to the client.

5. How did you handle errors in Lambda?

Answer:
I used try-catch blocks in my Lambda functions and returned proper HTTP status codes (e.g., 400 for bad input, 500 for server error). API Gateway was also configured to map errors to readable messages.

6. What is the cost model of Lambda and how is it cheaper?

Answer:
Lambda charges based on number of requests and compute time (ms). Since there are no idle costs and you don’t pay for unused capacity, it can save up to 90% compared to EC2 for low/moderate usage.

7. How did you structure data in DynamoDB?

Answer:
I used a single table with userId as the primary key. DynamoDB's schema-less nature allowed flexibility in storing different user data fields as needed.

8. How did you test and monitor the APIs?

Answer:
I used Postman for functional testing. For monitoring, I relied on CloudWatch Logs to debug Lambda function execution, and set up custom metrics to track request counts and errors.

9. How do you handle scaling with this setup?

Answer:
Scaling is automatic in serverless architecture. Lambda scales based on concurrent requests, and API Gateway can handle thousands of requests per second without manual intervention.

10. If traffic spikes, how does your system handle it?

Answer:
Lambda functions spin up more instances in parallel to handle high traffic. API Gateway and DynamoDB are also designed to scale automatically, so the architecture is resilient to sudden load increases.

⚠️ 5 Common Challenges You May Have Faced (and How You Handled Them)

Cold Start Latency
- Challenge: Initial delay in Lambda startup.
- Fix: Minimized dependencies and optimized code structure.
IAM Permissions Errors
- Challenge: Lambda couldn’t access DynamoDB due to insufficient permissions.
- Fix: Fine-tuned IAM roles and policies using least privilege principles.
CORS Issues in Frontend Integration
- Challenge: Browser blocked API requests.
- Fix: Enabled CORS headers in API Gateway.
Error Handling Consistency
- Challenge: Error responses were inconsistent.
- Fix: Standardized error format with status codes and messages across all functions.
JSON Event Parsing
- Challenge: Event structure from API Gateway to Lambda was confusing initially.
- Fix: Carefully extracted event.body, event.pathParameters, etc., and used JSON.parse.

Serverless REST API with AWS Lambda, API Gateway, and DynamoDB