Which metric is crucial for understanding the performance of APIs in production?

  • Number of API endpoints
  • Response time
  • Server disk space
  • User interface design
The response time is a crucial metric for understanding the performance of APIs in production. It measures the time it takes for an API to respond to a request, directly impacting user experience. Monitoring and optimizing response time are essential to ensure efficient and reliable API performance in a production environment.

For handling stateful operations, which API style is more suitable?

  • Both RESTful and SOAP APIs can handle stateful operations
  • GraphQL
  • RESTful API
  • SOAP API
SOAP APIs are better suited for handling stateful operations as they support features like sessions and transactions. RESTful APIs, on the other hand, are stateless by design, making them more suitable for stateless interactions.

In API versioning, what does semantic versioning (SemVer) typically involve?

  • Major.Minor.Patch format
  • Random version numbers
  • Sequential numbering
  • Year.Month.Day format
Semantic versioning (SemVer) follows the Major.Minor.Patch format, where the major version is for backward-incompatible changes, the minor version for backward-compatible additions, and the patch version for backward-compatible bug fixes. This approach helps developers understand the nature of changes at a glance.

The practice of _________ in CI/CD allows for early detection of defects in API integration.

  • Continuous Deployment
  • Continuous Integration
  • Continuous Monitoring
  • Continuous Testing
Continuous Testing in CI/CD is a crucial practice that enables the early detection of defects in API integration. By continuously testing the application throughout the pipeline, teams can identify issues early on, preventing the propagation of defects to later stages. This practice ensures the reliability and stability of the API integration process.

In tools like Postman, what is the purpose of using Collections?

  • Data Encryption
  • Grouping requests
  • Load Testing
  • Session Management
In tools like Postman, Collections serve the purpose of grouping related requests together. They allow users to organize and manage their API requests efficiently, making it easier to execute and maintain a suite of requests for a specific use case or project.

How do microservices communicate with each other in a typical microservices architecture?

  • Asynchronous Communication
  • Direct Memory Access
  • Shared Database
  • Synchronous Communication
Microservices typically communicate using asynchronous communication, allowing them to function independently without directly relying on each other's real-time responses.

What is the role of mock services in the context of API script automation?

  • Generating random test data
  • Optimizing script execution speed
  • Simulating external dependencies
  • Validating API documentation
Mock services simulate external dependencies, allowing API scripts to run in controlled environments. This helps in isolating the testing scope, ensuring reliable and repeatable results. It also facilitates testing scenarios that may be challenging to reproduce with real services.

In a banking system requiring high security and standardized operations, which API type would you recommend?

  • GraphQL
  • RESTful API
  • SOAP API
  • WebSockets
In a banking system, security and standardized operations are paramount. SOAP APIs provide a strict protocol for communication, ensuring reliability and security. RESTful APIs, while widely used, may not enforce standardized operations to the same extent. GraphQL and WebSockets may introduce unnecessary flexibility and potential security risks.

How does data partitioning impact API testing with large data sets?

  • Has no effect
  • Improves performance
  • Increases latency
  • Results in data loss
Data partitioning in API testing with large data sets impacts performance positively. It allows parallel processing, reducing execution time.

Ensuring the consistency of _________ across various test environments is vital for reliable API testing.

  • Authentication Tokens
  • Data Encryption
  • Request Headers
  • Test Data
Ensuring the consistency of test data across various test environments is vital for reliable API testing. Consistent test data helps in validating the functionality and performance of APIs under different conditions. It ensures that the API behaves consistently across development, testing, and production environments, reducing the likelihood of unexpected issues in real-world scenarios.