How does GraphQL handle real-time data and subscriptions?
- By periodically polling the server for updates
- By sending email notifications to clients
- By using RESTful APIs
- By using WebSockets to establish persistent connections
GraphQL handles real-time data and subscriptions by using WebSockets to establish persistent connections. This allows the server to push updates to clients as soon as new data is available, enabling real-time interaction without the need for frequent polling, which is both inefficient and less responsive in comparison.
In GraphQL, _____ allows clients to receive real-time updates when data they are interested in changes.
- GraphQL Query
- RESTful API
- SOAP
- Subscriptions
In GraphQL, Subscriptions allow clients to receive real-time updates when data they are interested in changes. Subscriptions enable a publish-subscribe model, enhancing the real-time capabilities of GraphQL.
Why is it important to perform load testing on an API?
- To ensure the API can handle expected traffic loads
- To evaluate the API's functionality and features
- To identify security vulnerabilities
- To improve API documentation
Load testing is essential for APIs to ensure they can handle expected traffic loads without performance degradation. It helps identify bottlenecks, scalability issues, and performance limitations, ensuring that the API can deliver a seamless experience to users under varying loads.
OpenID Connect is built on top of _____ and is used for user authentication.
- HTTPS
- JSON
- OAuth
- XML
OpenID Connect is built on top of OAuth and is used for user authentication. OAuth is a widely-used authorization protocol that allows third-party applications to access a user's resources without exposing their credentials. OpenID Connect extends OAuth to provide user authentication and allows applications to verify the identity of end-users.
How can rate limiting errors be identified and resolved during API debugging?
- Analyze user interface design
- Examine HTTP status codes and headers
- Monitor response time and latency
- Review API documentation
Rate limiting errors in APIs can be identified and resolved during debugging by examining HTTP status codes and headers. When an API rate limit is exceeded, the server typically responds with specific status codes or headers that indicate the issue. Understanding these indicators is crucial for debugging and resolving rate limiting errors.
What benefits does GraphQL offer over traditional REST APIs?
- Automatic generation of API documentation
- Better caching and query optimization
- Improved security and authentication mechanisms
- Simplicity in handling complex data structures
GraphQL offers benefits over traditional REST APIs, such as better caching and query optimization. GraphQL clients can request only the data they need, reducing over-fetching and under-fetching, which can enhance the efficiency of data retrieval.
One way to optimize API performance is to reduce the _____ time for each request.
- Authentication Time
- Bandwidth
- Latency
- Throughput
One way to optimize API performance is to reduce the latency time for each request. Latency represents the delay in communication between the client and server. Reducing latency leads to faster response times, improving the overall performance of the API.
A _____ API is typically exposed to external developers and may be used to extend the functionality of a platform.
- Internal
- Private
- Public
- Shared
A "Public" API is typically exposed to external developers and allows them to extend the functionality of a platform or application. It's accessible to external parties for integration.
By implementing _____, an API can efficiently handle multiple requests without degrading the performance.
- Authentication
- Caching
- Compression
- Encryption
By implementing caching, an API can efficiently handle multiple requests without degrading performance. Caching involves storing and reusing frequently requested data, reducing the need for repeated processing and resource-intensive operations, thus enhancing API efficiency.
How does GraphQL handle under-fetching and over-fetching of data compared to REST?
- It doesn't handle under-fetching or over-fetching, leaving it to the client's discretion.
- It handles under-fetching by automatically retrieving all available data and prevents over-fetching by limiting requests to one item at a time.
- It relies on server-side filtering to address both under-fetching and over-fetching issues.
- It solves under-fetching by enabling clients to request exactly the data they need, and it avoids over-fetching by reducing unnecessary data transfer.
GraphQL effectively handles under-fetching and over-fetching of data by allowing clients to specify exactly what data they need, eliminating the need to make multiple requests for related data and minimizing unnecessary data transfer. This results in more efficient data retrieval.