Best Practices

To ensure a robust, maintainable, and user-friendly API integration, adhere to the following best practices:

Error Handling and Response Codes: Use appropriate HTTP status codes to indicate the outcome of API requests (e.g., 200 OK, 201 Created, 400 Bad Request, 401 Unauthorized, 404 Not Found, 500 Internal Server Error). Integration layer should react and respond to all error messages and ensure a proper handling of different HTTP error codes from 4xx to 5xx.
Rate Limiting and Request Throttling: Implement rate limiting to control the number of requests a client can make within a specified time window, preventing abuse or overloading of the API. Return the "429 Too Many Requests" status code when a client exceeds the limit.
Pagination and Filtering: Use pagination to break large data sets into smaller, manageable chunks. Implement query parameters for filtering, sorting, and searching to help clients access relevant data efficiently. For example, use "_itemsOnPage" and "_page" parameters to control the number of records returned and the starting position within the data set.
Caching and Performance Optimization: Utilize caching strategies, such as ETag and Last-Modified headers, to minimize the need for repetitive API calls and reduce the load on the server. Apply performance optimizations, like data compression and minification, to decrease response payload sizes and improve client-side performance.
Retry Mechanisms and Idempotency: Integrate retry mechanisms with exponential backoff for transient failures. This ensures that API requests are retried with increasing delays, minimizing the risk of overloading the system. Implement idempotent endpoints for non-idempotent HTTP methods like POST and PATCH, which allows clients to safely retry requests without causing unintended side effects.

Last updated 3 months ago

Was this helpful?

Best Practices

To ensure a robust, maintainable, and user-friendly API integration, adhere to the following best practices:

Error Handling and Response Codes: Use appropriate HTTP status codes to indicate the outcome of API requests (e.g., 200 OK, 201 Created, 400 Bad Request, 401 Unauthorized, 404 Not Found, 500 Internal Server Error). Integration layer should react and respond to all error messages and ensure a proper handling of different HTTP error codes from 4xx to 5xx.
Rate Limiting and Request Throttling: Implement rate limiting to control the number of requests a client can make within a specified time window, preventing abuse or overloading of the API. Return the "429 Too Many Requests" status code when a client exceeds the limit.
Pagination and Filtering: Use pagination to break large data sets into smaller, manageable chunks. Implement query parameters for filtering, sorting, and searching to help clients access relevant data efficiently. For example, use "_itemsOnPage" and "_page" parameters to control the number of records returned and the starting position within the data set.
Caching and Performance Optimization: Utilize caching strategies, such as ETag and Last-Modified headers, to minimize the need for repetitive API calls and reduce the load on the server. Apply performance optimizations, like data compression and minification, to decrease response payload sizes and improve client-side performance.
Retry Mechanisms and Idempotency: Integrate retry mechanisms with exponential backoff for transient failures. This ensures that API requests are retried with increasing delays, minimizing the risk of overloading the system. Implement idempotent endpoints for non-idempotent HTTP methods like POST and PATCH, which allows clients to safely retry requests without causing unintended side effects.

Last updated 3 months ago

Was this helpful?