API Failures
TLDR: API failures occur when an API does not respond as expected, resulting in disruptions to applications or services relying on it. These failures can arise from misconfigurations, timeouts, authentication issues, or improper handling of edge cases. Since APIs are critical to modern software ecosystems, their failures can significantly impact system performance and user experience.
https://en.wikipedia.org/wiki/API
One common cause of API failures is poor error handling. For example, if an API returns ambiguous error codes or messages during an authentication failure, developers may struggle to identify the root cause. Using standard HTTP status codes and providing actionable error messages helps mitigate this issue and aligns with industry best practices for API design.
https://www.restapitutorial.com/httpstatuscodes.html
Another frequent issue is a lack of resiliency against high traffic or unexpected loads, leading to API downtime or throttling. Implementing techniques like rate limiting, circuit breakers, and retry policies ensures that systems degrade gracefully under stress. Proper monitoring and scaling mechanisms, such as auto-scaling groups, further enhance reliability.
https://aws.amazon.com/autoscaling/
API failures often stem from dependency issues, such as reliance on third-party services that become unavailable. To address this, developers can implement fallback mechanisms and asynchronous processing to reduce user-facing disruptions. Regular testing and monitoring using tools like Postman or Swagger ensure that API functionality remains robust and reliable.