¿Cuáles son algunas de las prácticas recomendadas para el manejo y la generación de informes de errores de API?

- 📋 Use consistent and meaningful error codes, following HTTP status codes (4xx for client errors, 5xx for server errors) and custom subcodes for specificity. - 📚 Document and standardize error codes across all API endpoints and versions for clarity and consistency. - 🗣️ Provide clear, descriptive error messages with details on what went wrong and how to fix it. - 🛠️ Include error handling in API design to gracefully manage common failure scenarios. - 📊 Log errors with sufficient detail for debugging, including request IDs and timestamps. - 🔄 Implement retry logic and rate limiting to handle transient errors and prevent server overload. - 📧 Notify users and admins of critical errors through alerts or notifications.

Here are some best practices for handling API errors: Use Standard HTTP Status Codes Provide Descriptive Error Messages Error Formatting Include Error Codes Error Response Payload Provide Proper Information Logging and Monitoring OAuth Token Expiry Handling By following these best practices, you can enhance the error handling and reporting capabilities of your API.

For effective API error handling and reporting, use proper HTTP status codes, provide structured error responses with codes, messages, and relevant details, categorize errors, implement logging/monitoring, document the approach, ensure backwards compatibility and follow security practices.

For API error handling: - Use clear messages and appropriate HTTP status codes. - Have detailed documentation and robust monitoring. - Regularly review and update handling strategies for improvement.

The use of appropriate HTTP status codes, the implementation of retry mechanisms, the provision of informative error messages, and the logging of problems for analysis and troubleshooting are some best practises for handling API issues.

Error messages should be clear, helpful, and explain the cause and solution. Use JSON/XML for structured responses with code, message, details, and suggestions. Employ plain language, avoid jargon, and localize for different languages and formats.

When we add an error message in the case of an exception, we need to wear the shoes of our customers. Most of them are non-technical. The error messages can be meaningful to you as a developer or QA engineer, but they can be Greek to the common end users. There is no use in showing error codes to the end users. Are they going to analyze the HTTP error code and fix them? Big No. If you are developing your application for normal non-technical users, show something useful to them instead.

One of these best practices is to provide clear and helpful error messages. Error messages should be clear, helpful, and explain the cause and solution. Use JSON/XML for structured responses with code, message, details, and suggestions. This can be achieved by using formats like JSON or XML to structure the error response with details such as error code, message, details, and suggestions. It is also important to use plain language and avoid technical jargon or abbreviations that might confuse users or developers. Furthermore, localization and internationalization techniques can be used to provide error messages in different languages and formats based on user preferences and location.

Ensure that error messages provided for API error handling are clear and informative. If an error pertains to an entity, the message should explicitly outline the issue and suggest corrective actions. Additionally, include appropriate status codes for easier understanding. For example: If there's an issue with the provided entity, return a response with a detailed error message specifying the problem and instructions on how to rectify it. Utilize suitable HTTP status codes (e.g., 400 Bad Request) to enhance clarity and facilitate user comprehension.

Multi-application environment is the new norm. Which means, we need to provide the maximum possible information captured by the application during the execution of the transaction to know the nature of the transaction, the error observed and the state of the applications involved during the transaction. This helps teams analyze and resolve the error. The error messages should be only for the logging purpose. The erred response from server to client side, on the contrary, should be containing minimal required information for the navigation of the mobile/web app to proceed.

I recommend we build logger beacons into all our scripts - maybe Postman or RestAssured - to light up with details whenever a funky response appears. These will scream if our precious APIs get ambushed or go rogue for any reason. We also need monitoring raadar blasting 24/7 for security risks, performance crises, availability attacks - the whole works! Splunk or New Relic can help us assemble urgent incident reports. And let's use Jira tickets to call all cyber heroes to troubleshoot issues together. We can hop on group chats as soon as alarms sound to protect our city!

A robust error handling system includes the implementation of error logging and monitoring. Logging details about encountered errors, along with relevant contextual information, aids in post-mortem analysis and debugging. Real-time monitoring allows for proactive identification of issues, enabling timely intervention and minimizing potential disruptions.

According to some sources, some of the best practices for API error handling and reporting are: Use standard HTTP status codes to indicate the type and severity of errors. Provide additional error codes and messages in the response body to give more details and context about the error Use a consistent and well-defined format for error messages, such as JSON, XML, or plain text Log errors for troubleshooting and monitoring purposes, using tools like Apidog or Skillsoft Implement error handling and reporting at different levels of the API, such as the controller, the service, and the client You can find more information and examples from these web sources.

Best Practice: Implement Error Logging and Monitoring Error logging and monitoring are vital for proactive error management in APIs. Log detailed error data like timestamps and request details centrally for easy access. Set up alerts to notify administrators of critical errors in real-time. Monitor performance metrics to assess API health and identify trends. Conduct trend analysis to address recurring issues effectively. Integrate with monitoring tools for seamless management and visibility, ensuring high service availability and reliability.

Implement Error Logging and Monitoring: Treat error logs like a detective's notebook—they help you uncover clues and patterns to solve mysteries. Set up systems to log errors systematically and keep an eye on them in real-time. It's like having a watchful guardian alert you to trouble before it escalates.

Adhering to the fail-fast and fail-safe principles ensures a proactive approach to error handling. Fail-fast involves detecting and addressing errors as early as possible in the process, preventing the propagation of issues. Fail-safe ensures that even in the presence of errors, the system can gracefully degrade, minimizing the impact on users and downstream processes.

Best practices for API error handling and reporting are: Use HTTP status codes to indicate the general nature of the error, such as 400 for client errors and 500 for server errors. Use domain-specific error codes to provide more detailed information about the error, such as what caused it and how to fix it. Include error messages in the response body to help API consumers understand the error context and provide actionable feedback. Generate a unique error trace ID for each error and include it in the response header or body. This can help API developers to track and debug errors more easily. Implement retry logic and exponential backoff for transient errors, such as network failures or service unavailability.

Test-Driven Development (TDD) is a powerful approach that supports the fail-fast principle in REST API development. In TDD, you write tests before writing the actual code. These tests are designed to fail initially, which provides immediate feedback when the implementation does not meet the requirements. Writing tests first defines clear specifications for what the API should do. This helps in ensuring that the implementation adheres to these expectations from the start. Tests act as a specification that drives development, reducing ambiguities and misalignments between the code and its requirements.

Best Practice: Follow Fail-Fast and Fail-Safe Principles To implement these principles: Fail-Fast: Immediately detect errors and halt execution to prevent cascading failures. Use assertions, validations, and input sanitization to catch errors early in the request processing pipeline. Return informative error responses to clients to facilitate prompt resolution. Fail-Safe: Design systems to gracefully handle errors and maintain stability. Implement fault tolerance mechanisms such as retries, circuit breakers, and fallback strategies to mitigate the impact of failures. Provide fallback mechanisms or alternative paths to ensure uninterrupted service availability.

Follow the Fail-Fast and Fail-Safe Principles: Picture your API as a safety net—when something goes wrong, it should catch you without causing more harm. Detect errors early to prevent further damage (fail-fast) but also handle them gracefully to avoid a domino effect of failures (fail-safe).

Transparent communication with stakeholders is a key best practice in API error handling. Keep users informed about system status, maintenance schedules, and any potential disruptions. Establishing channels for feedback and collaboration with users can provide valuable insights for improving error handling processes and user experience.

1. Research your stakeholders 2. Identify what is at stake for everyone 3. Learn each stakeholder’s language 4. Set specific expectations for everyone 5. Show how stakeholder input is put to work

In the API first world, error codes & messages must be communicated clearly. If the API is being used for a long time, versioning can be done to support backward compatibility. In my experience based on the stakeholder type, the documentation must be crafted.

Best Practice: Communicate and Collaborate with Stakeholders Maintain Open Channels: Keep developers, product managers, and support teams informed through regular updates. Share Strategies: Educate stakeholders on error handling methods and best practices. Seek Feedback: Actively solicit input on error handling processes and tools. Collaborate on Incidents: Work together during outages to diagnose and resolve issues promptly. Celebrate Successes: Recognize achievements in error handling and system reliability. Learn from Failures: Conduct post-incident reviews to identify areas for improvement.

Communicate and Collaborate with Your Stakeholders: Treat your users like allies on a shared journey—they'll appreciate being kept in the loop. Keep communication channels open with developers and end-users, gathering feedback to refine your error-handling strategy and ensure everyone stays on the same page.

Best Practice: Learn from Errors and Improve API Testing Continuous improvement is key to effective API testing. To learn from errors and improve API testing: Error Analysis: Thoroughly investigate API errors to understand their root causes and underlying issues. Identify Patterns: Look for recurring error patterns or trends across testing scenarios and production environments. Refine Test Cases: Adjust test cases to address discovered vulnerabilities or edge cases that led to errors. Update Test Environments: Ensure test environments accurately reflect production setups to simulate real-world conditions. Automate Testing: Automate repetitive testing tasks to increase efficiency and consistency in error detection.

A vital best practice in API error handling and reporting involves continuous learning and improvement of your API testing process. Utilize tools such as Kibana, Grafana, or Power BI to visually and analytically assess error trends, patterns, and root causes within your API testing. Implement automated API tests using tools like TestNG, JUnit, or PyTest to identify and prevent errors related to functionality, performance, or security. Additionally, employ behavior-driven testing tools like Cucumber, SpecFlow, or Behave to align API testing with business requirements and user expectations.

Learn from Your Errors and Improve Your API Testing: Errors are like teachers—they show you where you need to improve. Take each error as a lesson, analyzing what went wrong and adjusting your testing approach accordingly. It's all about continuous learning and evolving for the better.

Learn not only from "False positives" to improve your test script. but also equally (if not more) learn from "False negatives" (may be found by end users or manual QC teams).

Learn from Your Errors and Improve Your API Testing: Root Cause Analysis: Perform root cause analysis on frequent or critical errors to understand and address the underlying issues. Testing Enhancements: Incorporate error scenarios into your testing processes to ensure your API can handle them effectively.

HTTP status codes: Signal errors using standardized HTTP status codes. Use 404 for resource not found and 500 for internal server errors. Domain-specific error codes: Provide detailed insights with domain-specific error codes. Error messages in response body: Include clear, concise error messages in the response body. Global exception handler: Implement a global handler for consistent error processing. Retry logic for transient errors: Handle transient errors gracefully with retry logic. Logging: Log errors with key information for quick diagnosis. Documentation: Supply comprehensive documentation on error handling. Specific best practices may vary depending on the requirements of the API and the needs of the API consumers

From my experience, change in error code/message and not communicated may lead to embarrassment like app crash. Also error codes/messages can be clear but should not give specifics on the internals. This will aid attackers to gain access. When handling Authentication/authorisation error codes, generic message like "invalid credentials" is good rather than responding more specific error message.

From my experience, data sanitisation is key for verifying the APIs for security. APIs must allow the valid inputs and should not fall for XSS, SQL injection attacks.

API error handling and reporting include providing informative error messages, using appropriate HTTP status codes, implementing consistent error formats, offering error documentation, and logging errors for analysis and debugging.