Handling Mismatched API Calls In API Replay Systems

Hey guys! Let's dive into a recent discussion regarding how the Replay API handles situations where a requested API call doesn't have a matching recorded call. This is a super important topic for anyone working with API testing and replay systems, so let's get started!

The Problem: No Matching Call, Big Error

The core issue we're tackling is what happens when the Replay API can't find a recorded call that matches the current request. Currently, the system throws an error, which can be a bit disruptive, especially in dynamic testing environments. Check out this example output from a recent session:

replay-api: Searching for matching call in file reader-test.json: GET https://server.com/orders?page_size=200&offset=0&date_added_range=1609459200,1640995200
464 |         }
465 |         const searchResult = await this.replayer.findMatchingCall(request, this.matcher);
466 |         if (!searchResult.call) {
467 |           const errorMessage = `No matching recorded call found for: ${request.method} ${request.url}`;
468 |           if (searchResult.searchDetails) {
469 |             throw new Error(`${errorMessage}
                        ^
error: No matching recorded call found for: GET https://server.com?page_size=200&offset=0&date_added_range=1609459200,1640995200

Search details:
{
  "method": "GET",
  "url": "https://server.com/orders?page_size=200&offset=0&date_added_range=1609459200,1640995200",
  "pathname": "/orders",
  "queryParams": {
    "page_size": "200",
    "offset": "0",
    "date_added_range": "1609459200,1640995200"
  },
  "headers": {
    "accept": "application/json",
    "x-authorization": "<REDACTED>"
  },
  "body": null,
  "availableRecordings": []
}

As you can see, the API diligently searches for a matching call within the reader-test.json file. When it comes up empty-handed for the specific GET request to https://server.com/orders?page_size=200&offset=0&date_added_range=1609459200,1640995200, it throws a No matching recorded call found error. This error is triggered because the searchResult.call is null, indicating no match was found. The error message provides valuable debug information, including the request method (GET), the full URL, and detailed search parameters like the pathname, query parameters, headers, and body. This level of detail helps in pinpointing the exact discrepancy between the requested call and the available recordings. Furthermore, the output includes a structured representation of the search details, such as the method, URL, pathname, query parameters, headers (with sensitive information redacted), and body. This comprehensive overview aids developers in understanding why the call couldn't be matched, enabling them to refine their recording strategies or adjust the replay mechanism for better accuracy. The inclusion of the availableRecordings array, which is empty in this case, serves as a clear indicator that no suitable recordings exist for this specific request, prompting further investigation into the recording setup or the expected API behavior.

Why is This a Problem?

While throwing an error is a safe default, it can be a bit rigid. In many situations, especially during development and testing, it would be super helpful if the system could handle these mismatches more gracefully. Imagine a scenario where your API is constantly evolving, and you're adding new endpoints or modifying existing ones. An error-heavy approach can quickly become a bottleneck, halting the testing process and requiring manual intervention for every mismatch.

The Suggested Solution: A More Flexible Approach

The suggestion on the table is to change the behavior when no matching call is found. Instead of throwing an error immediately, the API should try to make the actual API call. Here's the key idea:

• Try the Real Call: If no match is found in the recorded data, the system should attempt to execute the actual API request against the target server.
• Record the Response (If it has a body): If the real API call returns a response with a body, the system should then record this response. This effectively creates a new recording for future replays.

This approach has the potential to make the Replay API much more adaptable and resilient to changes. By dynamically recording new calls, it can keep up with API evolution and reduce the friction in testing workflows. It ensures that the API replay system can adapt to changes in the API landscape, making the testing process more robust and less prone to interruptions. This dynamic adaptation is particularly beneficial in agile development environments where APIs are subject to frequent modifications and updates. By automatically recording new responses, the system minimizes the need for manual intervention and keeps the recorded interactions synchronized with the evolving API structure. Furthermore, this strategy promotes a more comprehensive testing coverage by capturing a wider range of API behaviors and edge cases, which might not be readily available in the initial set of recordings. The ability to dynamically record API calls not only streamlines the testing process but also enhances the quality and reliability of the system under test.

Diving Deeper: Benefits and Considerations

Let's break down the benefits and potential considerations of this proposed solution.

Benefits: The Upsides of Dynamic Recording

• Reduced Friction in Testing: By automatically handling mismatched calls, the system avoids interrupting the testing flow with errors. This allows for smoother, more continuous testing.
• Adaptability to API Evolution: The dynamic recording capability allows the Replay API to adapt to changes in the API. New endpoints or modified responses are automatically recorded, keeping the replay system up-to-date.
• Improved Test Coverage: By making real calls and recording the responses, you can capture a wider range of API behaviors, including edge cases and responses that might not have been initially recorded.
• Self-Healing Replay System: The system essentially