Fixing Kibana Serverless Search Test Failures

Hey everyone! Have you ever run into a failing test in Kibana, especially when dealing with serverless search functional tests? It's a common hiccup, but don't worry, we'll break down the issue and how to tackle it. Let's dive into the specifics of a recent failure related to the TSVB Open in Lens Table within the Visualizations section. We'll analyze the error, understand the context, and explore potential solutions. This will help you get your tests back on track. Let's get started!

Understanding the Failing Test: Serverless Search and Kibana

So, the specific test that failed is the "Visualizations - Group 3 lens app - TSVB Open in Lens Table should convert group by field with custom label." This test is part of the serverless search functional tests within Kibana. It's designed to ensure that the TSVB (Time Series Visual Builder) visualizations correctly convert group-by fields, particularly when custom labels are applied. In simple terms, the test verifies that when you use a field to group data in a table and give it a special name (a custom label), everything displays as expected in the Lens table. If the test fails, it means something went wrong during this conversion process, likely causing an issue with how your data is presented in the table. That can be annoying, right? But, let's fix it!

Digging into the Error Message

Let's dissect the error message to understand what's going on. The error indicates a "timed out waiting for rendering count to stabilize." This means the test script waited a certain amount of time for the table to fully load and render, but it never happened. Specifically, it was looking for an element with the selector [data-test-subj="lnsDataTable"], which is likely the HTML element representing the Lens data table. The test waited for over 10 seconds (10056ms), and then gave up, resulting in a TimeoutError. Why did this happen? It is related to the test environment, network, or the resources being used. Don't worry, we'll consider the possible root causes and the solutions.

Root Causes: What Went Wrong and Why?

Let's consider the likely reasons for the test failure. Understanding the root causes is the first step in getting your tests back to passing!

1. Slow Rendering and Performance Issues

One of the most common culprits is slow rendering times. If the data set is large, the transformations are complex, or the server is under heavy load, it can take a while for the table to render fully. The test might be timing out because it's not waiting long enough for the table to finish loading all its data and visual elements. This is a very important part to focus on. Make sure that the resources being used are adequate and that the test is able to wait for the necessary time before failing.

2. Issues with Data Transformations and Custom Labels

As the test specifically mentions custom labels, there might be a bug in how Kibana handles these labels within the TSVB and Lens integration. When you create a custom label for a group-by field, the system needs to update the table with this new information. There could be an issue, such as a misconfiguration, with the field. If this transformation process fails or takes too long, it can lead to the rendering timeout.

3. Test Environment Problems

Problems in the testing environment itself can also lead to failures. The server might be under heavy load, the network might be slow, or there might be conflicts with other tests running simultaneously. These issues could be the cause of intermittent test failures that you cannot explain.

4. Browser Compatibility and Selenium Issues

Browser compatibility issues, or problems with the Selenium WebDriver used for the test, can sometimes cause elements not to load correctly. Perhaps there's a bug in the Selenium version that isn't compatible with the Kibana version being tested.

Solutions and Troubleshooting Steps

Now that we know what might be causing the test to fail, let's walk through a few solutions and troubleshooting steps to get things working again. The first step is to replicate the error and confirm what is happening.

1. Increasing the Timeout

The simplest solution might be to increase the timeout within the test. If the table is taking longer to render than the current timeout allows, extending the wait time may resolve the issue. You can adjust the timeout in the test configuration or directly in the test script. However, make sure that you don't extend the timeout too much, or you'll not identify the error. Try to investigate why the table is slow instead of just increasing the timeout. You can adjust it gradually and see if the test passes.

2. Optimizing Data and Performance

• Data Optimization: If the dataset is large, consider optimizing the data. Can you reduce the amount of data used in the test? Can you create a subset of data for testing? Can you pre-aggregate the data before it's displayed in the visualization? This will make the data rendering faster. Try to do that and see the results, it's a key factor in making sure the test runs smoothly.
• Performance Tuning: Check the Kibana server's performance during testing. Are there any bottlenecks in the system? Monitor CPU usage, memory, and network I/O. Consider increasing resources (CPU, memory) if necessary, especially in the test environment. This will help the server render the visualizations faster, and make sure the tests pass.

3. Reviewing the Test Script and Implementation

• Verify Selectors: Make sure the CSS selectors and data-test-subj attributes used to locate the table elements are correct. Ensure the element with data-test-subj="lnsDataTable" exists and is correctly identified in the test. If the selector is wrong, the test will not find the element.
• Test Logic: Review the test's logic to ensure it correctly waits for the table to render. It might be necessary to add explicit waits or checks to verify the table's contents before proceeding with the test assertions. You can check whether the custom label is correctly rendered in the table.

4. Checking Kibana and Plugin Versions

Verify that you're using compatible versions of Kibana, the Elastic Stack, and any relevant plugins. Sometimes, a version mismatch can lead to unexpected behavior and test failures. Make sure the version of the Elastic Stack is compatible with the Kibana version being tested. This will reduce the risk of compatibility problems.

5. Environment Troubleshooting

• Test Environment Isolation: If possible, run tests in an isolated environment to minimize interference from other processes or tests. The server should be stable and not experiencing any other problems while testing. It is also a very important factor to take into consideration.
• Network Issues: If there are network problems, they should be identified and fixed before testing. Check for any network latency or connection problems that might be affecting the test execution.

6. Debugging with Logging and Screenshots

• Increase Logging: Add more logging to your test scripts to understand what's happening during execution. Log the time taken for certain operations, and capture any error messages. You can use the debug logs to identify problems easily.
• Take Screenshots: Capture screenshots at different stages of the test, especially when the error occurs. This can help visualize the state of the UI and pinpoint any rendering problems. Visual inspection can be very helpful in finding the source of the error.

Advanced Troubleshooting: Beyond the Basics

If the above steps don't solve the problem, you might need to dive deeper into the issue.

1. Analyzing Kibana Logs

Kibana logs can provide valuable insights into what's happening on the server. Check the logs for any errors or warnings that might be related to the rendering of the TSVB visualization or the Lens table. Errors in the logs can point to a specific problem in the code. Look for stack traces or error messages that can help identify the source of the problem.

2. Profiling and Performance Analysis

Use performance profiling tools to analyze the performance of the Kibana server and the browser during test execution. This can help you identify specific bottlenecks in the rendering process. You can use tools like the Chrome DevTools to analyze the performance of the browser. Performance analysis can help you identify and eliminate performance bottlenecks.

3. Contacting Elastic Support

If you've tried everything and the test still fails, don't hesitate to contact Elastic support. Provide them with detailed information about the test, the error message, the environment, and any troubleshooting steps you've taken. Their expertise and knowledge may help you to solve the issue. Reporting the issue can also help improve the product and other people working on the same problems.

Conclusion

Failing tests can be frustrating, but by systematically investigating the error, identifying potential root causes, and implementing the appropriate solutions, you can get your serverless search tests back on track. Remember to focus on performance, data optimization, and environment stability. By following the steps we've discussed, you'll be well-equipped to troubleshoot and resolve these issues, ultimately ensuring the reliability and accuracy of your Kibana visualizations. Good luck, guys!