private GeneratedMonitorTest(
      Method method,
      Scenario scenario,
      boolean fair,
      @Nullable Timeout timeout,
      Outcome expectedOutcome) {
    super(nameFor(method, scenario, fair, timeout, expectedOutcome));
    this.method = method;
    this.scenario = scenario;
    this.timeout = timeout;
    this.expectedOutcome = expectedOutcome;

        Handler handler = new Handler();
        Handler.GcsURLConnection conn = (Handler.GcsURLConnection) handler.openConnection(url);

        // Ensure environment variables are not set (in real scenario)
        // In this test, we expect IOException when project ID is blank
        try {
            conn.connect();
            fail("Should throw IOException when project ID is not set");

        Handler handler = new Handler();
        Handler.StorageURLConnection conn = (Handler.StorageURLConnection) handler.openConnection(url);

        // Ensure environment variables are not set (in real scenario)
        // In this test, we expect IOException when endpoint is blank
        try {
            conn.connect();
            fail("Should throw IOException when endpoint is not set");
        } catch (IOException e) {

    // causing the thread to be suspended for 3.5 seconds, and then park itself for 2 seconds after
    // being resumed. To avoid a flake in this scenario, calculate how long that thread actually
    // waited and assert based on that time. Empirically, the race where the thread ends up waiting
    // for 5.5 seconds happens about 2% of the time.

    // causing the thread to be suspended for 3.5 seconds, and then park itself for 2 seconds after
    // being resumed. To avoid a flake in this scenario, calculate how long that thread actually
    // waited and assert based on that time. Empirically, the race where the thread ends up waiting
    // for 5.5 seconds happens about 2% of the time.

- DRA: scheduling pods is up to 16x faster, depending on the scenario. Scheduling throughput depends a lot on cluster utilization. It is higher for lightly loaded clusters with free resources and gets lower when the cluster utilization increases. ([#127277](https://github.com/kubernetes/kubernetes/pull/127277), [@...

- The test is intended to verify pod scheduling with an anti-affinity scenario, but it uses the wrong pod template. 
  This affects functional correctness. ([#134262](https://github.com/kubernetes/kubernetes/pull/134262), [@sats-23](https://github.com/sats-23)) [SIG Testing]

## Dependencies

 *
 * <p>The job supports selective crawling by specifying configuration IDs for different
 * types of crawlers (web, file, data). It manages the crawler process lifecycle,
 * handles timeout scenarios, and ensures proper cleanup of resources.</p>
 *
 * <p>Key features:</p>
 * <ul>
 *   <li>Concurrent crawler process management with configurable limits</li>
 *   <li>Selective crawling based on configuration IDs</li>

- DRA kubelet: Fixed the kubelet to also clean up `ResourceSlices` in some additional failure scenarios (driver was removed forcibly or crashed and did not restart). ([#132058](https://github.com/kubernetes/kubernetes/pull/132058), [@pohly](https://github.com/pohly)) [SIG Node and Testing]