[CI][Metrics] Stabilize tests with polling and subprocess guards (#34566)

test_abort_metrics_reset is flaky due to hardware-dependent
fixed sleeps: replace fixed sleeps with polling.

test_metrics_exist_run_batch passes even when the engine crashes
on startup (false positive): add subprocess lifecycle guards.
Signed-off-by: Andreas Karatzas <akaratza@amd.com>

tests/entrypoints/instrumentator/test_metrics.py

@@ -17,6 +17,7 @@ from transformers import AutoTokenizer
 from tests.conftest import LocalAssetServer
 from tests.utils import RemoteOpenAIServer
 from vllm import version
+from vllm.utils.network_utils import get_open_port
 
 MODELS = {
     "text": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
@@ -315,14 +316,26 @@ async def test_abort_metrics_reset(
             client.completions.create(
                 model=model_name,
                 prompt=prompt_ids,
-                max_tokens=100,  # Long generation to give time to abort
+                max_tokens=500,  # Long generation to give time to abort
                 temperature=0.0,
             )
         )
         tasks.append(task)
 
-    # Wait a bit for requests to start processing
-    await asyncio.sleep(0.5)
+    # Poll until we see running requests rather than using a fixed sleep,
+    # since generation speed varies across hardware.
+    try:
+        await _poll_until(
+            lambda: _get_running_metrics_from_api(server)[0] > 0,
+            timeout=10.0,
+            interval=0.1,
+            description="running_requests > 0",
+        )
+    except TimeoutError:
+        for task in tasks:
+            task.cancel()
+        await asyncio.gather(*tasks, return_exceptions=True)
+        pytest.fail("Requests never appeared as running in metrics")
 
     # Check that we have running requests
     running_requests, waiting_requests, kv_cache_usage = _get_running_metrics_from_api(
@@ -336,13 +349,15 @@ async def test_abort_metrics_reset(
     # Cancel all tasks to abort the requests
     for task in tasks:
         task.cancel()
-
-    # Wait for cancellations to be processed
-    await asyncio.sleep(1.0)
-
-    # Check that metrics have reset to zero
-    response = requests.get(server.url_for("metrics"))
-    assert response.status_code == HTTPStatus.OK
+    await asyncio.gather(*tasks, return_exceptions=True)
+
+    # Poll until metrics reset rather than using a fixed sleep
+    await _poll_until(
+        lambda: _get_running_metrics_from_api(server) == (0, 0, 0),
+        timeout=10.0,
+        interval=0.2,
+        description="gauge metrics back to zero",
+    )
 
     # Verify running and waiting requests counts and KV cache usage are zero
     running_requests_after, waiting_requests_after, kv_cache_usage_after = (
@@ -360,6 +375,18 @@ async def test_abort_metrics_reset(
     )
 
 
+async def _poll_until(
+    predicate, *, timeout: float, interval: float = 0.5, description: str = "condition"
+):
+    """Poll until predicate() returns True, or raise TimeoutError."""
+    start = time.time()
+    while time.time() - start < timeout:
+        if predicate():
+            return
+        await asyncio.sleep(interval)
+    raise TimeoutError(f"Timed out after {timeout}s waiting for: {description}")
+
+
 def _get_running_metrics_from_api(server: RemoteOpenAIServer):
     """Return (running_count, waiting_count, kv_cache_usage)"""
 
@@ -399,7 +426,7 @@ def test_metrics_exist_run_batch():
     input_batch = """{"custom_id": "request-0", "method": "POST", "url": "/v1/embeddings", "body": {"model": "intfloat/multilingual-e5-small", "input": "You are a helpful assistant."}}"""  # noqa: E501
 
     base_url = "0.0.0.0"
-    port = "8001"
+    port = str(get_open_port())
     server_url = f"http://{base_url}:{port}"
 
     with (
@@ -427,6 +454,8 @@ def test_metrics_exist_run_batch():
             ],
         )
 
+        try:
+
             def is_server_up(url):
                 try:
                     response = requests.get(url)
@@ -434,10 +463,23 @@ def test_metrics_exist_run_batch():
                 except requests.ConnectionError:
                     return False
 
+            start = time.time()
+            timeout = 120
             while not is_server_up(server_url):
+                if proc.poll() is not None:
+                    pytest.fail(
+                        f"Batch process exited early with returncode={proc.returncode}"
+                    )
+                if time.time() - start > timeout:
+                    pytest.fail("Batch server did not start within timeout")
                 time.sleep(1)
 
             response = requests.get(server_url + "/metrics")
             assert response.status_code == HTTPStatus.OK
-
-        proc.wait()
+        finally:
+            proc.terminate()
+            try:
+                proc.wait(timeout=15)
+            except subprocess.TimeoutExpired:
+                proc.kill()
+                proc.wait(timeout=5)