feat: Shutdown DRT when vLLM engine fails (#2698)

Signed-off-by: J Wyman <jwyman@nvidia.com>

components/backends/vllm/src/dynamo/vllm/engine_monitor.py

+# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+import asyncio
+import logging
+import os
+
+from vllm.v1.engine.async_llm import AsyncLLM
+from vllm.v1.engine.exceptions import EngineDeadError
+
+from dynamo.runtime import DistributedRuntime
+from dynamo.runtime.logging import configure_dynamo_logging
+
+configure_dynamo_logging
+logger = logging.getLogger(__name__)
+
+HEALTH_CHECK_INTERVAL = 2
+
+
+class VllmEngineMonitor:
+    """
+    Monitors the health of the vLLM engine and initiates a shutdown if the engine is dead.
+    """
+
+    def __init__(self, runtime: DistributedRuntime, engine_client: AsyncLLM):
+        if not isinstance(runtime, DistributedRuntime):
+            raise ValueError(
+                f"{self.__class__.__name__} requires an instance of DistributedRuntime."
+            )
+        if not isinstance(engine_client, AsyncLLM):
+            raise ValueError(
+                f"{self.__class__.__name__} requires an instance of AsyncLLM."
+            )
+
+        self.runtime = runtime
+        self.engine_client = engine_client
+        self._monitor_task = asyncio.create_task(self._check_engine_health())
+
+        logger.info(
+            f"{self.__class__.__name__} initialized and health check task started."
+        )
+
+    def __del__(self):
+        self._monitor_task.cancel()
+
+    async def _check_engine_health(self):
+        while True:
+            try:
+                await self.engine_client.check_health()
+                await asyncio.sleep(HEALTH_CHECK_INTERVAL)
+            except EngineDeadError as e:
+                logger.error(f"vLLM AsyncLLM health check failed: {e}")
+                logger.warning("Initiating Dynamo Runtime shutdown.")
+                self.runtime.shutdown()
+                os._exit(1)
+            except asyncio.CancelledError:
+                pass

components/backends/vllm/src/dynamo/vllm/handlers.py

@@ -3,6 +3,7 @@
 
 import asyncio
 import logging
+import os
 import uuid
 from abc import ABC, abstractmethod
 from copy import deepcopy
@@ -11,9 +12,11 @@ from typing import AsyncGenerator
 import msgspec
 from vllm.inputs import TokensPrompt
 from vllm.sampling_params import SamplingParams
+from vllm.v1.engine.exceptions import EngineDeadError
 
 from dynamo.runtime.logging import configure_dynamo_logging
 
+from .engine_monitor import VllmEngineMonitor
 from .protocol import MyRequestOutput
 
 configure_dynamo_logging()
@@ -25,11 +28,13 @@ class BaseWorkerHandler(ABC):
     Request handler for the generate and clear_kv_blocks endpoints.
     """
 
-    def __init__(self, component, engine, default_sampling_params):
+    def __init__(self, runtime, component, engine, default_sampling_params):
+        self.runtime = runtime
         self.component = component
         self.engine_client = engine
         self.default_sampling_params = default_sampling_params
         self.kv_publisher = None
+        self.engine_monitor = VllmEngineMonitor(runtime, engine)
 
     @abstractmethod
     async def generate(self, request, context) -> AsyncGenerator[dict, None]:
@@ -47,6 +52,7 @@ class BaseWorkerHandler(ABC):
         pass
 
     async def generate_tokens(self, prompt, sampling_params, request_id):
+        try:
             gen = self.engine_client.generate(prompt, sampling_params, request_id)
 
             num_output_tokens_so_far = 0
@@ -79,12 +85,23 @@ class BaseWorkerHandler(ABC):
                     "Decode engine was shut down during token generation"
                 ) from None
 
+        except EngineDeadError as e:
+            logger.error(f"vLLM EngineDeadError: {e}")
+            logger.warning("Initiating Dynamo Runtime shutdown.")
+            self.runtime.shutdown()
+            os._exit(1)
+
 
 class DecodeWorkerHandler(BaseWorkerHandler):
     def __init__(
-        self, component, engine, default_sampling_params, prefill_worker_client=None
+        self,
+        runtime,
+        component,
+        engine,
+        default_sampling_params,
+        prefill_worker_client=None,
     ):
-        super().__init__(component, engine, default_sampling_params)
+        super().__init__(runtime, component, engine, default_sampling_params)
         self.prefill_worker_client = prefill_worker_client
         self.can_prefill = 0
         self._prefill_check_task = None
@@ -99,10 +116,13 @@ class DecodeWorkerHandler(BaseWorkerHandler):
                 if self.prefill_worker_client is not None:
                     self.can_prefill = len(self.prefill_worker_client.instance_ids())
                     logger.debug(f"Current Prefill Workers: {self.can_prefill}")
-                await asyncio.sleep(5)
+            except asyncio.CancelledError:
+                logger.warning("Prefill check loop cancelled.")
+                raise
             except Exception as e:
                 logger.error(f"Error in prefill check loop: {e}")
-                await asyncio.sleep(5)  # Still sleep on error to avoid tight loop
+
+            await asyncio.sleep(5)
 
     def cleanup(self):
         """Cancel background tasks."""
@@ -172,6 +192,7 @@ class DecodeWorkerHandler(BaseWorkerHandler):
                 "kv_transfer_params"
             ] = prefill_response.kv_transfer_params
 
+        try:
             async for tok in self.generate_tokens(prompt, sampling_params, request_id):
                 if context.is_stopped() or context.is_killed():
                     await self.engine_client.abort(request_id)
@@ -181,10 +202,16 @@ class DecodeWorkerHandler(BaseWorkerHandler):
 
                 yield tok
 
+        except EngineDeadError as e:
+            logger.error(f"vLLM EngineDeadError: {e}")
+            logger.warning("Initiating Dynamo Runtime shutdown.")
+            self.runtime.shutdown()
+            os._exit(1)
+
 
 class PrefillWorkerHandler(BaseWorkerHandler):
-    def __init__(self, component, engine, default_sampling_params):
-        super().__init__(component, engine, default_sampling_params)
+    def __init__(self, runtime, component, engine, default_sampling_params):
+        super().__init__(runtime, component, engine, default_sampling_params)
 
     async def generate(self, request, context):
         request_id = request["request_id"]
@@ -193,7 +220,13 @@ class PrefillWorkerHandler(BaseWorkerHandler):
         prompt = TokensPrompt(prompt_token_ids=request["token_ids"])
         sampling_params = msgspec.convert(request["sampling_params"], SamplingParams)
 
+        try:
             gen = self.engine_client.generate(prompt, sampling_params, request_id)
+        except EngineDeadError as e:
+            logger.error(f"vLLM EngineDeadError: {e}")
+            logger.warning("Initiating Dynamo Runtime shutdown.")
+            self.runtime.shutdown()
+            os._exit(1)
 
         # Generate only 1 token in prefill
         try:

components/backends/vllm/src/dynamo/vllm/main.py

@@ -142,7 +142,9 @@ async def init_prefill(runtime: DistributedRuntime, config: Config):
 
     # TODO register_prefill in similar vein to register_llm
 
-    handler = PrefillWorkerHandler(component, engine_client, default_sampling_params)
+    handler = PrefillWorkerHandler(
+        runtime, component, engine_client, default_sampling_params
+    )
 
     try:
         await asyncio.gather(
@@ -201,7 +203,11 @@ async def init(runtime: DistributedRuntime, config: Config):
     logger.info(f"VllmWorker for {config.model} has been initialized")
 
     handler = DecodeWorkerHandler(
-        component, engine_client, default_sampling_params, prefill_worker_client
+        runtime,
+        component,
+        engine_client,
+        default_sampling_params,
+        prefill_worker_client,
     )
 
     if config.engine_args.enable_prefix_caching:

tests/fault_tolerance/.gitignore

+*.txt
+*.log.txt

tests/fault_tolerance/test_vllm_health_check.py

+# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+import logging
+import os
+import shutil
+import time
+
+import pytest
+import requests
+from huggingface_hub import snapshot_download
+
+from tests.utils.deployment_graph import completions_response_handler
+from tests.utils.managed_process import ManagedProcess
+
+logger = logging.getLogger(__name__)
+
+
+class DynamoFrontendProcess(ManagedProcess):
+    """Process manager for Dynamo frontend"""
+
+    def __init__(self, request):
+        command = ["python", "-m", "dynamo.frontend", "--router-mode", "round-robin"]
+
+        log_dir = f"{request.node.name}_frontend"
+
+        # Clean up any existing log directory from previous runs
+        try:
+            shutil.rmtree(log_dir)
+            logger.info(f"Cleaned up existing log directory: {log_dir}")
+        except FileNotFoundError:
+            # Directory doesn't exist, which is fine
+            pass
+
+        super().__init__(
+            command=command,
+            display_output=True,
+            terminate_existing=True,
+            log_dir=log_dir,
+        )
+
+    def get_pid(self) -> int | None:
+        """Get the PID of the worker process"""
+        return self.proc.pid if self.proc else None
+
+
+class DynamoWorkerProcess(ManagedProcess):
+    """Process manager for Dynamo worker with vLLM backend"""
+
+    def __init__(self, request, worker_id: str):
+        self.worker_id = worker_id
+
+        command = [
+            "python3",
+            "-m",
+            "dynamo.vllm",
+            "--model",
+            "deepseek-ai/DeepSeek-R1-Distill-Llama-8B",
+            "--enforce-eager",
+            "--gpu-memory-utilization",
+            "0.45",
+            "--max-model-len",
+            "8192",
+            "--migration-limit",
+            "3",
+        ]
+
+        # Set debug logging environment
+        env = os.environ.copy()
+        env["DYN_LOG"] = "debug"
+        env["DYN_SYSTEM_ENABLED"] = "true"
+        env["DYN_SYSTEM_USE_ENDPOINT_HEALTH_STATUS"] = '["generate"]'
+        env["DYN_SYSTEM_PORT"] = "9345"
+
+        # TODO: Have the managed process take a command name explicitly to distinguish
+        #       between processes started with the same command.
+        log_dir = f"{request.node.name}_{worker_id}"
+
+        # Clean up any existing log directory from previous runs
+        try:
+            shutil.rmtree(log_dir)
+            logger.info(f"Cleaned up existing log directory: {log_dir}")
+        except FileNotFoundError:
+            # Directory doesn't exist, which is fine
+            pass
+
+        super().__init__(
+            command=command,
+            env=env,
+            health_check_urls=[("http://localhost:9345/health", self.is_ready)],
+            timeout=300,
+            display_output=True,
+            terminate_existing=False,
+            log_dir=log_dir,
+        )
+
+    def get_pid(self) -> int | None:
+        """Get the PID of the worker process"""
+        return self.proc.pid if hasattr(self, "proc") and self.proc else None
+
+    def is_ready(self, response) -> bool:
+        """Check the health of the worker process"""
+        try:
+            data = response.json()
+            if data.get("status") == "ready":
+                logger.info(
+                    f"{self.__class__.__name__} {{ name: {self.worker_id} }} status is ready"
+                )
+                return True
+            logger.warning(
+                f"{self.__class__.__name__} {{ name: {self.worker_id} }} status is not ready: {data.get('status')}"
+            )
+        except ValueError:
+            logger.warning(
+                f"{self.__class__.__name__} {{ name: {self.worker_id} }} health response is not valid JSON"
+            )
+        return False
+
+
+def download_model() -> None:
+    """
+    Download the DeepSeek-R1-Distill-Llama-8B model from HuggingFace Hub if not already cached.
+    """
+    model_id = "deepseek-ai/DeepSeek-R1-Distill-Llama-8B"
+    logger.info(f"Caching model {model_id}...")
+
+    max_retries = 5
+    retry_delay = 30  # seconds
+
+    for attempt in range(max_retries):
+        try:
+            # Download the model to the default cache directory
+            # This will skip download if the model is already cached
+            snapshot_download(
+                repo_id="deepseek-ai/DeepSeek-R1-Distill-Llama-8B",
+                repo_type="model",
+                local_files_only=False,
+            )
+            logger.info(f"Model {model_id} is ready for use")
+            return  # Success, exit the function
+        except Exception as e:
+            if attempt < max_retries - 1:  # Not the last attempt
+                logger.warning(
+                    f"Failed to download model {model_id} (attempt {attempt + 1}/{max_retries}): {e}"
+                )
+                logger.info(f"Retrying in {retry_delay} seconds...")
+                time.sleep(retry_delay)
+            else:  # Last attempt failed
+                logger.error(
+                    f"Failed to download model {model_id} after {max_retries} attempts: {e}"
+                )
+                raise
+
+
+def send_completion_request(
+    prompt: str, max_tokens: int, timeout: int = 120
+) -> requests.Response:
+    """Send a completion request to the frontend"""
+    payload = {
+        "model": "deepseek-ai/DeepSeek-R1-Distill-Llama-8B",
+        "prompt": prompt,
+        "max_tokens": max_tokens,
+    }
+
+    headers = {"Content-Type": "application/json"}
+
+    logger.info(
+        f"Sending completion request with prompt: '{prompt[:50]}...' and max_tokens: {max_tokens}"
+    )
+
+    try:
+        response = requests.post(
+            "http://localhost:8080/v1/completions",
+            headers=headers,
+            json=payload,
+            timeout=timeout,
+        )
+        logger.info(f"Received response with status code: {response.status_code}")
+        return response
+    except requests.exceptions.Timeout:
+        logger.error(f"Request timed out after {timeout} seconds")
+        raise
+    except requests.exceptions.RequestException as e:
+        logger.error(f"Request failed with error: {e}")
+        raise
+
+
+@pytest.mark.vllm
+@pytest.mark.gpu_1
+@pytest.mark.e2e
+@pytest.mark.slow
+def test_vllm_health_check_active(request, runtime_services):
+    """
+    End-to-end test for worker fault tolerance with migration support.
+
+    This test verifies that when a worker is killed during request processing,
+    the system can handle the failure gracefully and migrate the request to
+    another worker.
+    """
+    # Step 0: Download the model from HuggingFace if not already cached
+    download_model()
+
+    # Step 1: Start the frontend
+    logger.info("Starting frontend...")
+    with DynamoFrontendProcess(request):
+        logger.info("Frontend started.")
+
+        # Step 2: Start a worker
+        logger.info("Starting worker...")
+        with DynamoWorkerProcess(request, "decode") as worker:
+            logger.info(f"Worker PID: {worker.get_pid()}")
+
+            time.sleep(12)  # Give the model some time to get started.
+
+            # Step 3: Send a test request to prove the worker is live.
+            test_response = send_completion_request("Who are you?", 100, timeout=60)
+            completions_response_handler(test_response)
+            logger.info("Test request completed successfully")
+
+            # Step 4: Find and kill vLLM engine processes to force the EngineDeadError condition.
+            children = worker.subprocesses()
+            logger.info(f"Worker children: {[child.pid for child in children]}")
+            for child in children:
+                cmdline = child.cmdline()
+                if len(cmdline) > 0 and cmdline[0] == "VLLM::EngineCore":
+                    logger.warning(
+                        f"Killing vLLM engine process {{ pid: {child.pid}, cmdline: '{' '.join(cmdline)}' }}"
+                    )
+                    child.kill()
+                    break
+
+            time.sleep(2)  # Give some time for the worker to stabilize
+
+            # Step 5: Send a request triggering the handler to shutdown everything.
+            test_response = send_completion_request("How old are you?", 100, timeout=60)
+            logger.error(f"Test request failed: {test_response}")
+
+            # Step 6: Ensure the worker process has been stopped as a result of the EngineDeadError condition.
+            if worker.is_running():
+                pytest.fail(
+                    "Worker should not be running after killing vLLM engine process."
+                )
+
+
+@pytest.mark.vllm
+@pytest.mark.gpu_1
+@pytest.mark.e2e
+@pytest.mark.slow
+def test_vllm_health_check_passive(request, runtime_services):
+    """
+    End-to-end test for worker fault tolerance with migration support.
+
+    This test verifies that when a worker is killed during request processing,
+    the system can handle the failure gracefully and migrate the request to
+    another worker.
+    """
+    # Step 0: Download the model from HuggingFace if not already cached
+    download_model()
+
+    # Step 1: Start the frontend
+    logger.info("Starting frontend...")
+    with DynamoFrontendProcess(request):
+        logger.info("Frontend started.")
+
+        # Step 2: Start a worker
+        logger.info("Starting worker...")
+        with DynamoWorkerProcess(request, "decode") as worker:
+            logger.info(f"Worker PID: {worker.get_pid()}")
+
+            time.sleep(12)  # Give the model some time to get started.
+
+            # Step 3: Send a test request to prove the worker is live.
+            test_response = send_completion_request("Who are you?", 100, timeout=60)
+            completions_response_handler(test_response)
+            logger.info("Test request completed successfully")
+
+            # Step 4: Find and kill vLLM engine processes to force the EngineDeadError condition.
+            children = worker.subprocesses()
+            logger.info(f"Worker children: {[child.pid for child in children]}")
+            for child in children:
+                cmdline = child.cmdline()
+                if len(cmdline) > 0 and cmdline[0] == "VLLM::EngineCore":
+                    logger.warning(
+                        f"Killing vLLM engine process {{ pid: {child.pid}, cmdline: '{' '.join(cmdline)}' }}"
+                    )
+                    child.kill()
+                    break
+
+            time.sleep(6)  # Give some time for the worker to stabilize
+
+            # Step 5: Ensure the worker process has been stopped as a result of the EngineDeadError condition.
+            if worker.is_running():
+                pytest.fail(
+                    "Worker should not be running after killing vLLM engine process."
+                )

tests/utils/managed_process.py

@@ -433,6 +433,27 @@ class ManagedProcess:
                     # Process may have terminated or become inaccessible during iteration
                     pass
 
+    def is_running(self) -> bool:
+        """Check if the process is still running"""
+        return (
+            hasattr(self, "proc") and self.proc is not None and self.proc.poll() is None
+        )
+
+    def subprocesses(self) -> list[psutil.Process]:
+        """Find child processes of the current process."""
+        if (
+            not hasattr(self, "proc")
+            or self.proc is None
+            or self.proc.poll() is not None
+        ):
+            return []
+
+        try:
+            parent = psutil.Process(self.proc.pid)
+            return parent.children(recursive=True)
+        except psutil.NoSuchProcess:
+            return []
+
 
 def main():
     with ManagedProcess(