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[Cherry-Pick][APIServer][Feature] Add configurable worker health check timeout via FD_WORKER_ALIVE_TIMEOUT(#5865) (#5867)

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* Initial plan

* Cherry-pick PR #5865: Add configurable worker health check timeout via FD_WORKER_ALIVE_TIMEOUT

Co-authored-by: Jiang-Jia-Jun <163579578+Jiang-Jia-Jun@users.noreply.github.com>

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: Jiang-Jia-Jun <163579578+Jiang-Jia-Jun@users.noreply.github.com>
This commit is contained in:
Copilot
2026-01-05 09:45:19 +08:00
committed by GitHub
parent 2a71e427f9
commit 9de6ae375c
5 changed files with 16 additions and 5 deletions
Download Patch File Download Diff File Expand all files Collapse all files
docs/usage/environment_variables.md
+3
View File
@@ -88,5 +88,8 @@ environment_variables: dict[str, Callable[[], Any]] = {
# Count for cache_transfer_manager process error
"FD_CACHE_PROC_ERROR_COUNT": lambda: int(os.getenv("FD_CACHE_PROC_ERROR_COUNT", "10")),
# Worker process health check timeout when waiting for responses in seconds (default: 30)
"FD_WORKER_ALIVE_TIMEOUT": lambda: int(os.getenv("FD_WORKER_ALIVE_TIMEOUT", "30")),
}
```
docs/zh/usage/environment_variables.md
+5 -1
View File
@@ -87,5 +87,9 @@ environment_variables: dict[str, Callable[[], Any]] = {
"FD_CACHE_PROC_EXIT_TIMEOUT": lambda: int(os.getenv("FD_CACHE_PROC_EXIT_TIMEOUT", "600")),
# cache_transfer_manager 进程残留时连续错误阈值
"FD_CACHE_PROC_ERROR_COUNT": lambda: int(os.getenv("FD_CACHE_PROC_ERROR_COUNT", "10")),}
"FD_CACHE_PROC_ERROR_COUNT": lambda: int(os.getenv("FD_CACHE_PROC_ERROR_COUNT", "10")),
# Worker 进程响应等待时的健康检查超时时间（秒），默认 30 秒
"FD_WORKER_ALIVE_TIMEOUT": lambda: int(os.getenv("FD_WORKER_ALIVE_TIMEOUT", "30")),
}
```
fastdeploy/entrypoints/openai/serving_chat.py
+3 -2
View File
@@ -24,6 +24,7 @@ from typing import List, Optional
import numpy as np
import fastdeploy.envs as envs
from fastdeploy.entrypoints.openai.protocol import (
ChatCompletionRequest,
ChatCompletionResponse,
@@ -264,7 +265,7 @@ class OpenAIServingChat:
except asyncio.TimeoutError:
current_waiting_time += 10
if current_waiting_time == 300:
status, msg = self.engine_client.check_health()
status, msg = self.engine_client.check_health(time_interval_threashold=envs.FD_WORKER_ALIVE_TIMEOUT)
if not status:
if choices:
chunk.choices = choices
@@ -557,7 +558,7 @@ class OpenAIServingChat:
except asyncio.TimeoutError:
current_waiting_time += 10
if current_waiting_time == 300:
status, msg = self.engine_client.check_health()
status, msg = self.engine_client.check_health(time_interval_threashold=envs.FD_WORKER_ALIVE_TIMEOUT)
if not status:
raise ValueError(f"Engine is not healthy: {msg}")
else:
fastdeploy/entrypoints/openai/serving_completion.py
+3 -2
View File
@@ -25,6 +25,7 @@ from typing import List, Optional
import numpy as np
import fastdeploy.envs as envs
from fastdeploy.engine.request import RequestOutput
from fastdeploy.entrypoints.openai.protocol import (
CompletionLogprobs,
@@ -280,7 +281,7 @@ class OpenAIServingCompletion:
except asyncio.TimeoutError:
current_waiting_time += 10
if current_waiting_time == 300:
status, msg = self.engine_client.check_health()
status, msg = self.engine_client.check_health(time_interval_threashold=envs.FD_WORKER_ALIVE_TIMEOUT)
if not status:
raise ValueError(f"Engine is not healthy: {msg}")
else:
@@ -436,7 +437,7 @@ class OpenAIServingCompletion:
except asyncio.TimeoutError:
current_waiting_time += 10
if current_waiting_time == 300:
status, msg = self.engine_client.check_health()
status, msg = self.engine_client.check_health(time_interval_threashold=envs.FD_WORKER_ALIVE_TIMEOUT)
if not status:
raise ValueError(f"Engine is not healthy: {msg}")
else:
fastdeploy/envs.py
+2
View File
@@ -151,6 +151,8 @@ environment_variables: dict[str, Callable[[], Any]] = {
# "Number of tokens in the group for Mixture of Experts (MoE) computation processing on HPU"
"FD_HPU_CHUNK_SIZE": lambda: int(os.getenv("FD_HPU_CHUNK_SIZE", "64")),
"FD_PREFILL_WAIT_DECODE_RESOURCE_SECONDS": lambda: int(os.getenv("FD_PREFILL_WAIT_DECODE_RESOURCE_SECONDS", "30")),
# Timeout for worker process health check in seconds
"FD_WORKER_ALIVE_TIMEOUT": lambda: int(os.getenv("FD_WORKER_ALIVE_TIMEOUT", "30")),
}