wehub-resource-sync
58 lines
1.9 KiB
Python
58 lines
1.9 KiB
Python
# __begin_class_based_autoscaling_policy__
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import asyncio
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import json
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import logging
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from pathlib import Path
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from typing import Any, Dict, Tuple
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from ray.serve.config import AutoscalingContext
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logger = logging.getLogger("ray.serve")
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class FileBasedAutoscalingPolicy:
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"""Scale replicas based on a target written to a JSON file.
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A background asyncio task re-reads the file every ``poll_interval_s``
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seconds. ``__call__`` returns the latest value on every autoscaling
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tick. In production you could replace the file read with an HTTP
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call, a message-queue consumer, or any other async IO operation.
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"""
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def __init__(self, file_path: str, poll_interval_s: float = 5.0):
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self._file_path = Path(file_path)
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self._poll_interval_s = poll_interval_s
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self._desired_replicas: int = 1
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self._task: asyncio.Task = None
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self._started: bool = False
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def _ensure_started(self) -> None:
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"""Lazily start the background poll on the controller event loop."""
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if self._started:
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return
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self._started = True
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loop = asyncio.get_running_loop()
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self._task = loop.create_task(self._poll_file())
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async def _poll_file(self) -> None:
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"""Read the target replica count from the JSON file in a loop."""
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while True:
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try:
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text = self._file_path.read_text()
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data = json.loads(text)
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self._desired_replicas = int(data["replicas"])
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except Exception:
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pass # Keep the last known value on failure.
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await asyncio.sleep(self._poll_interval_s)
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def __call__(
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self, ctx: AutoscalingContext
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) -> Tuple[int, Dict[str, Any]]:
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self._ensure_started()
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desired = self._desired_replicas
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return desired, {"last_polled_value": self._desired_replicas}
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# __end_class_based_autoscaling_policy__
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