1d2caaf554
Reporting cost == max_perf puts an occupied worker at exactly 100% utilization, which the autoscaler reads as "at target, no action." The 3rd session_create then 429s on both active workers and stalls in the global queue instead of triggering a cold-worker activation (observed: 1→2 active scales fine, 2→3 does not). Bumping cost to 2 * max_perf makes each session look like more than one worker's work, so the autoscaler always keeps an extra active worker hot. Slight over-provisioning, but the 3rd reservation lands directly on a free worker rather than queueing. Expose --session-cost on the client so the value can be swept without edits. README documents the trade-off. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
209 lines
6.7 KiB
Python
209 lines
6.7 KiB
Python
import argparse
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import asyncio
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import logging
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import os
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import sys
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import time
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from vastai import Serverless
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logging.basicConfig(
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level=logging.INFO,
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format="%(asctime)s[%(levelname)-5s] %(message)s",
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datefmt="%Y-%m-%d %H:%M:%S",
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)
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log = logging.getLogger(__file__)
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ENDPOINT_NAME = "null-prod"
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# Default cost passed to /session/create. Bumping this above the worker's
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# max_perf (100) is how you tell the autoscaler "each session is more than
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# one worker of work" — keeps an extra active worker warm and ready, so
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# the next /session/create lands on a free worker instead of queueing.
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# See README "Endpoint scaling parameters" for the math.
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DEFAULT_SESSION_COST = 200
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async def reserve(
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client: Serverless,
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*,
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endpoint_name: str,
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hold_for: float,
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session_cost: int,
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label: str = "session",
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) -> None:
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"""Open a session, hold the worker for `hold_for` seconds, close cleanly.
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Uses the framework's session model — each session counts as one worker
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occupied, but unlike a held HTTP request it isn't poisoning the
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worker's throughput math. max_sessions=1 on the worker side means a
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second /session/create against the same worker gets 429, so serverless
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routes the second reservation to a free worker or scales a new one up.
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"""
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endpoint = await client.get_endpoint(name=endpoint_name)
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# Session lifetime must outlast the hold. The framework expires sessions
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# whose `expiration` (set to now + lifetime at creation) has passed; we
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# don't make any keepalive requests so no extension happens.
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lifetime = hold_for + 60
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start = time.monotonic()
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log.info(
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"[%s] creating session (cost=%d, lifetime=%.0fs, hold=%.0fs)",
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label, session_cost, lifetime, hold_for,
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)
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async with await endpoint.session(cost=session_cost, lifetime=lifetime) as s:
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log.info("[%s] session %s open", label, s.session_id)
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try:
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await asyncio.sleep(hold_for)
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log.info("[%s] hold complete, closing session", label)
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except asyncio.CancelledError:
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elapsed = time.monotonic() - start
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log.info("[%s] cancelled after %.1fs, closing session", label, elapsed)
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raise
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elapsed = time.monotonic() - start
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log.info("[%s] session closed cleanly after %.1fs", label, elapsed)
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async def run_demo(
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client: Serverless,
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*,
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endpoint_name: str,
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interval: float,
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plateau: float,
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session_cost: int,
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) -> None:
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"""Trapezoidal load: ramp up three sessions, plateau, then scale down.
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Start three sessions spaced `interval` seconds apart. Each holds for
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`(n-1)*interval + plateau` seconds, so the first release fires
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`plateau` seconds after the last session started — giving the
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autoscaler time to actually have all three workers running before any
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scale-down begins. Releases then fire `interval` seconds apart,
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matching the ramp-up.
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Each session ends via the SDK's `session.close()` on `async with` exit,
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which posts to /session/end with proper auth — counted as a normal
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success in metrics.
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"""
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n = 3
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hold = (n - 1) * interval + plateau
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tasks: list[asyncio.Task] = []
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for i in range(1, n + 1):
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label = f"res-{i}"
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log.info("[%s] starting (hold=%.0fs)", label, hold)
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task = asyncio.create_task(
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reserve(
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client,
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endpoint_name=endpoint_name,
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hold_for=hold,
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session_cost=session_cost,
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label=label,
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),
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name=label,
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)
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tasks.append(task)
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if i < n:
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log.info("Waiting %.0fs before next session...", interval)
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await asyncio.sleep(interval)
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log.info(
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"All %d sessions in flight; holding plateau for %.0fs, "
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"then scaling down %.0fs apart",
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n,
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plateau,
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interval,
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)
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results = await asyncio.gather(*tasks, return_exceptions=True)
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for task, result in zip(tasks, results):
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log.info("[%s] final: %r", task.get_name(), result)
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def build_arg_parser() -> argparse.ArgumentParser:
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p = argparse.ArgumentParser(description="Vast Null PyWorker demo client")
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p.add_argument(
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"--endpoint",
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default=os.environ.get("VAST_ENDPOINT", ENDPOINT_NAME),
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help=f"Vast endpoint name (default: {ENDPOINT_NAME})",
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)
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p.add_argument(
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"--duration",
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type=float,
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default=180.0,
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help="Single-reserve mode: seconds to hold the worker (default: 180)",
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)
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modes = p.add_mutually_exclusive_group(required=False)
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modes.add_argument(
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"--reserve",
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action="store_true",
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help="Make a single session (default if no mode given)",
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)
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modes.add_argument(
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"--demo",
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action="store_true",
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help="Run the staggered 3-reservation trapezoid demo",
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)
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p.add_argument(
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"--interval",
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type=float,
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default=30.0,
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help="Demo mode: seconds between reservation steps (default: 30)",
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)
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p.add_argument(
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"--plateau",
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type=float,
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default=300.0,
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help=(
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"Demo mode: seconds to hold all 3 reservations active before "
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"scale-down starts. Gives the autoscaler time to fully spin "
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"up the third worker (default: 300)"
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),
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)
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p.add_argument(
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"--session-cost",
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type=int,
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default=DEFAULT_SESSION_COST,
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help=(
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f"Cost reported to the autoscaler for each /session/create. "
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f"Setting this above the worker's max_perf (100) over-provisions "
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f"slightly, keeping an extra active worker warm so the next "
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f"session lands without queueing (default: {DEFAULT_SESSION_COST})"
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),
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)
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return p
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async def main_async():
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args = build_arg_parser().parse_args()
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print("=" * 60)
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print(f"Endpoint: {args.endpoint}")
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print("=" * 60)
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try:
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async with Serverless() as client:
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if args.demo:
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await run_demo(
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client,
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endpoint_name=args.endpoint,
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interval=args.interval,
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plateau=args.plateau,
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session_cost=args.session_cost,
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)
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else:
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await reserve(
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client,
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endpoint_name=args.endpoint,
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hold_for=args.duration,
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session_cost=args.session_cost,
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label="reservation",
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)
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except KeyboardInterrupt:
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log.info("Interrupted; dropping any in-flight sessions")
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except Exception as e:
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log.error("Error: %s", e, exc_info=True)
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sys.exit(1)
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if __name__ == "__main__":
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asyncio.run(main_async())
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