Suppress matplot debug logs

lib/backend.py

@@ -5,14 +5,13 @@ import base64
 import subprocess
 import dataclasses
 import logging
-from asyncio import wait, sleep, gather, Semaphore, FIRST_COMPLETED, create_task, get_running_loop
+from asyncio import wait, sleep, gather, Semaphore, FIRST_COMPLETED, create_task
 from typing import Tuple, Awaitable, NoReturn, List, Union, Callable, Optional
 from functools import cached_property
 from distutils.util import strtobool
 
 from anyio import open_file
 from aiohttp import web, ClientResponse, ClientSession, ClientConnectorError, ClientTimeout, TCPConnector
-import asyncio
 
 import requests
 from Crypto.Signature import pkcs1_15
@@ -26,12 +25,8 @@ from lib.data_types import (
     LogAction,
     ApiPayload_T,
     JsonDataException,
-    RequestMetrics,
-    BenchmarkResult
 )
 
-VERSION = "0.1.0"
-
 MSG_HISTORY_LEN = 100
 log = logging.getLogger(__file__)
 
@@ -47,7 +42,7 @@ class Backend:
     This class is responsible for:
     1. Tailing logs and updating load time metrics
     2. Taking an EndpointHandler alongside incoming payload, preparing a json to be sent to the model, and
-       sending the request. It also updates metrics as it makes those requests.
+    sending the request. It also updates metrics as it makes those requests.
     3. Running a benchmark from an EndpointHandler
     """
 
@@ -58,9 +53,7 @@ class Backend:
         EndpointHandler  # this endpoint handler will be used for benchmarking
     )
     log_actions: List[Tuple[LogAction, str]]
-    max_wait_time: float = 10.0
     reqnum = -1
-    version = VERSION
     msg_history = []
     sem: Semaphore = dataclasses.field(default_factory=Semaphore)
     unsecured: bool = dataclasses.field(
@@ -69,16 +62,10 @@ class Backend:
 
     def __post_init__(self):
         self.metrics = Metrics()
-        self.metrics._set_version(self.version)
         self._total_pubkey_fetch_errors = 0
         self._pubkey = self._fetch_pubkey()
         self.__start_healthcheck: bool = False
 
-        # NEW: FIFO queue + worker count
-        self.request_queue: "asyncio.Queue[tuple[EndpointHandler[ApiPayload_T], web.Request, asyncio.Future]]" = asyncio.Queue()
-        # If parallel allowed, let multiple workers drain the queue (order preserved by FIFO per worker; overall start order is FIFO).
-        self._num_workers: int = 1 if not self.allow_parallel_requests else int(os.environ.get("WORKERS", "4"))
-
     @property
     def pubkey(self) -> Optional[RSA.RsaKey]:
         if self._pubkey is None:
@@ -96,22 +83,6 @@ class Backend:
         timeout = ClientTimeout(total=None)
         return ClientSession(self.model_server_url, timeout=timeout, connector=connector)
 
-    async def _worker(self):
-        while True:
-            handler, request, fut = await self.request_queue.get()
-            try:
-                # Skip if already cancelled while waiting in the queue
-                if fut.cancelled():
-                    continue
-                res = await self.__process_enqueued_request(handler, request)
-                if not fut.cancelled():
-                    fut.set_result(res)
-            except Exception as e:
-                if not fut.cancelled():
-                    fut.set_exception(e)
-            finally:
-                self.request_queue.task_done()
-
     def create_handler(
         self,
         handler: EndpointHandler[ApiPayload_T],
@@ -148,36 +119,7 @@ class Backend:
         handler: EndpointHandler[ApiPayload_T],
         request: web.Request,
     ) -> Union[web.Response, web.StreamResponse]:
-        """use this function to enqueue requests for FIFO processing"""
-        loop = get_running_loop()
-        fut: asyncio.Future = loop.create_future()
-
-        # If the client disconnects while waiting in the FIFO, cancel the future so the worker skips it
-        cancel_watch = create_task(request.wait_for_disconnection())
-        def _cancel_if_disconnected(_):
-            if not fut.done():
-                fut.cancel()
-        cancel_watch.add_done_callback(_cancel_if_disconnected)
-
-        try:
-            await self.request_queue.put((handler, request, fut))
-            return await fut
-        except asyncio.CancelledError:
-            # Propagate cancellation to ensure aiohttp doesn't expect a response body
-            raise
-        finally:
-            # Best-effort cleanup of the watcher
-            cancel_watch.cancel()
-
-    async def __process_enqueued_request(
-        self,
-        handler: EndpointHandler[ApiPayload_T],
-        request: web.Request,
-    ) -> Union[web.Response, web.StreamResponse]:
-        """
-        This contains the original __handle_request logic and is invoked by workers,
-        ensuring FIFO execution via asyncio.Queue.
-        """
+        """use this function to forward requests to the model endpoint"""
         try:
             data = await request.json()
             auth_data, payload = handler.get_data_from_request(data)
@@ -185,63 +127,56 @@ class Backend:
             return web.json_response(data=e.message, status=422)
         except json.JSONDecodeError:
             return web.json_response(dict(error="invalid JSON"), status=422)
-
         workload = payload.count_workload()
-        request_metrics: RequestMetrics = RequestMetrics(
-            request_idx=auth_data.request_idx, reqnum=auth_data.reqnum, workload=workload, status="Created"
-        )
 
         async def cancel_api_call_if_disconnected() -> web.Response:
             await request.wait_for_disconnection()
-            log.debug(f"request with reqnum: {request_metrics.reqnum} was canceled")
-            self.metrics._request_canceled(request_metrics)
-            raise asyncio.CancelledError
+            log.debug(f"request with reqnum: {auth_data.reqnum} was canceled")
+            self.metrics._request_canceled(workload=workload)
+            return web.Response(status=500)
 
         async def make_request() -> Union[web.Response, web.StreamResponse]:
+            log.debug(f"got request, {auth_data.reqnum}")
+            self.metrics._request_start(workload=workload, reqnum=auth_data.reqnum)
+            if self.allow_parallel_requests is False:
+                log.debug(f"Waiting to aquire Sem for reqnum:{auth_data.reqnum}")
+                await self.sem.acquire()
+                log.debug(
+                    f"Sem acquired for reqnum:{auth_data.reqnum}, starting request..."
+                )
+            else:
+                log.debug(f"Starting request for reqnum:{auth_data.reqnum}")
             try:
                 response = await self.__call_api(handler=handler, payload=payload)
                 status_code = response.status
                 log.debug(
                     " ".join(
                         [
-                            f"request with reqnum:{request_metrics.reqnum}",
+                            f"request with reqnum:{auth_data.reqnum}",
                             f"returned status code: {status_code},",
                         ]
                     )
                 )
                 res = await handler.generate_client_response(request, response)
-                self.metrics._request_success(request_metrics)
+                self.metrics._request_success(workload=workload)
                 return res
             except requests.exceptions.RequestException as e:
                 log.debug(f"[backend] Request error: {e}")
-                self.metrics._request_errored(request_metrics)
+                self.metrics._request_errored(workload=workload)
                 return web.Response(status=500)
+            finally:
+                self.metrics._request_end(
+                    workload=workload,
+                    reqnum=auth_data.reqnum,
+                )
+                self.sem.release()
 
         ###########
 
         if self.__check_signature(auth_data) is False:
-            self.metrics._request_reject(request_metrics)
             return web.Response(status=401)
-        
-        if self.metrics.model_metrics.wait_time > self.max_wait_time:
-            self.metrics._request_reject(request_metrics)
-            return web.Response(status=429)
 
-        acquired = False
         try:
-            self.metrics._request_start(request_metrics)
-
-            # Preserve existing semaphore behavior for serializing requests when requested
-            if self.allow_parallel_requests is False:
-                log.debug(f"Waiting to aquire Sem for reqnum:{request_metrics.reqnum}")
-                await self.sem.acquire()
-                acquired = True
-                log.debug(
-                    f"Sem acquired for reqnum:{request_metrics.reqnum}, starting request..."
-                )
-            else:
-                log.debug(f"Starting request for reqnum:{request_metrics.reqnum}")
-
             done, pending = await wait(
                 [
                     create_task(make_request()),
@@ -249,27 +184,11 @@ class Backend:
                 ],
                 return_when=FIRST_COMPLETED,
             )
-            for t in pending:
-                t.cancel()
-            await asyncio.gather(*pending, return_exceptions=True)
-
-            done_task = done.pop()
-            try:
-                return done_task.result()
-            except Exception as e:
-                log.debug(f"Request task raised exception: {e}")
-                return web.Response(status=500)
-        except asyncio.CancelledError:
-            # Client is gone. Do not write a response; just unwind.
-            return web.Response(status=499) 
+            [task.cancel() for task in pending]
+            return done.pop().result()
         except Exception as e:
             log.debug(f"Exception in main handler loop {e}")
             return web.Response(status=500)
-        finally:
-            # Always release the semaphore if it was acquired
-            if acquired:
-                self.sem.release()
-            self.metrics._request_end(request_metrics)
 
     @cached_property  
     def healthcheck_session(self):
@@ -309,14 +228,8 @@ class Backend:
                 self.backend_errored(str(e))
 
     async def _start_tracking(self) -> None:
-        # Start the FIFO workers alongside existing loops
-        worker_tasks = tuple(self._worker() for _ in range(self._num_workers))
         await gather(
-            self.__read_logs(),
-            self.metrics._send_metrics_loop(),
-            self.__healthcheck(),
-            self.metrics._send_delete_requests_loop(),
-            *worker_tasks,
+            self.__read_logs(), self.metrics._send_metrics_loop(), self.__healthcheck()
         )
 
     def backend_errored(self, msg: str) -> None:
@@ -395,26 +308,18 @@ class Backend:
 
             for run in range(1, self.benchmark_handler.benchmark_runs + 1):
                 start = time.time()
-                benchmark_requests = []
+                tasks = []
+                total_workload = 0
 
-                for i in range(concurrent_requests):
+                for _ in range(concurrent_requests):
                     payload = self.benchmark_handler.make_benchmark_payload()
-                    workload = payload.count_workload()
-                    task = self.__call_api(handler=self.benchmark_handler, payload=payload)
-                    benchmark_requests.append(
-                        BenchmarkResult(request_idx=i, workload=workload, task=task)
+                    total_workload += payload.count_workload()
+                    tasks.append(
+                        self.__call_api(handler=self.benchmark_handler, payload=payload)
                     )
 
-                responses = await gather(*[br.task for br in benchmark_requests])
-                for br, response in zip(benchmark_requests, responses):
-                    br.response = response
-
-                total_workload = sum(br.workload for br in benchmark_requests if br.is_successful)
+                responses = await gather(*tasks)
                 time_elapsed = time.time() - start
-                successful_responses = sum([1 for br in benchmark_requests if br.is_successful])
-                if successful_responses == 0:
-                    self.backend_errored("No successful responses from benchmark")
-                    log.debug(f"benchmark failed: {successful_responses}/{concurrent_requests} successful responses")
 
                 throughput = total_workload / time_elapsed
                 sum_throughput += throughput
@@ -428,7 +333,7 @@ class Backend:
                             f"Run: {run}, concurrent_requests: {concurrent_requests}",
                             f"Total workload: {total_workload}, time_elapsed: {time_elapsed}s",
                             f"Throughput: {throughput} workload/s",
-                            f"Successful responses: {successful_responses}/{concurrent_requests}",
+                            f"Successful responses: {len([r for r in responses if r.status == 200])}",
                             "#" * 60,
                         ]
                     )
@@ -482,7 +387,7 @@ class Backend:
                     if line:
                         await handle_log_line(line.rstrip())
                     else:
-                        await asyncio.sleep(LOG_POLL_INTERVAL)
+                        time.sleep(LOG_POLL_INTERVAL)
 
         ###########
 

lib/data_types.py

@@ -3,7 +3,7 @@ import logging
 from dataclasses import dataclass, field
 from enum import Enum
 from abc import ABC, abstractmethod
-from typing import Dict, Any, Union, Tuple, Optional, Set, TypeVar, Generic, Type, Awaitable
+from typing import Dict, Any, Union, Tuple, Optional, Set, TypeVar, Generic, Type
 from aiohttp import web, ClientResponse
 import inspect
 
@@ -70,7 +70,6 @@ class AuthData:
     endpoint: str
     reqnum: int
     url: str
-    request_idx: int
 
     @classmethod
     def from_json_msg(cls, json_msg: Dict[str, Any]):
@@ -197,26 +196,6 @@ class SystemMetrics:
         self.model_loading_time = None
 
 
-@dataclass
-class RequestMetrics:
-    """Tracks metrics for an active request."""
-    request_idx: int
-    reqnum: int
-    workload: float
-    status: str
-    success: bool = False
-
-@dataclass
-class BenchmarkResult:
-    request_idx: int
-    workload: float
-    task: Awaitable[ClientResponse]
-    response: Optional[ClientResponse] = None
-
-    @property
-    def is_successful(self) -> bool:
-        return self.response is not None and self.response.status == 200
-
 @dataclass
 class ModelMetrics:
     """Model specific metrics"""
@@ -226,14 +205,12 @@ class ModelMetrics:
     workload_received: float
     workload_cancelled: float
     workload_errored: float
-    workload_rejected: float
     # these are not
     workload_pending: float
     error_msg: Optional[str]
     max_throughput: float
     requests_recieved: Set[int] = field(default_factory=set)
-    requests_working: dict[int, RequestMetrics] = field(default_factory=dict)
-    requests_deleting: list[RequestMetrics] = field(default_factory=list)
+    requests_working: Set[int] = field(default_factory=set)
     last_update: float = field(default_factory=time.time)
 
     @classmethod
@@ -243,30 +220,19 @@ class ModelMetrics:
             workload_served=0.0,
             workload_cancelled=0.0,
             workload_errored=0.0,
-            workload_rejected=0.0,
             workload_received=0.0,
             error_msg=None,
             max_throughput=0.0,
         )
-    
+
+    @property
+    def cur_perf(self) -> float:
+        return max(self.workload_served / (time.time() - self.last_update), 0.0)
+
     @property
     def workload_processing(self) -> float:
         return max(self.workload_received - self.workload_cancelled, 0.0)
 
-    @property
-    def wait_time(self) -> float:
-        if (len(self.requests_working) == 0):
-            return 0.0
-        return sum([request.workload for request in self.requests_working.values()]) / max(self.max_throughput, 0.00001)
-    
-    @property
-    def cur_load(self) -> float:
-        return sum([request.workload for request in self.requests_working.values()])
-
-    @property
-    def working_request_idxs(self) -> list[int]:
-        return [req.request_idx for req in self.requests_working.values()]
-
     def set_errored(self, error_msg):
         self.reset()
         self.error_msg = error_msg
@@ -276,20 +242,16 @@ class ModelMetrics:
         self.workload_received = 0
         self.workload_cancelled = 0
         self.workload_errored = 0
-        self.workload_rejected = 0
         self.last_update = time.time()
 
 
 @dataclass
-class AutoScalerData:
+class AutoScalaerData:
     """Data that is reported to autoscaler"""
 
     id: int
-    version: str
     loadtime: float
     cur_load: float
-    rej_load: float
-    new_load: float
     error_msg: str
     max_perf: float
     cur_perf: float
@@ -298,7 +260,6 @@ class AutoScalerData:
     num_requests_working: int
     num_requests_recieved: int
     additional_disk_usage: float
-    working_request_idxs: list[int]
     url: str
 
 

lib/metrics.py

@@ -5,14 +5,13 @@ import json
 from asyncio import sleep
 from dataclasses import dataclass, asdict, field
 from functools import cache
-import asyncio
-from aiohttp import ClientSession, ClientTimeout, TCPConnector, ClientResponseError
 
-from lib.data_types import AutoScalerData, SystemMetrics, ModelMetrics, RequestMetrics
+import requests
+
+from lib.data_types import AutoScalaerData, SystemMetrics, ModelMetrics
 from typing import Awaitable, NoReturn, List
 
 METRICS_UPDATE_INTERVAL = 1
-DELETE_REQUESTS_INTERVAL = 1
 
 log = logging.getLogger(__file__)
 
@@ -27,9 +26,7 @@ def get_url() -> str:
 
 @dataclass
 class Metrics:
-    version: str = "0"
     last_metric_update: float = 0.0
-    last_request_served: float = 0.0
     update_pending: bool = False
     id: int = field(default_factory=lambda: int(os.environ["CONTAINER_ID"]))
     report_addr: List[str] = field(
@@ -38,84 +35,42 @@ class Metrics:
     url: str = field(default_factory=get_url)
     system_metrics: SystemMetrics = field(default_factory=SystemMetrics.empty)
     model_metrics: ModelMetrics = field(default_factory=ModelMetrics.empty)
-    _session: ClientSession | None = field(default=None, init=False, repr=False)
 
-    async def http(self) -> ClientSession:
-        if self._session is None:
-            self._session = ClientSession(
-                timeout=ClientTimeout(total=10),
-                connector=TCPConnector(limit=8, limit_per_host=4, force_close=True, enable_cleanup_closed=True)
-            )
-        return self._session
-    
-    async def aclose(self) -> None:
-        if self._session is not None:
-            await self._session.close()
-            self._session = None
-
-    def _request_start(self, request: RequestMetrics) -> None:
+    def _request_start(self, workload: float, reqnum: int) -> None:
         """
         this function is called prior to forwarding a request to a model API.
         """
         log.debug("request start")
-        request.status = "Started"
-        self.model_metrics.workload_pending += request.workload
-        self.model_metrics.workload_received += request.workload
-        self.model_metrics.requests_recieved.add(request.reqnum)
-        self.model_metrics.requests_working[request.reqnum] = request
-        self.update_pending = True
+        self.model_metrics.workload_pending += workload
+        self.model_metrics.workload_received += workload
+        self.model_metrics.requests_recieved.add(reqnum)
+        self.model_metrics.requests_working.add(reqnum)
 
-    def _request_end(self, request: RequestMetrics) -> None:
+    def _request_end(self, workload: float, reqnum: int) -> None:
         """
         this function is called after handling of a request ends, regardless of the outcome
         """
-        self.model_metrics.workload_pending -= request.workload
-        self.model_metrics.requests_working.pop(request.reqnum, None)
-        self.model_metrics.requests_deleting.append(request)
-        self.last_request_served = time.time()
+        self.model_metrics.workload_pending -= workload
+        self.model_metrics.requests_working.discard(reqnum)
 
-    def _request_success(self, request: RequestMetrics) -> None:
+    def _request_success(self, workload: float) -> None:
         """
         this function is called after a response from model API is received and forwarded.
         """
-        self.model_metrics.workload_served += request.workload
-        request.status = "Success"
-        request.success = True
+        self.model_metrics.workload_served += workload
         self.update_pending = True
 
-    def _request_errored(self, request: RequestMetrics) -> None:
+    def _request_errored(self, workload: float) -> None:
         """
         this function is called if model API returns an error
         """
-        self.model_metrics.workload_errored += request.workload
-        request.status = "Error"
-        request.success = False
-        self.update_pending = True
+        self.model_metrics.workload_errored += workload
 
-    def _request_canceled(self, request: RequestMetrics) -> None:
+    def _request_canceled(self, workload: float) -> None:
         """
         this function is called if client drops connection before model API has responded
         """
-        self.model_metrics.workload_cancelled += request.workload
-        request.success = True
-        request.status = "Cancelled"
-    
-    def _request_reject(self, request: RequestMetrics):
-        """
-        this function is called if the current wait time for the model is above max_wait_time
-        """
-        self.model_metrics.requests_recieved.add(request.reqnum)
-        self.model_metrics.requests_deleting.append(request)
-        self.model_metrics.workload_rejected += request.workload
-        request.success = False
-        request.status = "Rejected"
-        self.update_pending = True
-
-    async def _send_delete_requests_loop(self) -> Awaitable[NoReturn]:
-        while True:
-            await sleep(DELETE_REQUESTS_INTERVAL)
-            if len(self.model_metrics.requests_deleting) > 0:
-                await self.__send_delete_requests_and_reset()
+        self.model_metrics.workload_cancelled += workload
 
     async def _send_metrics_loop(self) -> Awaitable[NoReturn]:
         while True:
@@ -123,10 +78,10 @@ class Metrics:
             elapsed = time.time() - self.last_metric_update
             if self.system_metrics.model_is_loaded is False and elapsed >= 10:
                 log.debug(f"sending loading model metrics after {int(elapsed)}s wait")
-                await self.__send_metrics_and_reset()
+                self.__send_metrics_and_reset(elapsed)
             elif self.update_pending or elapsed > 10:
                 log.debug(f"sending loaded model metrics after {int(elapsed)}s wait")
-                await self.__send_metrics_and_reset()
+                self.__send_metrics_and_reset(elapsed)
 
     def _model_loaded(self, max_throughput: float) -> None:
         self.system_metrics.model_loading_time = (
@@ -139,88 +94,27 @@ class Metrics:
         self.model_metrics.set_errored(error_msg)
         self.system_metrics.model_is_loaded = True
 
-    def _set_version(self, version: str) -> None:
-        self.version = version
-
     #######################################Private#######################################
 
-    async def __send_delete_requests_and_reset(self):
-        async def post(report_addr: str, idxs: list[int], success_flag: bool) -> bool:
-            data = {
-                "worker_id": self.id,
-                "request_idxs": idxs,
-                "success": success_flag,
-            }
-            log.debug(
-                f"Deleting requests that {'succeeded' if success_flag else 'failed'}: {data['request_idxs']}"
-            )
-            full_path = report_addr.rstrip("/") + "/delete_requests/"
-            for attempt in range(1, 4):
-                try:
-                    session = await self.http()
-                    async with session.post(full_path, json=data) as res:
-                        log.debug(f"delete_requests response: {res.status}")
-                        res.raise_for_status()
-                    return True
-                except asyncio.TimeoutError:
-                    log.debug("delete_requests timed out")
-                except (ClientResponseError, Exception) as e:
-                    log.debug(f"delete_requests failed with error: {e}")
-                await asyncio.sleep(2)
-                log.debug(f"retrying delete_request, attempt: {attempt}")
-            return False
+    def __send_metrics_and_reset(self, elapsed):
 
-        # Take a snapshot of what we plan to send this tick.
-        # New arrivals after this snapshot will remain in the queue for the next tick.
-        snapshot = list(self.model_metrics.requests_deleting)
-        success_idxs = [r.request_idx for r in snapshot if r.success is True]
-        failed_idxs  = [r.request_idx for r in snapshot if r.success is False]
-
-        if not success_idxs and not failed_idxs:
-            return  # nothing to do
-
-        for report_addr in self.report_addr:
-            sent_success = True
-            sent_failed  = True
-
-            if success_idxs:
-                sent_success = await post(report_addr, success_idxs, True)
-            if failed_idxs:
-                sent_failed = await post(report_addr, failed_idxs, False)
-
-            if sent_success and sent_failed:
-                # Remove only the items we actually sent from the live queue.
-                sent_set = set(success_idxs) | set(failed_idxs)
-                self.model_metrics.requests_deleting[:] = [
-                    r for r in self.model_metrics.requests_deleting
-                    if r.request_idx not in sent_set
-                ]
-                break
-
-
-    async def __send_metrics_and_reset(self):
-
-        def compute_autoscaler_data() -> AutoScalerData:
-            return AutoScalerData(
+        def compute_autoscaler_data() -> AutoScalaerData:
+            return AutoScalaerData(
                 id=self.id,
-                version=self.version,
                 loadtime=(self.system_metrics.model_loading_time or 0.0),
-                new_load=self.model_metrics.workload_processing,
-                cur_load=self.model_metrics.cur_load,
-                rej_load=self.model_metrics.workload_rejected,
+                cur_load=(self.model_metrics.workload_processing / elapsed),
                 max_perf=self.model_metrics.max_throughput,
-                cur_perf=self.model_metrics.workload_served,
+                cur_perf=self.model_metrics.cur_perf,
                 error_msg=self.model_metrics.error_msg or "",
                 num_requests_working=len(self.model_metrics.requests_working),
                 num_requests_recieved=len(self.model_metrics.requests_recieved),
                 additional_disk_usage=self.system_metrics.additional_disk_usage,
-                working_request_idxs=self.model_metrics.working_request_idxs,
                 cur_capacity=0,
                 max_capacity=0,
                 url=self.url,
             )
 
-        async def send_data(report_addr: str) -> bool:
+        def send_data(report_addr: str) -> bool:
             data = compute_autoscaler_data()
             full_path = report_addr.rstrip("/") + "/worker_status/"
             log.debug(
@@ -235,15 +129,14 @@ class Metrics:
             )
             for attempt in range(1, 4):
                 try:
-                    session = await self.http()
-                    async with session.post(full_path, json=asdict(data)) as res:
-                        res.raise_for_status()
+                    res = requests.post(full_path, json=asdict(data), timeout=1)
+                    res.raise_for_status()
                     return True
-                except asyncio.TimeoutError:
+                except requests.Timeout:
                     log.debug(f"autoscaler status update timed out")
-                except (ClientResponseError, Exception)  as e:
+                except Exception as e:
                     log.debug(f"autoscaler status update failed with error: {e}")
-                await asyncio.sleep(2)
+                time.sleep(2)
                 log.debug(f"retrying autoscaler status update, attempt: {attempt}")
             log.debug(f"failed to send update through {report_addr}")
             return False
@@ -253,7 +146,7 @@ class Metrics:
         self.system_metrics.update_disk_usage()
 
         for report_addr in self.report_addr:
-            success = await send_data(report_addr)
+            success = send_data(report_addr)
             if success is True:
                 break
         self.update_pending = False

start_server.sh

@@ -59,12 +59,12 @@ then
     fi
 
     # Fork testing
-    [[ ! -d $SERVER_DIR ]] && git clone "${PYWORKER_REPO:-https://github.com/vast-ai/pyworker}" "$SERVER_DIR"
+    git clone "${PYWORKER_REPO:-https://github.com/vast-ai/pyworker}" "$SERVER_DIR"
     if [[ -n ${PYWORKER_REF:-} ]]; then
         (cd "$SERVER_DIR" && git checkout "$PYWORKER_REF")
     fi
 
-    uv venv --python-preference only-managed "$ENV_PATH" -p 3.10
+    uv venv --managed-python "$ENV_PATH" -p 3.10
     source "$ENV_PATH/bin/activate"
 
     uv pip install -r "${SERVER_DIR}/requirements.txt"

workers/comfyui-json/README.md

@@ -12,21 +12,9 @@ A docker image is provided but you may use any if the above requirements are met
 
 ## Benchmarking
 
-### Custom Benchmark Workflows
+A simple image generation benchmark runs when each worker initializes to validate GPU performance and identify underperforming machines.
 
-You can provide a custom ComfyUI workflow for benchmarking by creating `workers/comfyui-json/misc/benchmark.json`. This allows you to test performance using your preferred models and workflow complexity.
-
-**Ways to provide the benchmark file:**
-- Fork this repository and add your `benchmark.json` file
-- Write the file during worker provisioning (onstart script or setup phase)
-
-An example file is provided in the repository. To ensure varied generations, use the placeholder `__RANDOM_INT__` in place of static seed values - it will be replaced with a random integer for each benchmark run.
-
-### Default Benchmark (Fallback)
-
-If `benchmark.json` is not available, a simple image generation benchmark runs when each worker initializes. This validates GPU performance and helps identify underperforming machines.
-
-The default benchmark uses Stable Diffusion v1.5 with ComfyUI's standard text-to-image workflow. Configure it using these environment variables:
+The benchmark uses Stable Diffusion v1.5 with ComfyUI's default text-to-image workflow. Configure the benchmark complexity and duration using these variables:
 
 | Environment Variable | Default Value | Description |
 | -------------------- | ------------- | ----------- |
@@ -36,7 +24,7 @@ The default benchmark uses Stable Diffusion v1.5 with ComfyUI's standard text-to
 
 Each benchmark run uses a random prompt from `misc/test_prompts.txt` and a random seed to ensure consistent GPU load patterns.
 
-#### Calibrating Fallback Benchmark Duration
+### Calibrating Benchmark Duration
 
 To screen for underperforming hardware, set `BENCHMARK_TEST_STEPS` to match your expected production workflow duration. This allows you to identify machines that won't meet performance requirements.
 

workers/comfyui-json/data_types.py

@@ -5,13 +5,12 @@ import dataclasses
 from typing import Dict, Any
 from functools import cache
 from math import ceil
-from pathlib import Path
-import json
-import logging
 
 from lib.data_types import ApiPayload, JsonDataException
 
-log = logging.getLogger(__file__)
+
+with open("workers/comfyui/misc/test_prompts.txt", "r") as f:
+    test_prompts = f.readlines()
 
 def count_workload() -> float:
     # Always 100.0 where there is a single instance of ComfyUI handling requests
@@ -25,32 +24,9 @@ class ComfyWorkflowData(ApiPayload):
     @classmethod
     def for_test(cls):
         """
-        If the user has provided a benchmark workflow we can use it here to properly gauge performance.
-        Otherwise, use the variables available to simulate workflows of the required running time
+        Use the variables available to simulate workflows of the required running time
         Example: SD1.5, simple image gen 10000 steps, 512px x 512px will run for approximately 9 minutes @ ~18 it/s (RTX 4090)
         """
-        # Try to load benchmark.json
-        benchmark_file = Path("workers/comfyui-json/misc/benchmark.json")
-        
-        if benchmark_file.exists():
-            try:
-                with open(benchmark_file, "r") as f:
-                    benchmark_workflow = json.load(f)
-                return cls(
-                    input={
-                        "request_id": f"test-{random.randint(1000, 99999)}",
-                        "workflow_json": benchmark_workflow
-                    }
-                )
-            except (json.JSONDecodeError, IOError):
-                # JSON is malformed or file can't be read, fall through to default
-                log.error(f"Failed to benchmark using {benchmark_file}")
-        
-        # Fallback: read prompts and construct payload
-        log.info("Using fallback method for benchmarking")
-        with open("workers/comfyui-json/misc/test_prompts.txt", "r") as f:
-            test_prompts = f.readlines()
-        
         test_prompt = random.choice(test_prompts).rstrip()
         return cls(
             input={

workers/comfyui-json/misc/benchmark.json.example

@@ -1,107 +0,0 @@
-{
-    "3": {
-        "inputs": {
-            "seed": "__RANDOM_INT__",
-            "steps": 20,
-            "cfg": 8,
-            "sampler_name": "euler",
-            "scheduler": "normal",
-            "denoise": 1,
-            "model": [
-            "4",
-            0
-            ],
-            "positive": [
-            "6",
-            0
-            ],
-            "negative": [
-            "7",
-            0
-            ],
-            "latent_image": [
-            "5",
-            0
-            ]
-        },
-        "class_type": "KSampler",
-        "_meta": {
-            "title": "KSampler"
-        }
-    },
-    "4": {
-        "inputs": {
-            "ckpt_name": "v1-5-pruned-emaonly-fp16.safetensors"
-        },
-        "class_type": "CheckpointLoaderSimple",
-        "_meta": {
-            "title": "Load Checkpoint"
-        }
-    },
-    "5": {
-        "inputs": {
-            "width": 512,
-            "height": 512,
-            "batch_size": 1
-        },
-        "class_type": "EmptyLatentImage",
-        "_meta": {
-            "title": "Empty Latent Image"
-        }
-    },
-    "6": {
-        "inputs": {
-            "text": "beautiful scenery nature glass bottle landscape, , purple galaxy bottle,",
-            "clip": [
-            "4",
-            1
-            ]
-        },
-        "class_type": "CLIPTextEncode",
-        "_meta": {
-            "title": "CLIP Text Encode (Prompt)"
-        }
-    },
-    "7": {
-        "inputs": {
-            "text": "text, watermark",
-            "clip": [
-            "4",
-            1
-            ]
-        },
-        "class_type": "CLIPTextEncode",
-        "_meta": {
-            "title": "CLIP Text Encode (Prompt)"
-        }
-    },
-    "8": {
-        "inputs": {
-            "samples": [
-            "3",
-            0
-            ],
-            "vae": [
-            "4",
-            2
-            ]
-        },
-        "class_type": "VAEDecode",
-        "_meta": {
-            "title": "VAE Decode"
-        }
-    },
-    "9": {
-        "inputs": {
-            "filename_prefix": "ComfyUI",
-            "images": [
-            "8",
-            0
-            ]
-        },
-        "class_type": "SaveImage",
-        "_meta": {
-            "title": "Save Image"
-        }
-    }
-}

workers/comfyui-json/server.py

@@ -19,7 +19,6 @@ MODEL_SERVER_START_LOG_MSG = "To see the GUI go to: "
 MODEL_SERVER_ERROR_LOG_MSGS = [
     "MetadataIncompleteBuffer",  # This error is emitted when the downloaded model is corrupted
     "Value not in list: ",  # This error is emitted when the model file is not there at all
-    "[ERROR] Provisioning Script failed", # Error inserted by provisioning script if models/nodes fail to download
 ]
 
 
@@ -71,7 +70,7 @@ class ComfyWorkflowHandler(EndpointHandler[ComfyWorkflowData]):
 
     @property
     def healthcheck_endpoint(self) -> Optional[str]:
-        return f"{MODEL_SERVER_URL}/health"
+        return "/health"
 
     @classmethod
     def payload_cls(cls) -> Type[ComfyWorkflowData]:

workers/openai/data_types/server.py

@@ -119,25 +119,14 @@ class GenericHandler(EndpointHandler[GenericData], ABC):
 class CompletionsData(GenericData):
     @classmethod
     def for_test(cls) -> "CompletionsData":
-        system_prompt = """You are a helpful AI assistant. You have access to the following knowledge base:
-    
-        Zebras (US: /ˈziːbrəz/, UK: /ˈzɛbrəz, ˈziː-/)[2] (subgenus Hippotigris) are African equines 
-        with distinctive black-and-white striped coats. There are three living species: Grévy's zebra 
-        (Equus grevyi), the plains zebra (E. quagga), and the mountain zebra (E. zebra). Zebras share the 
-        genus Equus with horses and asses, the three groups being the only living members of the family 
-        Equidae. Zebra stripes come in different patterns, unique to each individual. Zebras inhabit eastern 
-        and southern Africa and can be found in a variety of habitats such as savannahs, grasslands, 
-        woodlands, shrublands, and mountainous areas.
-        
-        Please answer the following question based on the above context."""
-        unique_question = " ".join(random.choices(WORD_LIST, k=int(100)))
+        prompt = " ".join(random.choices(WORD_LIST, k=int(250)))
         model = os.environ.get("MODEL_NAME")
         if not model:
             raise ValueError("MODEL_NAME environment variable not set")
 
         test_input = {
             "model": model,
-            "prompt": f"{system_prompt}\n\n{unique_question}",
+            "prompt": prompt,
             "temperature": 0.7,
             "max_tokens": 500,
         }
@@ -164,18 +153,7 @@ class ChatCompletionsData(GenericData):
 
     @classmethod
     def for_test(cls) -> "ChatCompletionsData":
-        system_prompt = """You are a helpful AI assistant. You have access to the following knowledge base:
-    
-        Zebras (US: /ˈziːbrəz/, UK: /ˈzɛbrəz, ˈziː-/)[2] (subgenus Hippotigris) are African equines 
-        with distinctive black-and-white striped coats. There are three living species: Grévy's zebra 
-        (Equus grevyi), the plains zebra (E. quagga), and the mountain zebra (E. zebra). Zebras share the 
-        genus Equus with horses and asses, the three groups being the only living members of the family 
-        Equidae. Zebra stripes come in different patterns, unique to each individual. Zebras inhabit eastern 
-        and southern Africa and can be found in a variety of habitats such as savannahs, grasslands, 
-        woodlands, shrublands, and mountainous areas.
-        
-        Please answer the following question based on the above context."""
-        unique_question = " ".join(random.choices(WORD_LIST, k=int(100)))
+        prompt = " ".join(random.choices(WORD_LIST, k=int(250)))
         model = os.environ.get("MODEL_NAME")
         if not model:
             raise ValueError("MODEL_NAME environment variable not set")
@@ -183,10 +161,7 @@ class ChatCompletionsData(GenericData):
         # Chat completions use messages format instead of prompt
         test_input = {
             "model": model,
-            "messages": [
-                {"role": "system", "content": system_prompt},  # Shared prefix
-                {"role": "user", "content": unique_question}   # Unique per request
-            ],
+            "messages": [{"role": "user", "content": prompt}],
             "temperature": 0.7,
             "max_tokens": 500,
         }

workers/openai/test_load.py

@@ -42,7 +42,6 @@ class ReqResult:
     total_ms: float
     ok: bool
     error: str = ""
-    status_code: int = 0
     t_start: float = 0.0
     t_end: float = 0.0
     workload: float = 0.0
@@ -59,73 +58,31 @@ def do_one(endpoint_name: str,
            route_session,
            worker_session):
     try:
-        workload = payload.count_workload()
-        route_payload = {"endpoint": endpoint_name, "api_key": endpoint_api_key, "cost": workload}
+        u = payload.count_workload()
+        route_payload = {"endpoint": endpoint_name, "api_key": endpoint_api_key, "cost": u}
         headers = {"Authorization": f"Bearer {endpoint_api_key}"}
         start = time.time()
         r0 = route_session.post(urljoin(server_url, "/route/"), json=route_payload, headers=headers, timeout=4)
         t_after_route = time.time()
         if r0.status_code != 200:
-            results_list.append(ReqResult(worker_url="", 
-                                            route_ms=(t_after_route - start) * 1000.0, 
-                                            worker_ms=0.0, 
-                                            total_ms=(t_after_route - start) * 1000.0, 
-                                            ok=False, 
-                                            error=f"route error {r0.reason} {r0.text}",
-                                            status_code=r0.status_code,
-                                            t_start=start - t0, 
-                                            t_end=t_after_route - t0, 
-                                            workload=workload))
+            results_list.append(ReqResult("", (t_after_route - start) * 1000.0, 0.0, (t_after_route - start) * 1000.0, False,
+                                          f"route {r0.status_code} {r0.text}"))
             return
         msg = r0.json()
 
-        # 1) Check if we got a worker back from route
-        worker_url = msg.get("url", "")
-        if not worker_url:
-            status = msg.get("status", "")
+        # 1) "Status" is in the response when no worker is ready
+        worker_sampled = True
+        status = msg.get("status", "")
+        if status:
             m = re.search(r"total workers:\s*(\d+).*loading workers:\s*(\d+).*standby workers:\s*(\d+).*error workers:\s*(\d+)", status, re.I | re.S)
             if m:
                 tot, loading, standby, err = map(int, m.groups())
                 idle = max(tot - loading - standby - err, 0)
                 status_samples.append((time.time() - t0, idle))
+                worker_sampled = False
 
-        # 2) If we got a worker, send the request
-        if worker_url:
-            req = dict(payload=payload.__dict__, auth_data=AuthData.from_json_msg(msg).__dict__)
-            t_before_worker = time.time()
-            r1 = worker_session.post(
-                urljoin(worker_url, worker_endpoint),
-                json=req,
-                verify=get_cert_file_path(),
-                timeout=(4, 120),
-            )
-            t_after_worker = time.time()
-            if r1.status_code != 200:
-                results_list.append(ReqResult(worker_url=worker_url, 
-                                                route_ms=(t_after_route - start) * 1000.0, 
-                                                worker_ms=(t_after_worker - t_before_worker) * 1000.0,
-                                                total_ms=(t_after_worker - start) * 1000.0, 
-                                                ok=False,
-                                                error=f"worker inference error {r1.reason} {r1.text}",
-                                                status_code=r1.status_code,
-                                                t_start=start - t0, 
-                                                t_end=t_after_worker - t0, 
-                                                workload=workload))
-                return
-            # Success case
-            results_list.append(ReqResult(worker_url=worker_url, 
-                                            route_ms=(t_after_route - start) * 1000.0, 
-                                            worker_ms=(t_after_worker - t_before_worker) * 1000.0, 
-                                            total_ms=(t_after_worker - start) * 1000.0,
-                                            ok=True,
-                                            error="",
-                                            status_code=200,
-                                            t_start=start - t0, 
-                                            t_end=t_after_worker - t0, 
-                                            workload=workload))
-
-        # 3) If so, sample via /get_endpoint_workers/ for eligible (idle) worker tracking
-        if worker_url:
+        # 2) Otherwise (successful request), sample via /get_endpoint_workers/ for eligible (idle) worker tracking
+        if worker_sampled:
             try:
                 r_status = route_session.post(
                     urljoin(server_url, "/get_endpoint_workers/"),
@@ -143,18 +100,29 @@ def do_one(endpoint_name: str,
                     status_samples.append((time.time() - t0, idle))
             except Exception:
                 pass
+
+        # 3) Send the request
+        worker_address = msg["url"]
+        req = dict(payload=payload.__dict__, auth_data=AuthData.from_json_msg(msg).__dict__)
+        t1 = time.time()
+        # Use explicit connect/read timeouts to avoid long hangs
+        r1 = worker_session.post(
+            urljoin(worker_address, worker_endpoint),
+            json=req,
+            verify=get_cert_file_path(),
+            timeout=(4, 120),
+        )
+        t2 = time.time()
+        if r1.status_code != 200:
+            results_list.append(ReqResult(worker_address, (t_after_route - start) * 1000.0, (t2 - t1) * 1000.0,
+                                          (t2 - start) * 1000.0, False,
+                                          f"infer {r1.status_code} {r1.text}"))
+            return
+        results_list.append(ReqResult(worker_address, (t_after_route - start) * 1000.0, (t2 - t1) * 1000.0, (t2 - start) * 1000.0,
+                                        True, "", t_start=start - t0, t_end=t2 - t0, workload=u))
     except Exception as e:
         t = time.time()
-        results_list.append(ReqResult(worker_url="", 
-                                        route_ms=0.0, 
-                                        worker_ms=0.0, 
-                                        total_ms=0.0, 
-                                        ok=False, 
-                                        error=f"unknown error {e}",
-                                        status_code=0,
-                                        t_start=t - t0, 
-                                        t_end=t - t0, 
-                                        workload=0.0))
+        results_list.append(ReqResult("", (t - start) * 1000.0, 0.0, (t - start) * 1000.0, False, str(e)))
 
 def run_load_with_metrics(num_requests: int,
                           requests_per_second: float,
@@ -164,7 +132,7 @@ def run_load_with_metrics(num_requests: int,
                           worker_endpoint: str,
                           instance: str,
                           out_path: str):
-
+    # Resolve endpoint id + endpoint-scoped API key
     ep_info = Endpoint.get_endpoint_info(endpoint_name=endpoint_group_name,
                                          account_api_key=account_api_key,
                                          instance=instance)
@@ -177,7 +145,8 @@ def run_load_with_metrics(num_requests: int,
     t0 = time.time()
     results = []
     status_samples = []
-    max_concurrency = int(os.environ.get("MAX_CONCURRENCY", "8192"))
+    # Concurrency control
+    max_concurrency = int(os.environ.get("MAX_CONCURRENCY", "1024"))
     submit_queue_factor = 2  # cap queued tasks to reduce memory
 
     # Shared HTTP sessions with connection pooling (persistent connections)
@@ -189,9 +158,9 @@ def run_load_with_metrics(num_requests: int,
         return sess
 
     # Router: mostly single host, small connection pool is sufficient
-    route_session = make_session(pool_connections=1, pool_maxsize=max_concurrency)
+    route_session = make_session(pool_connections=8, pool_maxsize=max_concurrency)
     # Workers: many hosts; allow many pools and per-host concurrency up to max_concurrency
-    worker_session = make_session(pool_connections=64, pool_maxsize=max_concurrency // 8)
+    worker_session = make_session(pool_connections=max(256, max_concurrency), pool_maxsize=max_concurrency)
 
     # Fire requests using a thread pool, scheduling at requested RPS
     inflight = set()
@@ -240,12 +209,11 @@ def run_load_with_metrics(num_requests: int,
 
     total_ms = np.array([r.total_ms for r in oks]) if succ else np.array([])
     worker_ms = np.array([r.worker_ms for r in oks]) if succ else np.array([])
-    route_ms = np.array([r.route_ms for r in oks]) if succ else np.array([])
+    #route_ms = np.array([r.route_ms for r in oks]) if succ else np.array([])
 
     avg_total = float(np.mean(total_ms)) if succ else 0.0
-    avg_worker = float(np.mean(worker_ms)) if succ else 0.0
-    avg_route = float(np.mean(route_ms)) if succ else 0.0
     p50_total, p95_total = (float(np.percentile(total_ms, 50)), float(np.percentile(total_ms, 95))) if succ else (0.0, 0.0)
+    total_compute_time_ms = float(np.sum(worker_ms)) if succ else 0.0
 
     # Distribution over workers (by host:port)
     hosts = [urlparse(r.worker_url).netloc for r in oks if r.worker_url]
@@ -272,11 +240,11 @@ def run_load_with_metrics(num_requests: int,
 
     print(f"\nResults: total={total_reqs} success={succ} errors={len(errs)}")
     print(f"Avg latency (ms): {avg_total:.1f}  p50: {p50_total:.1f}  p95: {p95_total:.1f}")
-    print(f"Avg route latency (ms): {avg_route:.1f}  Avg worker latency (ms): {avg_worker:.1f}")
+    print(f"Total compute time (sum worker latency, s): {total_compute_time_ms/1000.0:.2f}")
     if errs:
         print("Sample errors:")
         for e in errs[:5]:
-            print(f"  {e.status_code} {e.error}")
+            print(f"  {e.error}")
 
     # Plot: 2x3 grid
     fig, axes = plt.subplots(2, 3, figsize=(15, 8))
@@ -296,7 +264,7 @@ def run_load_with_metrics(num_requests: int,
     # Latency histogram (total)
     ax1 = axes[0, 1]
     if succ:
-        ax1.hist(total_ms, bins=30)
+        ax1.hist(total_ms, bins=30, color="#4e79a7")
     ax1.set_title("Total latency (ms)")
     ax1.set_xlabel("ms")
     ax1.set_ylabel("freq")
@@ -322,7 +290,7 @@ def run_load_with_metrics(num_requests: int,
         ax_idle.plot(ts, vals, "-o", ms=3)
     ax_idle.set_title("Completions per second")
     ax_idle.set_xlabel("time (s)")
-    ax_idle.set_ylabel("completions / sec")
+    ax_idle.set_ylabel("req/s")
 
     # Summary text
     ax3 = axes[1, 1]
@@ -330,36 +298,22 @@ def run_load_with_metrics(num_requests: int,
     text = (
         f"Total requests: {total_reqs}\n"
         f"Success: {succ}  Errors: {len(errs)}\n"
-        f"Avg total latency: {avg_total:.1f} ms\n"
+        f"Avg latency: {avg_total:.1f} ms\n"
         f"p50: {p50_total:.1f} ms  p95: {p95_total:.1f} ms\n"
-        f"Avg route latency: {avg_route:.1f} ms\n"  
-        f"Avg worker latency: {avg_worker:.1f} ms\n"
-        f"300 errors: {len([r for r in errs if r.status_code >= 300 and r.status_code < 400])}\n"
-        f"429 errors: {len([r for r in errs if r.status_code == 429])}\n"
-        f"500 errors: {len([r for r in errs if r.status_code >= 500])}\n"
-        f"Other errors: {len([r for r in errs if r.status_code not in [300, 429, 500]])}\n"
+        f"Total compute time: {total_compute_time_ms/1000.0:.2f} s"
     )
     ax3.set_title("Summary")
     ax3.text(0.02, 0.98, text, va="top", ha="left", fontsize=11, transform=ax3.transAxes)
 
-    # Error count over time
-    ax_errors = axes[1, 2]
-    all_end_times = [int(r.t_end) for r in results if r.t_end > 0]
-    if all_end_times:
-        min_second = min(all_end_times)
-        max_second = max(all_end_times)
-        # Count errors per second
-        errors_per_second = {}
-        for result in errs:
-            second = int(result.t_end)
-            errors_per_second[second] = errors_per_second.get(second, 0) + 1
-        # Create complete timeline including zeros
-        time_seconds = list(range(min_second, max_second + 1))
-        error_counts = [errors_per_second.get(sec, 0) for sec in time_seconds]
-        ax_errors.plot(time_seconds, error_counts, "-o", ms=3)
-    ax_errors.set_title("Errors per second")
-    ax_errors.set_xlabel("time (s)")
-    ax_errors.set_ylabel("errors / sec")
+    # Latency CDF (total_ms)
+    ax_cdf = axes[1, 2]
+    if succ:
+        x = np.sort(total_ms)
+        y = np.linspace(0, 1, len(x), endpoint=True)
+        ax_cdf.plot(x, y)
+    ax_cdf.set_title("Latency CDF")
+    ax_cdf.set_xlabel("ms")
+    ax_cdf.set_ylabel("fraction ≤ x")
 
     # Ensure unique output path and create directory if needed
     final_out_path = get_incremented_path(out_path)