Files
app/backend/fluksio/main.py
T
stroblmeandClaude Opus 5 6ff56533f5 Schedule a node across every machine, not just this one
The engine answered "where does this node run" twice, in two ways that could
not see each other: a device sent it to a worker carrying that label, and
resources were counted against the engine's own cores. Declaring both meant the
second answer won and nothing was counted at all — which the data-science
getting-started page and the worked example both do.

One question now, in flow/placement.py: of every machine attached, which could
grant what this node asked for, and which of those has it free. The books move
onto each machine — one accountant per worker, built from the inventory it
reported — and the waiting moves above them, where one condition variable can
be woken by a release anywhere or by a worker attaching. Locks go one way:
placer, then a machine's books, never back.

So a node asking for a card now finds the box that has one, rather than being
clamped down to none and run here. When nothing can grant the ask at all it is
still cut down and run — a flow written on a cluster has to work on a laptop —
but the ceiling is one real machine now, since taking the largest of each
dimension separately can describe a machine nobody has.

Two things fixed on the way. A device on a connector node held every batch run
of its flow forever, waiting for a worker that could never run an entry point.
And `prefer` falling back to the engine skipped the books, so the fallback held
nothing.

The bench flow's node has taken a `params` argument that with_settings has not
forwarded for some time, so the benchmark could not run at all: 62 ms median
submit-to-result with this, against the 61 ms on record.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01A6HeySA27EkGANZN95QySW
2026-08-27 08:49:36 +02:00

349 lines
14 KiB
Python

import asyncio
import contextlib
import logging
from collections.abc import AsyncIterator
from contextlib import AbstractAsyncContextManager, asynccontextmanager
import sentry_sdk
from fastapi import FastAPI, Request
from fastapi.concurrency import run_in_threadpool
from fastapi.responses import JSONResponse
from fastapi.routing import APIRoute
from fluksio_worker.worker_main import ARTIFACT_DIR_ENV
from starlette.middleware.cors import CORSMiddleware
from fluksio.api.main import api_router
from fluksio.api.routes.alerts import read_config as read_alerts_config
from fluksio.cloud import config as cloud_config
from fluksio.core import security
from fluksio.core.config import settings
from fluksio.core.db import engine as db_engine
from fluksio.core.db import prepare
from fluksio.flow import logs, modules
from fluksio.flow.alerts import AlertManager
from fluksio.flow.artifacts import ArtifactStore
from fluksio.flow.controller import FlowController, RebuildBusy
from fluksio.flow.dashboards import DashboardStore
from fluksio.flow.events import event_bus
from fluksio.flow.executor import ExecutionService
from fluksio.flow.metrics import MetricsCollector
from fluksio.flow.nodes.http import close_shared_client
from fluksio.flow.pipeline import ValueSource
from fluksio.flow.placement import Placer
from fluksio.flow.plugins import load_plugins
from fluksio.flow.queue import MemoryWorkQueue, RedisWorkQueue, WorkQueue
from fluksio.flow.remote import RemoteWorkerHub
from fluksio.flow.resources import ResourceAccountant, fair_share_env
from fluksio.flow.runs import RUN_STATE_TTL, RunService, sweep_artifacts
from fluksio.flow.secrets import init_secrets
from fluksio.flow.state import MemoryState, RedisState, StateBackend
from fluksio.flow.store import FlowStore
from fluksio.flow.watchdog import LoopWatchdog
from fluksio.flow.workers import PythonWorkerPool
logger = logging.getLogger(__name__)
def custom_generate_unique_id(route: APIRoute) -> str:
return f"{route.tags[0]}-{route.name}"
if settings.SENTRY_DSN and settings.ENVIRONMENT != "local":
# `enable_tracing` was removed in sentry-sdk 2.x; this is what it meant.
sentry_sdk.init(dsn=str(settings.SENTRY_DSN), traces_sample_rate=1.0)
def _state_backend() -> StateBackend:
if settings.REDIS_HOST:
return RedisState(host=settings.REDIS_HOST, port=settings.REDIS_PORT)
return MemoryState()
def _work_queue(namespace: str = "queue") -> WorkQueue:
"""Redis makes queued work survive the process; memory does not pretend to."""
if settings.REDIS_HOST:
return RedisWorkQueue(
host=settings.REDIS_HOST, port=settings.REDIS_PORT, namespace=namespace
)
return MemoryWorkQueue()
def _run_state(namespace: str) -> StateBackend:
"""A state backend of a run's own, which is what isolates it.
It expires: a finished run's messages are read out into its result, and
what is left is only worth keeping while someone might look at it.
"""
if settings.REDIS_HOST:
return RedisState(
host=settings.REDIS_HOST,
port=settings.REDIS_PORT,
namespace=namespace,
ttl=RUN_STATE_TTL,
)
return MemoryState()
async def _sweep_artifacts(store: ArtifactStore, controller: FlowController) -> None:
"""Take unreferenced artifact bytes off the disk, on a slow loop.
A flow streaming media writes one artifact per frame, so a store nothing
prunes only grows. Runs in a thread: it walks a directory and reads state.
"""
interval = settings.ARTIFACT_GC_INTERVAL_S
if interval <= 0:
return
while True:
await asyncio.sleep(interval)
try:
await run_in_threadpool(
sweep_artifacts,
store,
controller.state,
settings.ARTIFACT_GC_GRACE_S,
)
except Exception:
logger.exception("Artifact sweep failed")
def _mcp_sessions() -> AbstractAsyncContextManager[None]:
"""The MCP session manager's run scope, or nothing when MCP is off."""
if not settings.MCP_ENABLED:
return contextlib.nullcontext()
from fluksio.mcp.server import mcp as mcp_server
return mcp_server.session_manager.run()
@asynccontextmanager
async def lifespan(app: FastAPI) -> AsyncIterator[None]:
"""Start the flow engine alongside the API."""
# The schema and the first superuser, before anything reads either. It is
# idempotent, so a deployment that ran this from its own prestart step
# pays a version check for it and nothing else.
await run_in_threadpool(prepare, db_engine)
event_bus.bind(asyncio.get_running_loop())
# Node code is user code, and `print` is how it says things.
logs.install()
init_secrets(settings.SECRETS_FILE, settings.SECRET_KEY)
# Connectors register their node types before any flow is built with them.
load_plugins()
alerts = AlertManager(event_bus, config=read_alerts_config())
execution = ExecutionService(
queue=_work_queue(),
max_workers=settings.FLOW_MAX_WORKERS,
events=event_bus,
max_cascades=settings.FLOW_MAX_CASCADES,
)
store = FlowStore(settings.FLOWS_DIR)
# The packages node code imports, before anything tries to import them.
await run_in_threadpool(modules.reconcile, store)
# Beside the flows rather than in them: an artifact is what a run produced,
# not something anyone wrote, so it has no business in the git repository.
artifacts = ArtifactStore(settings.FLOWS_DIR.parent / "artifacts")
app.state.artifact_store = artifacts
accountant = ResourceAccountant(cpus=settings.FLOW_CPUS, gpus=settings.FLOW_GPUS)
app.state.resources = accountant
# Every machine a node could run on: this one, and whatever attaches.
placer = Placer(local=accountant, events=event_bus)
app.state.placer = placer
pool = PythonWorkerPool(
python=modules.venv_python(),
size=settings.FLOW_MAX_WORKERS,
events=event_bus,
# A worker in this container writes to the store directly; a remote one
# is given a URL instead. Node code calls the same two functions.
env={
ARTIFACT_DIR_ENV: str(artifacts.root),
# Every slot can be busy at once, so a worker left to size its own
# thread pool to the machine means as many processes as there are
# slots, each believing it has the whole of it. A node that says
# what it needs overrides this; one that says nothing gets a share.
**fair_share_env(accountant.cpus, settings.FLOW_MAX_WORKERS),
},
)
pool.start()
app.state.worker_pool = pool
# Assigned rather than passed both ways: the hub tells the placer when a
# machine comes or goes, and the placer needs the hub to know what is there.
worker_hub = RemoteWorkerHub(on_change=placer.wake)
placer.hub = worker_hub
app.state.worker_hub = worker_hub
controller = FlowController(
store=store,
state=_state_backend(),
events=event_bus,
max_workers=settings.FLOW_MAX_WORKERS,
fastapi_app=app,
execution=execution,
alerts=alerts,
workers=pool,
remote=worker_hub,
resources=accountant,
placer=placer,
)
app.state.flow_controller = controller
# A "dashboard" alert channel puts its alert into the graph. Bound here
# rather than passed in: the manager is built before the controller is.
alerts.publish = lambda name, value: controller.publish_message(
name, value, ValueSource(kind="api", id="alerts", label="Alerts")
)
dashboards = DashboardStore(controller.store)
app.state.dashboard_store = dashboards
controller.dashboards = dashboards
# Charts need a deeper series than the default; tell the engine
# before it starts recording.
controller.set_history_limits(dashboards.history_requirements())
# Runs read from a stream of their own: a burst of sweep runs must not
# stand between the automations and their work, and a run that takes an
# hour must not be judged by the cascade reaper's timings.
run_service = RunService(
controller=controller,
queue=_work_queue("run"),
state_factory=_run_state,
artifacts=artifacts,
)
app.state.run_service = run_service
watchdog = LoopWatchdog(event_bus)
app.state.watchdog = watchdog
watchdog_task = asyncio.create_task(watchdog.run(), name="loop-watchdog")
alerts_task = asyncio.create_task(alerts.run(), name="alert-manager")
metrics_task = asyncio.create_task(
MetricsCollector(event_bus).run(), name="metrics-collector"
)
gc_task = asyncio.create_task(
_sweep_artifacts(artifacts, controller), name="artifact-gc"
)
await controller.start()
run_service.start()
# Optional, and off unless someone enrolled this installation: the
# connector dials the portal, nothing dials in.
cloud_task: asyncio.Task[None] | None = None
app.state.cloud_connector = None
app.state.cloud_task = None
from fluksio.cloud import connector as cloud_connector
if cloud_config.exists():
cloud_connector.start(app)
cloud_task = app.state.cloud_task
# Watched whether or not one exists now: enrolling from the CLI writes the
# config from another process entirely, and an engine already serving
# should pick it up rather than need restarting.
enrol_task = asyncio.create_task(
cloud_connector.watch_enrolment(app), name="cloud-enrolment-watch"
)
try:
# A mounted sub-app gets no lifespan of its own, so the MCP session
# manager is entered here; without it every /mcp request fails.
async with _mcp_sessions():
yield
finally:
watchdog_task.cancel()
alerts_task.cancel()
metrics_task.cancel()
gc_task.cancel()
enrol_task.cancel()
# Re-read from app.state: enrolling at runtime replaces this.
running_cloud = getattr(app.state, "cloud_task", None) or cloud_task
if running_cloud is not None:
running_cloud.cancel()
await run_in_threadpool(run_service.stop)
await controller.stop()
pool.stop()
close_shared_client()
if settings.MCP_ENABLED:
from fluksio.mcp.http import aclose
await aclose()
# The schema enumerates every endpoint this installation serves, including the
# paths trigger nodes mount at runtime. That is exactly what a developer wants
# and exactly what an internet-facing deployment should not hand out, so it
# follows the environment — the same rule the portal's backend uses. The
# generated client is built from a local run, not from the deployed host.
_docs_enabled = settings.ENVIRONMENT != "production"
app = FastAPI(
title=settings.PROJECT_NAME,
openapi_url=f"{settings.API_V1_STR}/openapi.json" if _docs_enabled else None,
docs_url="/docs" if _docs_enabled else None,
redoc_url="/redoc" if _docs_enabled else None,
generate_unique_id_function=custom_generate_unique_id,
lifespan=lifespan,
)
# Set all CORS enabled origins
if settings.all_cors_origins:
app.add_middleware(
CORSMiddleware,
allow_origins=settings.all_cors_origins,
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
app.include_router(api_router, prefix=settings.API_V1_STR)
@app.exception_handler(RebuildBusy)
async def rebuild_busy(request: Request, exc: RebuildBusy) -> JSONResponse: # noqa: ARG001
"""Every route that deploys something answers a wedged rebuild the same way.
The request was fine and retrying it may well work, so this is the engine
saying it is busy rather than the request having gone wrong.
"""
return JSONResponse(status_code=503, content={"detail": str(exc)})
# Tagged because the operation-id builder reads the first tag; the route
# itself stays out of the schema.
@app.get(
"/.well-known/oauth-authorization-server",
include_in_schema=False,
tags=["oauth"],
)
def oauth_authorization_server() -> JSONResponse:
"""RFC 8414 metadata, so an agent can find its way in unaided.
The authorization endpoint is the dashboard rather than the API: approving
a client needs a signed-in human, and the browser session lives there.
"""
issuer = settings.oauth_issuer
return JSONResponse(
content={
"issuer": issuer,
"authorization_endpoint": (
f"{settings.FRONTEND_HOST.rstrip('/')}/oauth/authorize"
),
"token_endpoint": f"{issuer}{settings.API_V1_STR}/oauth/token",
"registration_endpoint": f"{issuer}{settings.API_V1_STR}/oauth/register",
"jwks_uri": f"{issuer}/.well-known/jwks.json",
"response_types_supported": ["code"],
"grant_types_supported": ["authorization_code", "refresh_token"],
"code_challenge_methods_supported": ["S256"],
"token_endpoint_auth_methods_supported": ["none"],
"scopes_supported": [security.MCP_SCOPE],
},
headers={"Cache-Control": "public, max-age=3600"},
)
@app.get("/.well-known/jwks.json", include_in_schema=False, tags=["oauth"])
def jwks() -> JSONResponse:
"""The public half of the MCP signing key."""
return JSONResponse(
content=security.public_jwks(),
headers={"Cache-Control": "public, max-age=3600"},
)
# Mounted last, and at the root: the SDK serves both /mcp and the protected
# resource metadata that has to sit beside it, so mounting under /mcp would put
# that metadata somewhere no client looks for it.
if settings.MCP_ENABLED:
from fluksio.mcp.http import build_http_app
app.mount("/", build_http_app(app))