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FabledCurator/backend/app/services/worker_control.py
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feat: a saturated lane can grow itself, within the cap the operator set (4297)
Milestone 422 step 7 — the one sweep in this milestone that decides rather
than obeys, so it is off until a lane is opted in, bounded by the operator's
cap, floored at the operator's value, and it reports every decision including
the ones where it did nothing.

Growth needs BOTH halves: all slots busy AND a backlog. Depth alone means
celery is about to pick those up and growing would add idle children (#1253
is that bug in the GPU agent); saturation alone means the lane is busy with
exactly as much work as exists. The backlog is depth PLUS reserved, because
celery prefetches and LLEN reads 0 while a worker holds thirty tasks in
memory — the case an LLEN-only autoscaler misses entirely, and the reason
step 2 plumbed `reserved` through.

The two sweeps had to be taught not to fight. The reconcile drives every
lane to its stored slots every five minutes, which would have reverted each
grow on the next tick: grow, revert, grow, revert, forever. For an
autoscaling lane the stored value is now a FLOOR — restored when a lane
falls below it, never taken back above it.

The operator's "a task that runs for x concurrent time" idea stays a UI
warning rather than a trigger: a long task does not finish sooner because
the lane gained a slot, so scaling on it would spend memory to change
nothing. Read from `task_run` on our own wall clock, not celery's
`time_start`, which is the WORKER's monotonic clock and would produce a
duration that is meaningless in the direction that matters — plausible.

Caught while reading it back: the first version read the stored slots as the
CURRENT pool. The autoscaler never writes that row, so every tick would have
proposed floor+1 — resizing nothing, reporting `grew` anyway (a replica
already past the target is issued no message and reports success), and
capping the lane one slot above its floor forever while claiming otherwise.
It now reads the live pool and keeps the stored value purely as the floor,
and the tests fix the two to different numbers so an equal-fixture pass
cannot hide it again.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LVjrnpQjRgHdvq95rASoiR
2026-09-22 10:05:43 -04:00

779 lines
33 KiB
Python

"""Read and change a lane's live pool, over the broker.
Milestone 422 step 2. The half of the milestone that does something.
## No docker socket is involved, and that is the point
Milestone 365 put "acting on the state" out of scope because restarting a
dead worker needs a docker socket the web container deliberately does not
have. That is true of RESTARTING a container. It is not true of changing how
much work a RUNNING worker does: celery's remote control sends a message over
the broker and the worker resizes its own pool. Same Redis the app already
uses, no new privilege, no new surface.
pool_grow / pool_shrink how many slots a lane runs
add_consumer / cancel_consumer whether it consumes its queues at all
The operator ruled the socket out independently (2026-09-22: *"this feature
is a very invasive idea in my mind and I'd like to avoid it"*), and nothing
here raises the question.
## The setting is PER PROCESS, not per lane total
`pool_grow(n, destination=[...])` adds n slots to EACH destination it names.
While the stack still runs several containers per lane — the operator's
production `worker` is `replicas: 2` — a single delta applied to a lane's
total would be wrong for every replica.
So `slots` means what `CELERY_CONCURRENCY` means: the pool size of one
process. The reconcile below drives EACH replica to that number
independently, computing its own delta from that replica's current pool, so
replicas that have drifted apart (one restarted, one was grown) converge
rather than being moved in lockstep from a shared baseline.
After step 5 there is one process per lane and the distinction disappears.
It matters now, and getting it wrong now would be invisible — the totals
would simply be double what the UI claimed.
## Why reserved() is read alongside the queue depth
Celery PREFETCHES: a worker pulls more messages than it can run and holds
them in memory. Those have already left the Redis list, so `LLEN` — which is
what `/api/system/activity/queues` reports — can read 0 while thirty tasks
are waiting inside a worker. Any judgement about backlog that uses only LLEN
under-reports, which matters for the UI and is disqualifying for step 7's
autoscaler.
"""
from __future__ import annotations
import asyncio
import logging
from dataclasses import dataclass, field
from datetime import UTC, datetime
from sqlalchemy import func, select
from sqlalchemy.ext.asyncio import AsyncSession
from ..models import TaskRun, WorkerLane
from .worker_lanes import LANES, LANES_BY_QUEUE_KEY, Lane, derived_ceiling
log = logging.getLogger(__name__)
# celery control is a broker round trip on a request path, so it gets a
# deadline (rule 156) — the same reasoning and the same budget as
# service_roster's inspect. A broker that stopped answering must make this
# report "not present", which is true, rather than hang the page.
CONTROL_TIMEOUT_SECONDS = 2.0
@dataclass
class LaneLiveState:
"""What `celery inspect` says about one lane right now.
`present=False` is NOT "zero slots" — it is "nothing answered". A lane
whose worker is restarting, or whose broker is unreachable, must read as
unknown rather than as stopped: an unswept absence is not a verdict
(snippet #3969). The reconcile in step 3 skips an absent lane rather than
correcting it, which is only safe because this distinction is kept.
"""
present: bool = False
replicas: int = 0
active: int = 0
reserved: int = 0
hostnames: list[str] = field(default_factory=list)
# The queues this lane is actually consuming right now, across replicas.
# Distinct from the lane's CONFIGURED queues: `cancel_consumer` stops a
# worker consuming one without changing what it was started with, which
# is how `enabled=false` is implemented. The reconcile needs this to tell
# "already disabled" from "needs disabling" — without it, it would re-send
# add_consumer for every queue on every tick forever (lesson #4183).
consuming: set[str] = field(default_factory=set)
# Pool size PER HOSTNAME, not aggregated. The resize below computes each
# replica's own delta from its own current pool, so replicas that have
# drifted apart converge instead of being moved in lockstep from a shared
# baseline — which is what an aggregate here would silently reintroduce.
pools: dict[str, int] = field(default_factory=dict)
@property
def pool(self) -> int | None:
"""One number for the UI. `max` rather than a sum: `slots` means the
pool size of ONE process (see the module docstring), so the largest
replica is the honest answer to "what is this lane set to". None when
no replica reported — unknown, never zero."""
return max(self.pools.values()) if self.pools else None
@property
def capacity(self) -> int:
"""Total slots across replicas — how many tasks this lane can run at
once. Distinct from `pool`, and the two must not be confused: `pool`
is the DIAL (one process's size, what grow/shrink move), `capacity` is
the CAPABILITY. Asking "is this lane saturated" compares `active`,
which is summed across replicas, against this — against `pool` it
would call two half-busy replicas of 4 saturated at 4 active."""
return sum(self.pools.values())
def _lane_for_queues(queues: tuple[str, ...]) -> Lane | None:
return LANES_BY_QUEUE_KEY.get(tuple(sorted(queues)))
def inspect_lanes_sync() -> dict[str, LaneLiveState]:
"""Live state per lane name. Sync — callers wrap in asyncio.to_thread.
Never raises. Every lane is present in the result; ones nothing answered
for carry `present=False`, so a caller cannot accidentally read a missing
lane as an empty one by iterating only what came back.
"""
out = {lane.name: LaneLiveState() for lane in LANES}
try:
from ..celery_app import celery as celery_app
insp = celery_app.control.inspect(timeout=CONTROL_TIMEOUT_SECONDS)
active_queues = insp.active_queues() or {}
stats = insp.stats() or {}
active = insp.active() or {}
reserved = insp.reserved() or {}
except Exception:
log.warning("worker_control: celery inspect failed", exc_info=True)
return out
for hostname, queues in active_queues.items():
lane = _lane_for_queues(tuple(q["name"] for q in queues))
if lane is None:
# A deployment slicing CELERY_QUEUES differently. Reported by the
# roster under its raw queue list; it simply has no lane row to
# control, which is honest rather than an error.
continue
state = out[lane.name]
state.present = True
state.replicas += 1
state.hostnames.append(hostname)
state.active += len(active.get(hostname, []))
state.reserved += len(reserved.get(hostname, []))
state.consuming.update(q["name"] for q in queues)
# `pool.max-concurrency` is the number pool_grow/pool_shrink move and
# the number the UI shows. Absent on a worker whose stats did not
# answer, which leaves pool=None — unknown, not zero.
pool = (stats.get(hostname) or {}).get("pool", {}).get("max-concurrency")
if isinstance(pool, int):
state.pools[hostname] = pool
for state in out.values():
state.hostnames.sort()
return out
def set_lane_slots_sync(
lane: Lane, target: int, live: LaneLiveState | None = None,
) -> tuple[bool, str | None]:
"""Drive every replica of `lane` to `target` slots. Returns (applied, err).
Per-replica deltas rather than one shared delta: see the module docstring.
A replica already at the target is issued nothing at all, which is what
makes step 3's periodic reconcile converge instead of re-sending a grow of
zero forever (lesson #4183 — an enforcer without a reachable fixed point
re-does its own work every tick).
`applied=False` is not a failure of the SETTING. The caller has already
stored the value; this says only that the live push did not land, and the
reconcile will carry it when the lane answers again.
"""
try:
from ..celery_app import celery as celery_app
if live is None:
live = inspect_lanes_sync()[lane.name]
if not live.present:
return False, "lane is not running"
if not live.pools:
return False, "worker did not report its pool size"
control = celery_app.control
unreported = [h for h in live.hostnames if h not in live.pools]
for hostname, current in live.pools.items():
delta = target - current
if delta > 0:
control.pool_grow(delta, destination=[hostname])
elif delta < 0:
control.pool_shrink(-delta, destination=[hostname])
if unreported:
# Resized what could be resized, and said which could not. Silence
# here would leave a replica running at a size the UI claims it is
# not, with nothing anywhere recording the gap.
return False, f"no pool size reported by {', '.join(sorted(unreported))}"
return True, None
except Exception as exc: # noqa: BLE001 — reported, never raised at a caller
log.warning("worker_control: could not resize %s", lane.name, exc_info=True)
return False, str(exc)
def set_lane_enabled_sync(
lane: Lane, enabled: bool, live: LaneLiveState | None = None,
) -> tuple[bool, str | None]:
"""Start or stop `lane` consuming its queues, without killing the process.
`cancel_consumer` rather than a shutdown: a stopped consumer keeps its
worker alive and answering `inspect`, so a disabled lane stays visible and
can be turned back on. A killed worker would read as absent, which is the
same signal as a crash — and the whole point of the roster (#365) is that
those two must not look alike.
"""
try:
from ..celery_app import celery as celery_app
if live is None:
live = inspect_lanes_sync()[lane.name]
if not live.present:
return False, "lane is not running"
control = celery_app.control
for queue in lane.queues:
if enabled:
control.add_consumer(queue, destination=live.hostnames)
else:
control.cancel_consumer(queue, destination=live.hostnames)
return True, None
except Exception as exc: # noqa: BLE001
log.warning(
"worker_control: could not %s %s",
"enable" if enabled else "disable", lane.name, exc_info=True,
)
return False, str(exc)
# --- the settings half, which is async ----------------------------------------
#
# Sync celery control above, async DB below, in one module. Same split
# `service_roster` already runs (`_inspect_celery_sync` beside `touch_service`)
# — the boundary is the transport, not the concern, and "control the workers"
# is one concern.
async def _rows_by_name(session: AsyncSession) -> dict[str, WorkerLane]:
"""Every lane's row, creating any that are missing from its LANES defaults.
Self-heals rather than depending on a migration having run for a lane
added later: alembic 0103 seeded the four that existed on 2026-09-22, and
a fifth added to LANES afterwards gets its row the first time anything
asks. Without this, a new lane would read as absent and the UI would
simply not show it.
"""
rows = {
row.name: row
for row in (await session.execute(select(WorkerLane))).scalars()
}
missing = [lane for lane in LANES if lane.name not in rows]
for lane in missing:
row = WorkerLane(
name=lane.name,
slots=lane.default_slots,
slots_cap=lane.default_slots_cap,
enabled=lane.default_enabled,
autoscale=lane.default_autoscale,
)
session.add(row)
rows[lane.name] = row
if missing:
await session.commit()
return rows
async def lane_view(session: AsyncSession) -> list[dict]:
"""Every lane: what is configured, what is live, what it may grow to.
One call rather than making the UI join three sources. `pending` is the
honest backlog — Redis depth PLUS reserved — because celery prefetches and
LLEN alone reads 0 while a worker holds tasks in memory.
"""
rows = await _rows_by_name(session)
live = await asyncio.to_thread(inspect_lanes_sync)
depths = await asyncio.to_thread(_queue_depths_sync)
oldest = await _oldest_running_by_queue(session)
now = datetime.now(UTC)
out = []
for lane in LANES:
row = rows[lane.name]
state = live[lane.name]
# None for a queue the broker did not answer for, which must not be
# silently summed as zero — an unknown depth is not an empty one.
known = [depths.get(q) for q in lane.queues]
depth = sum(d for d in known if d is not None) if any(
d is not None for d in known
) else None
out.append({
"name": lane.name,
"display_name": lane.display_name,
"queues": list(lane.queues),
"slots": row.slots,
"slots_cap": row.slots_cap,
"ceiling": derived_ceiling(lane),
"enabled": row.enabled,
"autoscale": row.autoscale,
"memory_bound": lane.memory_bound,
"optional": lane.optional,
# What enabling this lane will download, so the UI can say WHICH
# model and how big BEFORE the switch is thrown rather than after
# a multi-GB fetch has started. `measured` travels with the
# numbers: the card must not present an estimate as a fact.
"models": [
{
"repo": m.repo,
"download_bytes": m.approx_download_bytes,
"resident_bytes": m.approx_resident_bytes,
"measured": m.measured,
}
for m in lane.models
],
"live": {
"present": state.present,
"replicas": state.replicas,
"pool": state.pool,
"active": state.active,
"reserved": state.reserved,
},
"queue_depth": depth,
"pending": None if depth is None else depth + state.reserved,
# How long the oldest still-running task on this lane has been
# going, in minutes. The operator asked for a trigger here — grow
# a lane whose tasks run past some duration — and it stayed a
# REPORT: a long task does not finish sooner because the lane
# gained a slot, so scaling on it would spend memory to change
# nothing. Shown so they can see a lane wedged on one slow job,
# which is the genuinely useful half of the idea.
"oldest_running_minutes": _minutes_since(
min(
(oldest[q] for q in lane.queues if q in oldest),
default=None,
),
now,
),
})
return out
async def _oldest_running_by_queue(session: AsyncSession) -> dict[str, datetime]:
"""When the longest-running unfinished task on each queue started.
Read from `task_run`, which is OUR OWN table on OUR OWN wall clock, and
deliberately not from celery's `inspect active()`. Those entries carry a
`time_start` taken from the WORKER's `time.monotonic()` — a clock with an
arbitrary origin per process. Subtracting it from this process's wall
clock produces a number that looks like a duration and is meaningless, and
it would be meaningless in the direction that matters: plausible.
`task_run` also already carries the per-queue staleness thresholds the
recovery sweep uses, so a row still `running` here is one the system
itself considers legitimately in flight rather than abandoned.
"""
result = await session.execute(
select(TaskRun.queue, func.min(TaskRun.started_at))
.where(TaskRun.status == "running", TaskRun.finished_at.is_(None))
.group_by(TaskRun.queue)
)
return {queue: started for queue, started in result if started is not None}
def _minutes_since(started: datetime | None, now: datetime) -> int | None:
"""Whole minutes, or None when nothing is running. Never negative: a row
written by a container whose clock is a few seconds ahead must read as 0
rather than as a task that starts in the future."""
if started is None:
return None
return max(0, int((now - started).total_seconds() // 60))
def _queue_depths_sync() -> dict[str, int | None]:
"""Redis LLEN per queue. None for one that did not answer — see lane_view.
Sync; the caller threads it. A per-queue try/except so one bad queue does
not cost the whole report, matching `api/system_activity._read_queues_sync`.
"""
import redis
from ..config import get_config
out: dict[str, int | None] = {}
try:
client = redis.Redis.from_url(get_config().celery_broker_url)
except Exception:
log.warning("worker_control: no broker for queue depths", exc_info=True)
return {q: None for lane in LANES for q in lane.queues}
for lane in LANES:
for queue in lane.queues:
try:
out[queue] = int(client.llen(queue))
except Exception: # noqa: BLE001 — a hiccup must not break the UI
out[queue] = None
return out
class LaneUpdateRefused(ValueError):
"""A requested value is outside what the lane may hold. Carries the reason
the UI shows — a greyed control with no explanation reads as a bug."""
async def set_lane(
session: AsyncSession,
lane: Lane,
*,
slots: int | None = None,
slots_cap: int | None = None,
enabled: bool | None = None,
autoscale: bool | None = None,
) -> dict:
"""Store the operator's choice, then push it to the running lane.
BOTH, in one call, and the order matters. `pool_grow`/`pool_shrink` are
not durable — a restart drops every lane back to its env concurrency — so
a UI that only pushed would have its setting evaporate on the next deploy
with nothing to show for it (lesson #4202: the live change does not
survive, and nothing says so). Storing alone would be a number that
describes nothing until something restarts.
A failed PUSH is not a failed setting. The value is saved either way and
step 3's reconcile carries it when the lane answers again; the result says
`applied: false` with a reason so the UI can say "saved, not yet live"
rather than "that didn't work".
"""
rows = await _rows_by_name(session)
row = rows[lane.name]
new_cap = row.slots_cap if slots_cap is None else slots_cap
new_slots = row.slots if slots is None else slots
new_enabled = row.enabled if enabled is None else enabled
new_autoscale = row.autoscale if autoscale is None else autoscale
ceiling = derived_ceiling(lane)
if new_cap < 0 or new_slots < 0:
raise LaneUpdateRefused("slots and cap cannot be negative")
if new_cap > ceiling:
raise LaneUpdateRefused(
f"cap {new_cap} is above what this container can hold "
f"({ceiling} for {lane.display_name})"
)
if new_slots > new_cap:
raise LaneUpdateRefused(f"slots {new_slots} is above the cap {new_cap}")
row.slots_cap = new_cap
row.slots = new_slots
row.enabled = new_enabled
row.autoscale = new_autoscale
await session.commit()
applied, error = True, None
if enabled is not None:
applied, error = await asyncio.to_thread(
set_lane_enabled_sync, lane, new_enabled,
)
if applied and slots is not None:
applied, error = await asyncio.to_thread(set_lane_slots_sync, lane, new_slots)
# Enabling a lane that needs models is what triggers the fetch (milestone
# 422 step 6). Never at boot: that made every start of the ML role reach
# HuggingFace for ~3.5GB, and rule 164 permits a runtime fetch only for a
# feature that is optional and clearly OFF.
#
# Only when the lane actually came on — `enabled is True` rather than
# `new_enabled`, so re-saving slots on an already-enabled lane does not
# re-enqueue. And only when the consumer change landed: enqueueing a task
# onto a queue nothing is consuming would leave it pending with no
# explanation until the lane returns.
fetching = False
if enabled is True and lane.models and applied:
fetching = _enqueue_model_fetch()
return {
"name": lane.name,
"slots": row.slots,
"slots_cap": row.slots_cap,
"ceiling": ceiling,
"enabled": row.enabled,
"autoscale": row.autoscale,
"applied": applied,
"apply_error": error,
# Tells the card to say a download has started rather than leaving the
# operator to wonder why a freshly enabled lane is busy.
"fetching_models": fetching,
}
def _enqueue_model_fetch() -> bool:
"""Queue the model download. Returns whether it was accepted.
Import inside the function: `backend.app.tasks.ml` pulls in torch, and web
must not pay that import cost on a module that every settings request
touches.
Never raises. A broker that will not take the task is worth reporting, but
the SETTING has already been stored and the lane is already enabled — so
failing the whole request here would roll back nothing and tell the
operator their change did not happen when it did.
"""
try:
from ..tasks.ml import ensure_models
ensure_models.delay()
return True
except Exception: # noqa: BLE001 — reported, never raised at a caller
log.warning("worker_control: could not enqueue the model fetch", exc_info=True)
return False
def reconcile_lanes_sync(
desired: dict[str, tuple[int, bool]],
autoscaling: frozenset[str] = frozenset(),
) -> dict:
"""Drive every RUNNING lane to its stored slots and enabled flag.
`desired` is lane name -> (slots, enabled), read from the database by the
caller. `autoscaling` names the lanes the autoscaler is allowed to move.
## For an autoscaling lane the stored value is a FLOOR, not a target
Step 7's autoscaler raises a saturated lane's live pool without changing
its row — the row holds what the OPERATOR set. If this pass treated that
row as an exact target it would shrink the lane back on the very next
tick, and the two sweeps would fight forever at five-minute intervals:
grow, revert, grow, revert. That is lesson #4183's failure arriving
between two enforcers rather than inside one.
So for those lanes the target becomes `max(stored, current)` — this pass
still restores a lane that came back from a restart below what the
operator set, and never takes back what the autoscaler added. Bringing it
down is the autoscaler's job, and it does so only to that same floor. This function touches no database: the celery task that schedules
it owns the sync session, and keeping the DB out of here is what lets the
same code be called from anywhere that already knows the target.
## Why this exists at all
`pool_grow` is not durable. A worker that dies and is restarted by its
supervisor comes back at its ENV concurrency — silently below whatever the
operator set — and nothing in step 2's path would ever notice. Storing the
value made it survivable; this is what makes it actually survive.
## It must converge and then go quiet
One `inspect` for all lanes, and `set_lane_slots_sync` issues nothing at
all to a replica already at its target. So a settled system performs one
broker round trip per tick and sends no control messages — the reachable
fixed point lesson #4183 is about. An enforcer that re-sent a grow of zero
every tick would churn forever and bury a real correction in its own noise,
which is why `changed` below counts only lanes that actually moved.
## An absent lane is SKIPPED, not corrected
`present=False` means nothing answered — a worker restarting, or a broker
that is unreachable. It does NOT mean zero slots. Correcting an absence
would be drawing a conclusion from an unswept read (snippet #3969), and
here it would be worse than useless: there is nothing to send the message
to. The lane is reported as skipped and picked up on a later tick.
"""
live = inspect_lanes_sync()
changed: list[str] = []
skipped: list[str] = []
failed: dict[str, str] = {}
for lane in LANES:
target = desired.get(lane.name)
if target is None:
continue
slots, enabled = target
state = live[lane.name]
if not state.present:
skipped.append(lane.name)
continue
# Enabled first: a lane being turned on should be consuming before
# its pool is sized, so the slots it gains have work to pick up.
#
# Only when it DISAGREES. Calling this unconditionally would send
# add_consumer for every queue on every tick of a settled system —
# the exact churn lesson #4183 describes, and invisible because
# add_consumer on a queue already consumed is harmless.
consuming_all = state.consuming.issuperset(lane.queues)
if enabled != consuming_all:
ok, err = set_lane_enabled_sync(lane, enabled, live=state)
if not ok:
failed[lane.name] = err or "could not set consumers"
continue
changed.append(lane.name)
current = state.pool
# The floor, for a lane the autoscaler manages. See the docstring.
target_slots = slots
if lane.name in autoscaling and current is not None:
target_slots = max(slots, current)
if current is not None and current == target_slots:
continue
ok, err = set_lane_slots_sync(lane, target_slots, live=state)
if ok:
if lane.name not in changed:
changed.append(lane.name)
log.info(
"worker_control: %s reconciled %s -> %s slots",
lane.name, current, target_slots,
)
else:
failed[lane.name] = err or "could not resize"
return {"changed": changed, "skipped": skipped, "failed": failed}
# --- the autoscaler (step 7) --------------------------------------------------
#
# The only part of this milestone that acts without anyone asking. Everything
# above does what an operator pressed; this decides. So it is off by default,
# opted into per lane, bounded by the cap the operator set, and it reports what
# it did rather than moving numbers silently.
# ## Why these three numbers are not in Settings
#
# Rule 25 puts anything an operator might want to tune in the UI, and the
# knobs that decide what this does ARE there: whether a lane autoscales at
# all, its cap, and its floor — all DB-backed, all changeable without a
# restart. What is left here is the POLICY's internals, and exposing them
# would add four numbers per lane to a card whose whole value is being
# readable at a glance, to tune a decision the operator has a better lever
# for. If growth turns out to be too eager or too shy in practice, that is a
# reason to change these values for everyone, not to ask each operator to
# discover them.
# All slots busy AND this many tasks waiting before a lane may grow.
#
# The AND is the design. Depth with free slots means nothing — celery is about
# to pick those up, and growing the pool would add idle children. Saturation
# with an empty queue means nothing either: the lane is busy with exactly as
# much work as exists. Only both together say "there is more work than this
# lane can reach".
AUTOSCALE_BACKLOG_THRESHOLD = 10
# Grow by one slot per tick, never to the cap in one jump. A lane that is
# saturated because of one slow burst settles a slot or two above where it
# started rather than at its ceiling, and the next tick re-measures rather
# than committing to a guess made once.
AUTOSCALE_STEP = 1
# Hysteresis: shrink only when the backlog is well BELOW the grow threshold,
# not merely under it. Equal thresholds flap — one task arriving and leaving
# would grow and shrink the lane forever at the tick interval, which is
# lesson #4183's churn arriving through a different door.
AUTOSCALE_SHRINK_BELOW = 2
@dataclass
class AutoscaleDecision:
"""What the autoscaler did to one lane, and why — in the operator's terms.
A reason string on every outcome including "nothing", because an
autoscaler that only speaks when it acts is one nobody can debug when it
does not.
"""
lane: str
action: str # "grew" | "shrank" | "held"
slots: int
reason: str
def autoscale_lanes_sync(
lanes: dict[str, tuple[int, int, bool]],
) -> list[AutoscaleDecision]:
"""Decide and apply one round of autoscaling.
`lanes` is name -> (slots_cap, configured_slots, autoscale_on), read from
the database by the caller — this function touches no database, for the
same reason `reconcile_lanes_sync` does not.
## What is current, and what is the floor
The value this moves is the LIVE pool, read from `inspect`. The stored
`configured_slots` is what the operator set and is only the FLOOR: growth
goes above it and a shrink returns to it, never below.
The two are deliberately not the same number, and reading the stored value
as "current" is the mistake that makes this function useless in a way no
unit test of a single tick would show. The autoscaler never writes the
row, so the stored value never moves; a tick that computed `stored + 1`
would propose the same target forever, cap the lane one slot above the
floor no matter the load, and — because resizing a replica already at the
target issues nothing and reports success — claim `grew` on every tick
while nothing changed. Lesson #4183's non-convergence, arriving with a
success message attached.
So: `current = state.pool`, `configured` is the floor, and both `grew` and
`shrank` mean the live pool actually moved.
"""
live = inspect_lanes_sync()
depths = _queue_depths_sync()
out: list[AutoscaleDecision] = []
for lane in LANES:
target = lanes.get(lane.name)
if target is None:
continue
cap, configured, on = target
if not on:
continue
state = live[lane.name]
if not state.present or state.pool is None:
# Nothing answered. Not "idle" — unknown, and a decision drawn
# from an unswept read is exactly what snippet #3969 warns about.
# `configured` is reported because there is no live number to
# report; it is what the lane will come back at.
out.append(AutoscaleDecision(
lane.name, "held", configured, "lane is not answering",
))
continue
current = state.pool
known = [depths.get(q) for q in lane.queues]
if all(d is None for d in known):
out.append(AutoscaleDecision(
lane.name, "held", current, "queue depth unavailable",
))
continue
backlog = sum(d for d in known if d is not None) + state.reserved
# Against CAPACITY, not against the dial: `active` is summed across
# replicas, so comparing it to one replica's pool size would call two
# half-busy replicas of 4 saturated at 4 active and grow a lane that
# has idle slots.
saturated = state.active >= state.capacity > 0
busy = backlog >= AUTOSCALE_BACKLOG_THRESHOLD
if saturated and busy and current < cap:
new = min(cap, current + AUTOSCALE_STEP)
ok, err = set_lane_slots_sync(lane, new, live=state)
out.append(AutoscaleDecision(
lane.name, "grew" if ok else "held", new if ok else current,
f"{backlog} waiting and all {state.capacity} slots busy"
if ok else f"could not grow: {err}",
))
elif saturated and busy:
# At the cap with work still waiting. Said out loud rather than
# held silently: this is the operator's own ceiling doing its job,
# and it is the moment they would want to know they set it.
out.append(AutoscaleDecision(
lane.name, "held", current,
f"{backlog} waiting but the cap is {cap}",
))
elif current > configured and backlog <= AUTOSCALE_SHRINK_BELOW:
new = max(configured, current - AUTOSCALE_STEP)
ok, err = set_lane_slots_sync(lane, new, live=state)
out.append(AutoscaleDecision(
lane.name, "shrank" if ok else "held", new if ok else current,
f"backlog cleared, back toward {configured}"
if ok else f"could not shrink: {err}",
))
else:
# The fixed point. A settled lane sends nothing and says so —
# the tick is one inspect and one LLEN sweep, no control messages.
out.append(AutoscaleDecision(
lane.name, "held", current,
f"{backlog} waiting, {state.active} busy",
))
return out