Everything that goes wrong already travelled the event bus, but the only
subscriber was the editor's websocket — so a flow quarantined at three in
the morning was invisible until someone opened the browser.
An alert manager now watches the same bus and forwards failures to ntfy,
email or a webhook. Most of what it does is decline to send: the same
node failing every second is one alert with a count of what followed, a
connection flapping up and down is muted until it settles, and nothing
gets past ten notifications an hour. Verified against a live instance —
six identical failures produced one alert carrying the real traceback
message.
Channels and rules are configured through the API, with a test send so a
channel can be proven before anything depends on it.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011LF61rxW1FG5YCD2J9YqjY
Execution was fire-and-forget: an MQTT message or webhook ran a cascade
on a ThreadPoolExecutor built for that one wave, and an engine that died
halfway through simply lost whatever was in flight. Concurrent triggers
each built their own pool, so load meant unbounded threads.
Every external trigger is now journaled to a Redis Streams queue before
anything runs, and acknowledged only once its cascade finishes. A
consumer thread drives cascades on one long-lived pool while node bodies
run on another, so a cascade cannot starve the nodes it is waiting for.
A reaper reclaims what a dead consumer never acknowledged — verified end
to end: work journaled while the engine was stopped runs on restart, and
work abandoned mid-cascade comes back as a second delivery.
At-least-once needs a guard, so nodes that reach outside are marked
non-idempotent and skipped on a redelivery they already completed.
Without Redis the queue degrades to an in-memory one that does not
pretend to be durable, and interactive callers still run inline.
Also fixes two things this turned up: a delay node was sleeping on a
worker thread, where a handful of them could occupy the whole pool, and
webhooks 404'd whenever MCP was enabled because the app mounted at /
answered first for every path.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011LF61rxW1FG5YCD2J9YqjY
Logic nodes are pure functions with no state handle, but real automations
count things and remember the last reading. The shape for that is a
message a node both reads and writes: the graph already declines to make
a node depend on itself, so this worked by accident. It is now defined,
tested, and checked — a node that is the only writer of a message it
reads is told at edit time that it needs a starting value, rather than
silently never running.
Feeding a value back between two nodes was still a cycle, and rejected.
An input can now be marked non-triggering: read when the node runs, never
the reason it runs, and no dependency either way. That is what a back
edge actually means.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011LF61rxW1FG5YCD2J9YqjY
nodes.py had grown to 2k lines holding every integration behind a single
blanket mypy exemption. It is now a package split by the outside world
each node talks to, so the exemption shrinks to the four integration
modules; base and mlp are type-checked, which turned up a dozen missing
annotations.
The senders opened a fresh connection — and, in the MQTT case, a fresh
thread pool and event loop — for every single message. HTTP senders now
share one pooled client, and a publisher holds one broker connection for
its lifetime, fed from a bounded queue that drops the oldest value when
the broker cannot keep up.
An HTTP sender also no longer trips over a JSON reply that is not an
object: outputs are keyed by port, so a bare scalar is a valid reply with
nothing to publish.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011LF61rxW1FG5YCD2J9YqjY
A node's subscription, schedule or poll loop was a bare asyncio task: one
that raised outside its own retry handling was simply gone, and the node
went on being listed as running while nothing listened any more.
Those loops now run under a supervisor that restarts them with a growing
delay and quarantines a flow that burns through five restarts in five
minutes — a flow crash-looping every second is worse than one that is
visibly stopped, and the dashboard can now say which.
The MQTT subscription loses its private five-second reconnect in the
process: one backoff policy per socket, and it belongs to the supervisor.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011LF61rxW1FG5YCD2J9YqjY
The API image ran four uvicorn workers, and each one built a full flow
controller — four sets of MQTT subscriptions, cron ticks and webhooks.
Runs one worker now; scaling out is the worker split, not more processes.
Adds a loop-lag watchdog and a deep /utils/health/ that fails when the
event loop is wedged or Redis is unreachable, the two failure modes a
process-alive check never sees. Autoheal restarts on that signal, behind
a compose profile because it mounts the Docker socket.
The private user-seeding routes now need an explicit opt-in rather than
just ENVIRONMENT=local, so a deployment that kept the default never
exposes them.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011LF61rxW1FG5YCD2J9YqjY
