- bus.test.ts: 4 cases for the new onPublish hook contract - nats.test.ts: stream creation idempotency + JSON publish bridge - scheduler.test.ts: startup delay, fan-out, per-user failure isolation - ADR-0010 documents the bridge-don't-replace decision and the Todoist scheduler isolation, plus open follow-ups (#98 ml/serving consumer, #54 protobuf migration, graceful shutdown, metrics) - README/overview/services README reflect the bridged event substrate - CLAUDE.md gains a "don't nats.publish() directly" rule - .env.example documents NATS_URL + TODOIST_SYNC_INTERVAL_MS Verified in deployment 2026-04-18: api -> nats bridge connects on boot, signals + feedback streams created, scheduler tick logs "todoist sync: 1 ok, 0 failed (1 users)" within 10s. Closes #21, #22. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2.8 KiB
ADR-0010: NATS bridge over the in-process bus, and Todoist background sync
Status
Accepted — 2026-04-18
Context
ADR-0005 set protobuf + JetStream as the long-term event substrate. M1 shipped
an in-process EventEmitter-based bus with the right subjects (signals.*,
feedback.*) so the swap would be mechanical.
Two pressures pulled forward:
- ml/serving and future feature pipelines need to consume signals across process boundaries — the in-proc emitter cannot do that.
- Todoist signals were only fetched on the recommend path. Cold-cache hits added latency and a single 401/429 stalled the request that triggered it.
Decision
1. Bridge, do not replace
The Bus stays the producer. A new Bus.onPublish(hook) hook fires on every
publish. When NATS_URL is set, connectNats() registers a hook that
JSON-encodes the payload and js.publish(subject, data)s it to JetStream.
- Streams are created on startup and are idempotent:
signals(signals.>, 7-day file storage, 500k msgs) andfeedback(feedback.>, 30-day, 200k). - JetStream publish errors are caught inside the hook so an unhealthy broker cannot crash the in-process publisher or its subscribers.
- When
NATS_URLis unset,connectNatsis a no-op — local dev keeps working.
This preserves the existing bus.subscribe() contract for in-process consumers
(reward inference, ring-buffer tail for the admin event viewer) while making
events durably consumable across processes.
2. Schedule Todoist, keep on-demand as the SLA fallback
A 15-minute background scheduler (TODOIST_SYNC_INTERVAL_MS) walks every
user with tokenStatus = 'active' and calls todoistSource.fetchSignals(uid),
which in turn emits signals.task.synced. The per-request fetch in
recommender stays — when the cache is colder than 30 s it still goes to
Todoist inline, so freshness on the user's first hit of the day is unchanged.
Per-user failures are isolated with Promise.allSettled; one expired token
cannot stop the rest of the cohort. The whole tick is wrapped so a transient
SQLite error logs and skips, never crashes the API.
Consequences
- ml/serving (and any future Python consumer) can durably tail
signals.task.synced,signals.tip.served,signals.tip.feedbackfrom JetStream without coupling to the API process. - Local dev still runs without NATS; the bridge is opt-in via env.
- Wire format is JSON today (envelope per ADR-0005 not enforced yet) — see Open follow-ups.
Open follow-ups
- A ml/serving JetStream consumer for the feature pipeline (today nothing reads from JetStream — the API only writes).
- Move the wire payload to the protobuf envelope from ADR-0005 once the schema-registry CI gate (#54) lands.
- Graceful shutdown of the scheduler timer on
SIGTERM. - Per-publish failure metrics exported to the admin health view.