feat(scheduler): every background run is a durable row

What a job last did lived in the API process's memory and was gone at
every restart; the audit log kept a run only when it was manual, failed
or changed something. Now each run is a job_runs row written at its
start and its end in its own session: who started it, its outcome as
data, what it spent of the YouTube quota (quota_events.job_run_id) and
the lines it logged (log_events.run_id, filterable in the log console).

- a run a stopped process left open is marked interrupted at startup
- "run now" is a one-shot job on the scheduler, which now always starts
  (interval jobs only with SCHEDULER_ENABLED); the manual actor is reset
  after the run, since pool threads are reused
- the dashboard's last run comes from job_runs, so it survives a deploy
- runs leave the audit log: migration 0109 moves the old job_run rows
  over (and back on downgrade); the audit page's run folding goes
- job_run_retention_days (default 30) prunes old runs in audit_gc
This commit is contained in:
2026-10-17 23:08:55 +02:00
parent 4b1f6d7ec2
commit 45c0ee7d58
31 changed files with 870 additions and 489 deletions
+11 -3
View File
@@ -16,7 +16,7 @@ from sqlalchemy.dialects.postgresql import insert as pg_insert
from sqlalchemy.engine import CursorResult
from sqlalchemy.orm import Session
from app import sysconfig
from app import logs, sysconfig
from app.db import SessionLocal
from app.models import ApiQuotaUsage, QuotaEvent
@@ -204,6 +204,14 @@ def record_usage(units: int) -> None:
)
with SessionLocal() as qs:
qs.execute(stmt)
# Audit detail: who/what spent it (per-user attribution; NULL actor = system).
qs.add(QuotaEvent(user_id=_actor_id.get(), action=_action.get(), units=units))
# Audit detail: who/what spent it (per-user attribution; NULL actor = system), and the
# background run it belongs to, so the run's row can say what it cost.
qs.add(
QuotaEvent(
user_id=_actor_id.get(),
action=_action.get(),
units=units,
job_run_id=logs.current_run_id(),
)
)
qs.commit()