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

backend/app/logsink.py

@@ -362,6 +362,7 @@ def serialize(row: LogEvent) -> dict:
         "request_id": row.request_id,
         "user_id": row.user_id,
         "job_id": row.job_id,
+        "run_id": row.run_id,
         "debug_session_id": row.debug_session_id,
         "version": row.version,
     }