Async Job Engine
BullMQ-backed queue/worker pattern with idempotency keys, retry policies, dead-letter queues, and surfaced job status — built for operations to inspect.
Long-running operations (bulk imports, schedule generation, QA cycle close-outs, exports) need to be reliable, observable, and idempotent. FrontLine's job engine is built on BullMQ with explicit retry policies, dead-letter queues for failures that exhausted retries, and an operator-facing job inspector so your ops team can see what's running, what failed, and what's pending.
Built so operators can see what's running, what failed, and what's pending
Jobs are enqueued via a typed contract per job kind, with a required idempotency key. The worker service consumes from named queues with configured concurrency. Each job kind declares retry parameters (max attempts, backoff strategy) and timeout. Failures past retry land in a DLQ for inspection. Job state, progress percentage, and result are queryable via API. Redis runs in noeviction mode so queued jobs cannot be silently dropped under memory pressure.
What's covered out of the box
Audit-ready artifacts your reviewers can lean on
- SOC 2 Type II — availability and reliability controls
- Job retry policies documented per job kind
- DLQ retention defaults to 30 days
- Operator runbooks for common failure modes
What security and compliance reviewers actually ask
What happens if a worker crashes mid-job?+
Can we see what jobs are running?+
Are job submissions audited?+
How do you handle stuck jobs?+
Run this past your security team
We share security overviews, RLS policy DDL, audit-event schemas, and SOC 2 progress on request. Book a 30-minute security review with the founders.