Platform Reliability
Spot stalled jobs and retry failed work without creating duplicate clips or posts.
The problem
A job can stall even when each service looks healthy. Retrying it blindly can create a second clip or post.
How NNW catches stalled jobs
Workers report progress so the platform can spot stalled jobs and retry them safely.
Treat compute, storage, and quotas as finite.
What it does
Detect stalled work, not just dead servers
Notice when an end-to-end media job has stopped moving.
How it works
Compare expected work with heartbeat and watchdog progress.
Lifecycle states make a stalled handoff observable even if a health endpoint still responds. An operator can intervene before an unnoticed backlog grows.
Limit Some third-party faults still need human diagnosis.
Bound repeated or expensive work
Keep finite compute, storage, and API quotas usable.
How it works
Use locks, cooldowns, priority scheduling, and reuse of valid results.
Concurrency is limited and archive preservation receives priority over replaceable indexing. One noisy job cannot silently consume the entire operating budget.
Limit Bounded capacity means later work may wait.
Recover without duplicating side effects
Resume after a worker restart or interrupted deploy.
How it works
Reconcile durable job identity and state before a retry or external action.
Idempotent boundaries keep the same clip, archive, or upload from being created twice. Recovery is a controlled transition rather than a blind replay.
Limit The public record intentionally omits infrastructure topology, addresses, and operational paths.
Engineering
Show decisions and tradeoffs
Supervise expected behavior
I monitor whether scheduled work and workers make progress, not only whether a process responds. A healthy endpoint can coexist with a stalled pipeline.
Tradeoff Progress checks require explicit lifecycle state.
Bound concurrency
I serialize expensive or provider-limited work and reuse valid results. Duplicate jobs consume compute, quota, and storage without improving the outcome.
Tradeoff Later work may queue instead of starting immediately.
Design retries around idempotency
I check recorded state before repeating an external side effect. A restart should not create a second clip, upload, or archive record.
Tradeoff Every integration needs durable identity and reconciliation.
Fail deployments safely
I preserve observable state and recover bounded jobs instead of clearing evidence. A deployment should not turn an operating problem into an invisible one.
Tradeoff Safe rollout and diagnosis take longer than blind replacement.
Evidence
- covered by shared operating discipline
- 6 systemsPublic-safe aggregate
- concurrency, retries, and recovery
- BoundedArchitecture behavior
- compute, storage, and provider quotas
- FiniteExplicit operating constraint
Current state and limits
- Available
- NNW uses heartbeat and watchdog supervision, locks, cooldowns, idempotent boundaries, quota-aware scheduling, deploy safeguards, and bounded recovery.
- Limits
- The platform depends on third parties and a finite operating envelope; some failures still require human diagnosis.
- Next
- Unify lifecycle evidence across all six systems without exposing sensitive topology.
- Project role
- Sole designer, engineer, and operator
- Built with
- Python · PostgreSQL · Job workers · Provider APIs · Object storage · Deployment automation