R9S operations should give platform, product, and finance teams the same view of model traffic. Monitor usage, latency, errors, and spend before increasing production traffic.
Usage dashboard
Use the R9S console to inspect:
- API call volume.
- Token consumption.
- Cost breakdowns.
- Usage by API key.
- Usage by model.
- Usage by time range.
- Usage by organization or member when applicable.
Performance metrics
Track these indicators for every production workload:
| Metric | Why it matters |
|---|---|
| Request latency | Shows end-to-end response time |
| Time to first token | Indicates interactive streaming quality |
| Error rate | Captures gateway and upstream failures |
| Retry rate | Shows provider instability or aggressive client behavior |
| Throughput | Measures capacity and demand |
| Token volume | Explains cost and model load |
| Cache usage | Shows whether repeated work is being avoided |
Segment metrics by endpoint, model, API key, route, channel, region, and application attribution.
Log query
Use detailed logs for debugging and audit workflows. At minimum, logs should let you correlate:
- Request ID.
- Timestamp.
- API key or token ID.
- Model.
- Endpoint.
- Status code.
- Latency.
- Input and output token counts.
- Channel or provider path.
- Retry and fallback decisions.
Do not log sensitive prompts or responses unless your organization explicitly allows that data handling pattern.
Alerting
Create alerts for:
- Error rate spikes.
- Sustained latency regression.
- Streaming time-to-first-token regression.
- Unexpected cost increase.
- Quota or balance exhaustion.
- Fallback activation above the expected baseline.
- Authentication failures that may indicate expired, leaked, or revoked keys.
Retry behavior
Retry transient 429 and 5xx responses with exponential backoff and jitter. Keep retry limits conservative because AI requests can be expensive and slow.
Recommended client behavior:
- Retry only idempotent or safely repeatable requests.
- Use request timeouts.
- Add jitter to avoid synchronized retry storms.
- Stop retrying once the user-visible operation is no longer useful.
- Log the final attempt count.
Cost operations
Use usage records to track:
- Cost by model.
- Cost by API key.
- Cost by app attribution.
- Cost by organization or user.
- Cached-token savings.
- Daily or monthly burn rate.
Set budgets and alerts before a new service reaches primary traffic.
Incident workflow
When a production issue occurs:
- Identify the affected endpoint, model, region, and API key.
- Compare error rate, latency, and fallback activity against the previous baseline.
- Inspect logs by request ID.
- Reduce traffic or adjust the route if the issue is isolated to one upstream path.
- Roll back model or route changes when compatibility or quality regresses.
- Record the incident with request examples, timeline, impact, and mitigation.