Peg monitoring L3: GraphQL oracle-events alert consumer
Open
Nobody has claimed this yet.
enhancement
- Dominant language
- Python
- Stars
- 13
- Forks
- 13
- Avg merge
- 1d 9h
- Merged PRs (30d)
- 19
Description
Context
Layer 3 (consumer side). Reads the Chainlink AnswerUpdated rows indexed by the Envio indexer (issue in chain-events/yearn-indexing-test) and turns anomalies into alerts. Mirrors the existing Envio→Telegram pattern.
Scope
- New script (mirror
protocols/timelock/timelock_alerts.py) queryingENVIO_GRAPHQL_URLfor recent rounds per feed. - Detect: large round-over-round jumps, missed-heartbeat gaps, and sequence anomalies. Alert via
utils/alert.pywith per-asset channel routing from the shared registry. - De-dupe across runs via the cache (same pattern as
timelock_alerts.py). - Add to the hourly (or 10-min) profile in
automation/jobs.yaml.
Acceptance criteria
- Given indexed rounds, anomalies produce alerts; reruns do not re-alert on the same round.
References
protocols/timelock/timelock_alerts.py,protocols/yearn/alert_large_flows.py(both useENVIO_GRAPHQL_URL).- Indexer issue:
chain-events/yearn-indexing-test. - Foundation issue (shared registry for routing).
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading protocols/timelock/timelock_alerts.py and protocols/yearn/alert_large_flows.py, then inspect automation/jobs.yaml and the shared alert registry references. Use the indexed rounds from ENVIO_GRAPHQL_URL to verify anomaly detection and run the relevant monitoring profile; done means anomalies alert through utils/alert.py and reruns do not alert for the same round.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- graphql, python
- Domain
- observability
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 55/100