@@ -229,7 +229,7 @@ We also have a dashboard specifically for monitoring AI features: [Create: Code
#### Issue identification process
1.Every week we check the kibana and grafana dashboards listed above
1.If the 7-day error budget for the past week is red, we create an investigation issue to identify the root cause ([example](https://gitlab.com/gitlab-org/gitlab/-/issues/584137))
2. If we identify an endpoint or worker that contributes significantly to the error budget, we create an issue (if not created already) and label it based on our [severity](/handbook/product-development/how-we-work/issue-triage/#severity) and [priority](/handbook/product-development/how-we-work/issue-triage/#priority) criteria
- If an issue is already created, check whether the severity/priority needs to be updated
3. Performance issues are surfaced during planning automatically using a dedicated GLQL view, to priorize them accordingly