canary

You can monitor a production app after a deploy by running a continuous live-monitoring session that uses automated checks, periodic screenshots, and console tracing to detect errors, performance regressions, and visual anomalies on live URLs.

Canary deployment monitoring tracks live app health by comparing post-deploy metrics and screenshots against pre-deploy baselines to detect regressions and visual differences, ensuring you catch problems before users notice.

You can start a 10-minute post-deploy verification session by running the /canary <url> command on the specified production or canary URL to trigger automated anomaly detection and alerting.

Yes, you need a browse daemon to collect events, perform baseline comparisons, take periodic screenshots, and apply alerting thresholds for rapid anomaly detection during your post-release workflow.

Yes, you can integrate automated visual regression checks and baseline comparisons with your deployment workflow to perform rapid post-release verification and trigger alerts across multiple URLs and environments.