canary

Post-deploy canary monitoring captures periodic screenshots of configured pages, compares them against stored baselines, and raises alerts when it detects performance regressions or page failures.

Baseline-driven canary monitoring uses a browse daemon to capture initial page screenshots, error states, and performance metrics, then continuously compares live production pages against these stored baselines to detect anomalies.

You can set up an automated canary check by configuring your target URLs and alert tuning parameters, then running the monitoring daemon to continuously watch for new console errors during a specified duration window.

Yes, you can tune alert sensitivity, specify monitoring duration, and target specific production pages to ensure anomaly alerts match the exact criteria needed to stop bad releases quickly.

Yes, this canary monitoring operates entirely locally by using its own browse daemon to capture baselines and storing all monitoring results locally without requiring external dependencies or third-party observability platforms.

Automated baseline comparison is the best way to detect page failures, as it periodically captures screenshots of live pages and raises alerts automatically when visual anomalies or new errors appear, eliminating manual review.