Monitor console errors, network requests, performance metrics, and visual layout after deployment.
npx skills add https://github.com/himes19/pulsevolt-infra --skill canary-himes19
Please help me install this Agent Skill. Skill: canary Source: https://github.com/himes19/pulsevolt-infra/tree/main/skills/gstack/canary Command: npx skills add https://github.com/himes19/pulsevolt-infra --skill canary-himes19
Post-deploy monitoring helps catch issues that only appear under real user traffic, including errors, performance regressions, and visual regressions.
Run the canary after deployment to start a 30-minute monitoring loop that checks for console errors, network failures, and performance changes.
High-intent search queries and answers about installing and using this skill.
Post-deploy anomaly detection catches issues appearing under real user traffic by monitoring console errors, network failures, and performance regressions within a 30-minute window after deployment.
Run post-deploy health checks by starting a 30-minute monitoring loop that exercises 2-3 critical flows, checking console errors, network requests, performance metrics, and visual layout every 2-5 minutes.
Yes, you can monitor visual layout and network requests by operating in production-like environments with real-user traffic to detect anomalies and compare iterations against a baseline.
Detect performance regressions by running a fixed monitoring cadence that compares post-deploy iterations to a baseline, alerting when new console errors or performance drops appear in the health report.
Yes, post-deploy monitoring operates in production-like environments with real-user traffic to effectively catch issues that only appear under real load, exercising critical flows during the monitoring window.
The 30-minute post-deploy monitoring window limits detection to immediate anomalies within that timeframe, using a fixed cadence and focusing on 2-3 critical flows rather than long-term performance trends.
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