Monitor live web applications for console errors and page failures post-deployment.
npx skills add https://github.com/AkbarDevop/ayah-studio --skill canary-akbardevop
Please help me install this Agent Skill. Skill: canary Source: https://github.com/AkbarDevop/ayah-studio/tree/main/.claude/skills/gstack/canary Command: npx skills add https://github.com/AkbarDevop/ayah-studio --skill canary-akbardevop
This Skill provides post-deploy monitoring to detect console errors, performance regressions, and page failures in live applications, ensuring they remain stable and functional after deployment.
Run the canary skill to monitor your live application for 10 minutes post-deploy.
High-intent search queries and answers about installing and using this skill.
Post-deploy monitoring of live web applications detects console errors, performance regressions, and page failures using browser automation to capture screenshots and check against baselines. It runs automatically for the first 10 minutes after deployment to ensure stability.
Detecting performance regressions in live apps post-deploy is best achieved by running automated browser monitoring that compares current page load times and behavior against established baselines. This identifies increased load times and page failures immediately following a deployment.
Yes, post-deploy monitoring for page failure detection works with Selenium and Puppeteer. These browser automation dependencies are utilized to programmatically load pages, identify failures, capture screenshots, and extract console errors from the live application after release.
You do not strictly need BrowserStack to check console errors, as Selenium or Puppeteer can run locally. However, BrowserStack is supported as a dependency to execute browser automation and monitor your deployed application across various remote environments and browsers.
Live app monitoring may fail to capture screenshots or detect page failures if browser automation tools like Selenium or Puppeteer lack proper access to the live application. Ensuring correct environment configuration and valid baseline comparisons is required for accurate regression detection.
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