Visual Regression Testing Workflow
This workflow implements automated visual regression testing of web pages through an AI visual model, automatically generating and comparing web page screenshots to accurately identify changes in content, layout, and color. It integrates web screenshot services and cloud storage to ensure efficient screenshot management. It can promptly detect visual anomalies on web pages, generate structured change reports, and create tasks to help teams quickly locate issues, thereby enhancing product quality. It is suitable for development, testing, and operations teams in continuous integration and delivery processes.
Workflow Name
Visual Regression Testing Workflow
Key Features and Highlights
This workflow implements AI-driven visual regression testing for web pages by automatically capturing and comparing screenshots to accurately detect changes in content, layout, color, and other visual aspects. It leverages the Google Gemini visual model for image comparison and automatically generates structured change reports. Results can be created as tasks in Linear for easy team tracking and resolution. The workflow integrates Apify’s web screenshot service along with Google Drive and Google Sheets to ensure efficient and reliable screenshot storage and management.
Core Problems Addressed
Traditional web regression testing struggles to automatically detect subtle visual changes such as layout shifts, image anomalies, or color variations. This workflow uses AI visual models to automatically compare screenshots, eliminating manual repetitive checks, improving the accuracy and efficiency of issue detection, and helping development and QA teams quickly pinpoint visual anomalies to ensure product quality.
Use Cases
- Automated UI change detection in website or web app CI/CD pipelines
- Multi-version web UI consistency monitoring
- Quick visual verification of web pages by designers and testers after updates
- Regular inspections of large websites to identify abnormal page content changes
Main Process Steps
- Retrieve Webpage List — Read URLs and baseline screenshot metadata from Google Sheets.
- Generate Baseline Screenshots (Part A) — Capture webpage screenshots via Apify, upload to Google Drive for storage, and update screenshot IDs in Google Sheets.
- Scheduled Test Trigger (Part B) — Automatically fetch the webpage list on schedule and for each page:
- Download baseline and latest screenshots (latest captured again via Apify)
- Merge the two screenshots and send them to the Google Gemini visual model for comparison
- Parse Comparison Results — Use a structured output parser to convert AI detection results into JSON format for further processing.
- Filter Changed Pages — Identify pages with visual differences.
- Generate Test Report — Aggregate all detected changes and automatically create Linear tasks for team review and follow-up.
Involved Systems and Services
- Google Sheets: Manage webpage URL lists and screenshot metadata
- Apify.com: Webpage screenshot generation service
- Google Drive: Storage and management of screenshot files
- Google Gemini (PaLM) Visual Model: AI-powered image comparison and visual difference detection
- Linear.app: Automated creation of change report tasks to support team collaboration
Target Users and Value
- Test Engineers: Automate visual regression testing to reduce manual verification workload
- Frontend Developers and Designers: Quickly detect visual anomalies to ensure user experience quality
- Product Managers and Operations Teams: Monitor webpage update risks and improve release quality
- Any team requiring web visual quality monitoring: Enhance efficiency and accuracy through automated workflows
By combining modern tools and AI technologies, this workflow delivers an efficient and intelligent visual regression testing solution for web pages, significantly reducing the risk of missing visual anomalies. It is suitable for teams of all sizes to use in daily development and operations.