Building an Enterprise-Grade n8n Dashboard with Real-Time Monitoring [#14 Aemal Sayer] скачать в хорошем качестве

Building an Enterprise-Grade n8n Dashboard with Real-Time Monitoring [#14 Aemal Sayer]

🎁 Download Part 1 Here: https://go.n8n.io/n8n-dashboard-frontend 🎁 Download Part 2 Here: https://go.n8n.io/n8n-dashboard-backend In this episode, Aemal walks through building a comprehensive monitoring dashboard for n8n workflows that enterprises can use to track every execution, identify failures, and even calculate workflow costs. Timestamps: 0:00 - Introduction 2:30 - Understanding n8n Backend Hooks 8:45 - Setting Up Supabase Schema 15:20 - Capturing Execution Data 22:10 - Building the Dashboard with Replit 35:15 - Security Best Practices 38:40 - Future of AI Development What You'll Learn: • How to use n8n backend hooks to capture execution telemetry data • Setting up Supabase to store workflow execution logs • Building a real-time dashboard with Next.js and Replit • Implementing enterprise-grade monitoring for n8n instances • Security best practices when connecting frontend to backend • Using AG Grid for advanced data filtering and visualization Key Features Built: ✅ Real-time execution tracking ✅ Failure monitoring and notifications ✅ Execution data analysis with full JSON context ✅ Cost tracking for workflows (especially token usage) ✅ Enterprise-grade UI with Hero UI components Tech Stack: n8n (workflow automation) Supabase (database) Next.js (full-stack framework) Replit (development & deployment) AG Grid (data tables) Hero UI (component library) GitHub Repositories: Both the n8n backend hooks and the dashboard UI are available as open-source repositories. Links in the description! Perfect For: CTOs and technical leaders monitoring n8n deployments Business operators tracking workflow performance DevOps teams needing execution visibility Anyone running enterprise n8n instances Bonus Discussion: We also dive into the future of AI-native development, vibe coding with tools like Replit and Cursor, and how AI is transforming software engineering productivity by 20-50x.