Build Your Own n8n Insights Dashboard To Track Workflow Executions Using Lovable
- Harshal
- 7 minutes ago
- 3 min read
Build Notes for an n8n execution tracker using Lovable, Supabase, and n8n API
I show here how you can track n8n workflow aggregated execution counts and success rates across all workflows. You can build your own ("BYO") dashboard with Lovable, Supabase, and the n8n API.
You need 2 minutes to read this.
Related:
I work at n8n, but this blog represents my personal technical exploration and opinions, not official n8n policy or product guidance. The approaches described are my own experiments.
Problem Context
The n8n executions tab shows execution history. That helps track individual runs. But you may want aggregated execution data across all your workflows. Specifically:
Total execution counts per workflow over time
Success versus failure rates over time
Manual execution stats apart from production executions
Preserved historical trends for a long time
This lets you understand your automation usage and prioritize improvements on workflows with high execution counts or frequent failures.
Solution Via App
This dashboard gives you aggregated execution data and preserves history over time.
App lives here: n8n Usage Insights Dashboard
Video walkthrough:
Open the dashboard to see execution counts and success rates for all workflows. The dashboard tracks:
Execution counts: Aggregated by workflow
Execution type: Production versus manual executions
Success versus failure split: Per workflow and overall
Historical data: Stored in Supabase DB, preserved over time
Anyone can use this dashboard by entering their n8n instance URL and API key.
Features
Aggregated execution counts across workflows
Success and failure split visualization
Production and manual execution tracking
Data persistence over time
Light and dark mode
Auto-sync on first daily visit
Privacy ensured because without a matching instance URL and API key, you cannot view your data, even if you persisted it.
API Key is only used within the browser.
Tech Stack
Lovable - frontend and AI copilot
Supabase - backend for data persistence, edge functions to fetch from n8n API
n8n API - fetch execution data and workflow names
OpenAI, Gemini, Google Drawings - make the logo
Learnings
Data persistence: Check whether the data source you are fetching for your app has data persistence for the length of time you want. If not, then build a data persistence layer. Example, I stored n8n execution data in Supabase to preserve history beyond its 7-day retention in my personal cloud instance.
Alternative data persistence: You could log every execution to an n8n data table or Google Sheet by adding nodes to each workflow. I skipped that approach because it requires modifying every workflow and increases execution counts. Fetching from the API is simpler. You could have a cron job in Supabase to fetch the data every few days.
Daily sync trigger: The dashboard syncs data on first daily visit, not on every visit. This reduces API calls and latency to show info to users.
Data structure: The n8n API returns execution data by execution ID. I used a Supabase edge functions aggregate and normalize this data for the dashboard.
Multi-user support: From other Lovable projects, I felt multi-user project with authentication has a lot of security holes. So instead, I build the dashboard to accept any n8n instance URL and API key. Anyone can use it for their own instance.
Future improvements
Add an n8n MCP (Model Context Protocol) integration for the instance to enable AI chat-based customization.
Add filtering by date range.
Add execution time tracking per workflow.
Add time saved tracking
Related:
