FastAPI Radar: Real-Time Monitoring Dashboard

Arif Dogan

Completed work

Software Engineer

FastAPI

React

Shadcn UI

Computer Software

FastAPI Radar

A debugging dashboard for FastAPI applications providing real-time request, database query, and exception monitoring.

Just one line to add powerful monitoring to your FastAPI app!

See it in Action

Installation

pip install fastapi-radar

Or with your favorite package manager:

# Using poetry
poetry add fastapi-radar

# Using pipenv
pipenv install fastapi-radar

Note: The dashboard comes pre-built! No need to build anything - just install and use.

Quick Start

With SQL Database (Full Monitoring)

from fastapi import FastAPI
from fastapi_radar import Radar
from sqlalchemy import create_engine

app = FastAPI()
engine = create_engine("sqlite:///./app.db")

# Full monitoring with SQL query tracking
radar = Radar(app, db_engine=engine)
radar.create_tables()

# Your routes work unchanged
@app.get("/users")
async def get_users():
    return {"users": []}

Without SQL Database (HTTP & Exception Monitoring)

from fastapi import FastAPI
from fastapi_radar import Radar

app = FastAPI()

# Monitor HTTP requests and exceptions only
# Perfect for NoSQL databases, external APIs, or database-less apps
radar = Radar(app)  # No db_engine parameter needed!
radar.create_tables()

@app.get("/api/data")
async def get_data():
    # Your MongoDB, Redis, or external API calls here
    return {"data": []}

Access your dashboard at: http://localhost:8000/\_\_radar/

Features

Zero Configuration - Works with any FastAPI app (SQL database optional)

Request Monitoring - Complete HTTP request/response capture with timing

Database Monitoring - SQL query logging with execution times (when using SQLAlchemy)

Exception Tracking - Automatic exception capture with stack traces

Real-time Updates - Live dashboard updates as requests happen

Flexible Integration - Use with SQL, NoSQL, or no database at all

Configuration

radar = Radar(
    app,
    db_engine=engine,            # Optional: SQLAlchemy engine for SQL query monitoring
    dashboard_path="/__radar",   # Custom dashboard path (default: "/__radar")
    max_requests=1000,           # Max requests to store (default: 1000)
    retention_hours=24,          # Data retention period (default: 24)
    slow_query_threshold=100,    # Mark queries slower than this as slow (ms)
    capture_sql_bindings=True,   # Capture SQL query parameters
    exclude_paths=["/health"],   # Paths to exclude from monitoring
    theme="auto",                # Dashboard theme: "light", "dark", or "auto"
    db_path="/path/to/db",       # Custom path for radar.duckdb file (default: current directory)
)

Custom Database Location

By default, FastAPI Radar stores its monitoring data in a radar.duckdb file in your current working directory. You can customize this location using the db_path parameter:

# Store in a specific directory
radar = Radar(app, db_path="/var/data/monitoring")
# Creates: /var/data/monitoring/radar.duckdb

# Store with a specific filename
radar = Radar(app, db_path="/var/data/my_app_monitoring.duckdb")
# Creates: /var/data/my_app_monitoring.duckdb

# Use a relative path
radar = Radar(app, db_path="./data")
# Creates: ./data/radar.duckdb

If the specified path cannot be created, FastAPI Radar will fallback to using the current directory with a warning.

Development Mode with Auto-Reload

When running your FastAPI application with fastapi dev (which uses auto-reload), FastAPI Radar automatically switches to an in-memory database to avoid file locking issues. This means:

No file locking errors - The dashboard will work seamlessly in development

Data doesn't persist between reloads - Each reload starts with a fresh database

Production behavior unchanged - When using fastapi run or deploying, the normal file-based database is used

# With fastapi dev (auto-reload enabled):
# Automatically uses in-memory database - no configuration needed!
radar = Radar(app)
radar.create_tables()  # Safe to call - handles multiple processes gracefully

This behavior only applies when using the development server with auto-reload (fastapi dev). In production or when using fastapi run, the standard file-based DuckDB storage is used.

What Gets Captured?

✅ HTTP requests and responses

✅ Response times and performance metrics

✅ SQL queries with execution times

✅ Query parameters and bindings

✅ Slow query detection

✅ Exceptions with stack traces

✅ Request/response bodies and headers

Contributing

We welcome contributions! Please see our Contributing Guide for details.

Development Setup

For contributors who want to modify the codebase:

Clone the repository:

git clone https://github.com/doganarif/fastapi-radar.git
cd fastapi-radar

Install development dependencies:

pip install -e ".[dev]"

(Optional) If modifying the dashboard UI:

cd fastapi_radar/dashboard
npm install
npm run dev  # For development with hot reload
# or
npm run build  # To rebuild the production bundle

Run the example apps:

# Example with SQL database
python example_app.py

# Example without SQL database (NoSQL/in-memory)
python example_nosql_app.py

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

Built with FastAPI

Dashboard powered by React and shadcn/ui

Like this project

Completed work

Posted Oct 1, 2025

Developed FastAPI Radar, a real-time monitoring dashboard for FastAPI apps.

Likes

Views