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+---
+title: FastAPI + Uvicorn
+weight: 6
+---
+
+This guide demonstrates how to integrate Prometheus metrics into a [FastAPI](https://fastapi.tiangolo.com/) application using the native [Uvicorn](https://www.uvicorn.org/) ASGI server with production-ready multiprocess support.
+
+### Basic Implementation
+Save the following in a `myapp.py` file:
+
+```python
+import os
+from fastapi import FastAPI
+from prometheus_client import make_asgi_app, Counter, Gauge, CollectorRegistry, multiprocess
+from fastapi.responses import JSONResponse
+import psutil
+
+app = FastAPI()
+
+Define metrics with multiprocess aggregation
+REQUEST_COUNT = Counter(
+    "http_requests_total",
+    "Total HTTP requests by endpoint",
+    ["endpoint"],
+    registry=CollectorRegistry()  # Isolated registry
+)
+CPU_USAGE = Gauge(
+    "system_cpu_usage_percent",
+    "Current CPU utilization percentage (aggregated)",
+    multiprocess_mode='livesum'  # Critical for worker aggregation
+)
+
+def create_metrics_app():
+    """Create multiprocess-aware metrics endpoint"""
+    registry = CollectorRegistry()
+    multiprocess.MultiProcessCollector(
+        registry,
+        path=os.environ.get(  # Explicit path handling
+            'PROMETHEUS_MULTIPROC_DIR', 
+            '/tmp/prometheus'  # Fallback path
+        )
+    )
+    return make_asgi_app(registry=registry)
+
+Mount endpoint with trailing slash
+app.mount("/metrics/", create_metrics_app())
+
+@app.get("/")
+async def home():
+    REQUEST_COUNT.labels(endpoint="/").inc()
+    CPU_USAGE.set(psutil.cpu_percent(interval=None))  # System-wide measurement
+    return JSONResponse({"status": "ok"})
+```
+
+### Key Configuration
+1. **Multiprocess Aggregation**  
+   Required for gauge metrics in worker environments:
+   ```python
+   # Supported modes: livesum/max/liveall
+   Gauge(..., multiprocess_mode='livesum')
+   ```
+
+2. **Registry Isolation**  
+   Prevents metric conflicts between components:
+   ```python
+   REQUEST_COUNT = Counter(..., registry=CollectorRegistry())
+   ```
+
+### Running the Application
+```bash
+1. Install dependencies with psutil
+pip install fastapi uvicorn prometheus-client psutil
+
+2. Single-process mode (development)
+uvicorn myapp:app --port 8000
+
+3. Multiprocess mode (production)
+export PROMETHEUS_MULTIPROC_DIR=./metrics_data  # Persistent storage
+mkdir -p $PROMETHEUS_MULTIPROC_DIR
+uvicorn myapp:app --port 8000 --workers 4
+
+4. Generate load for verification
+for i in {1..100}; do curl -s http://localhost:8000/ & done
+
+5. Verify aggregated metrics
+curl -s http://localhost:8000/metrics/ | grep -E 'http_requests_total|system_cpu_usage_percent'
+```
+
+### Expected Output
+```text
+TYPE http_requests_total counter
+http_requests_total{endpoint="/"} 100.0
+
+TYPE system_cpu_usage_percent gauge
+system_cpu_usage_percent 68.5  # Aggregated across workers
+```
+
+### Production Checklist
+1. **Directory Configuration**  
+   ```bash
+   chmod 750 ./metrics_data  # Secure write permissions
+   ```
+2. **Storage Management**  
+   - Use dedicated volume for `PROMETHEUS_MULTIPROC_DIR`
+   - Implement cleanup cron job:
+     ```bash
+     0 * * * * find /path/to/metrics_data -name '*.db' -mtime +7 -delete
+     ```
+3. **Validation Tools**  
+   ```bash
+   # Check active worker count
+   ps aux | grep -c '[u]vicorn.*worker'
+
+   # Monitor data files
+   watch -n 5 'ls -lh $PROMETHEUS_MULTIPROC_DIR | grep .db'
+   ```
+
+### Troubleshooting
+| Symptom                | Solution                      | Verification Command             |
+|------------------------|-------------------------------|-----------------------------------|
+| PID labels in metrics  | Add `multiprocess_mode` param | `grep 'multiprocess_mode' myapp.py` |
+| Missing .db files      | Check directory permissions   | `ls -ld $PROMETHEUS_MULTIPROC_DIR` |
+| Stale values           | Verify endpoint activation    | `curl -I http://localhost:8000/`   |