feat: Implement Step 10-11 - Statistics and Notification Services

Step 10: Data Analytics and Statistics Service
- Created comprehensive statistics service with real-time metrics collection
- Implemented time-series data storage interface (InfluxDB compatible)
- Added data aggregation and analytics endpoints
- Integrated Redis caching for performance optimization
- Made Kafka connection optional for resilience

Step 11: Real-time Notification System
- Built multi-channel notification service (Email, SMS, Push, In-App)
- Implemented priority-based queue management with Redis
- Created template engine for dynamic notifications
- Added user preference management for personalized notifications
- Integrated WebSocket server for real-time updates
- Fixed pymongo/motor compatibility issues (motor 3.5.1)

Testing:
- Created comprehensive test suites for both services
- Added integration test script to verify cross-service communication
- All services passing health checks and functional tests

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

services/notifications/backend/Dockerfile

@@ -0,0 +1,21 @@
+FROM python:3.11-slim
+
+WORKDIR /app
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    gcc \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy requirements first for better caching
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy application code
+COPY . .
+
+# Expose port
+EXPOSE 8000
+
+# Run the application
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000", "--reload"]