TrackFlow is an advanced tracking system designed to handle large volumes of tracking data with high efficiency. The system is built using Go for backend services and features a range of capabilities including geolocation integration, database optimization, and real-time metrics visualization. TrackFlow leverages modern technologies such as Docker for container management and ClickHouse for high-volume data processing, making it an ideal solution for developers seeking robust data tracking and analytics.
- Client-Side Tracker: JavaScript-based tracking for capturing page views and user interactions.
- Go Backend API: High-performance API designed for efficient data handling and processing.
- Geolocation Services: Real-time IP address to geographic location mapping.
- PostgreSQL and ClickHouse Integration: Efficient data storage and processing with a migration path from PostgreSQL to ClickHouse.
- Dockerized Development: Simplified setup and deployment with Docker.
- Performance Testing and Traffic Generation: Tools for simulating high-load scenarios and testing system performance.
- Database Optimization: Enhanced query performance and data handling with ClickHouse.
- CLI Dashboard: Command-line interface for real-time system monitoring and metrics visualization.
- VM Deployment: Scalable deployment strategies for virtual machines.
- Go: Core language for backend services.
- Chi: Lightweight and idiomatic router for Go applications.
- Docker SDK: Comprehensive container management for streamlined development.
- PostgreSQL: Initial relational database setup.
- ClickHouse: High-performance columnar database for large-scale data handling.
- BoltDB: Lightweight key-value store for persistent task management.
- goprocinfo: Library for system and process metrics collection in Go.
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Client-Side Tracker:
- JavaScript-based solution for tracking page views and user interactions.
- Handles missing data gracefully and supports asynchronous data collection.
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Backend API:
- Built with Go and Chi for high performance and low latency.
- Supports tracking data processing, geolocation lookups, and Docker-based testing.
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Data Storage:
- Initially stores data in PostgreSQL, with optimized migration to ClickHouse for high-volume processing.
- Ensures fast and efficient CRUD operations with data normalization techniques.
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Docker Integration:
- Docker SDK utilized for managing container lifecycle during development and testing.
- Simplifies setup and ensures consistent environments across different stages.
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Real-Time Monitoring:
- CLI dashboard provides a real-time view of system metrics and performance.
- goprocinfo used for detailed process and system metric collection.
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Deployment:
- Supports scalable deployment to virtual machines, with robust configuration and API authentication.
- Go (version 1.18+)
- Docker (version 20.10+)
- PostgreSQL and ClickHouse databases