Faktur: Scaling Electronic Invoicing
for Enterprise Compliance
The client
Faktur is an electronic invoicing system that allows companies to automatically create, send, validate, and store electronic invoices in accordance with their country's regulations (in Colombia, with the DIAN). The platform serves businesses of all sizes, enabling them to stay compliant while streamlining their invoicing workflows.
The challenge
- Scalable management of bulk uploads of invoices from Faktur customers.
- Improve data extraction logic, strengthen error handling, and ensure compatibility with official DIAN standards.
- Integrate monitoring without overloading the system and ensure alerts are useful to the support team.
- Architecture and external dependencies management.
- Backup management and disaster recovery.
The solution
We implemented a comprehensive solution to address Faktur's scaling and reliability challenges:
- Standardize and automate backup and deployment processes to minimize risks and downtime.
- Scale the system by adding workers without exceeding external API limits and maintaining data integrity.
- Allow operational adjustments without modifying the codebase, facilitating scalability and customization for different clients.
- Optimize queuing and file processing, reduce Mean Time To Detect (MTTD) failures, and shift from reactive to proactive support.
We implemented a robust technical stack optimized for high-volume invoice processing and compliance:
- Python & Django: Main language and web framework powering the core application logic
- Django REST Framework: API layer for seamless integrations and third-party connectivity
- Celery & Redis: Asynchronous task processing for bulk invoice uploads and background job management
- PostgreSQL: Robust database for reliable data storage and complex queries
- Dropbox SDK: Cloud file integration for document management and storage
- UWSGI & NGINX: Production deployment stack for optimal request handling and performance
- Slack API: Automated notifications for real-time alerts to the support team
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Process Automation
Monitoring & Alerts
Infrastructure & Deployment
Tech We Used
Django
Python
Docker
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