DeDOC Production Systems
Build enterprise document processing systems with DeDOC: scalable architecture, microservices deployment, and production optimization
What is DeDOC?
DeDOC (Document Decomposer) is an open-source system for extracting structured information from documents. Unlike simple parsers, DeDOC provides enterprise-grade document processing with support for complex layouts, tables, hierarchical structures, and metadata extraction across multiple document formats (PDF, DOCX, HTML, etc.).
Enterprise Document Processing at Scale
DeDOC enables organizations to process millions of documents with consistent structure extraction, maintaining document hierarchy, relationships, and metadata while supporting batch processing, real-time streaming, and distributed deployment patterns.
Key Capabilities
- • Structure-aware document parsing
- • Hierarchical content extraction
- • Table detection and extraction
- • Metadata and annotation preservation
- • Multi-format support (20+ formats)
- • RESTful API with async processing
Production Benefits
- • 10,000+ documents/hour throughput
- • 95%+ structure preservation accuracy
- • Horizontal scaling with Docker
- • Fault tolerance and retry logic
- • Comprehensive monitoring
- • Integration with major cloud platforms
DeDOC System Performance Calculator
Estimate processing performance and resource requirements for your document workloads:
DeDOC Architecture Components
DeDOC's modular architecture enables flexible deployment patterns from single-server installations to distributed cloud deployments with automatic scaling and fault tolerance.
Core Processing Engine
Document Readers
Format-specific parsers for PDF, DOCX, HTML, TXT
- • Native format understanding
- • Metadata preservation
- • Error handling & recovery
Structure Analyzers
Hierarchical structure detection and classification
- • Heading hierarchy detection
- • List and table identification
- • Reading order determination
API & Orchestration Layer
RESTful API
High-performance async API with job queuing
- • Async job submission
- • Status tracking & webhooks
- • Rate limiting & authentication
Task Queue
Distributed job processing with Redis/Celery
- • Priority-based scheduling
- • Retry logic & error handling
- • Horizontal worker scaling
Storage & Caching
Document Storage
Scalable storage with S3/MinIO integration
- • Object storage integration
- • Temporary file management
- • Compression & archival
Result Caching
Intelligent caching with Redis for performance
- • Hash-based result caching
- • TTL management
- • Cache invalidation strategies
Production Deployment
Deploy DeDOC in production with Docker containers, Kubernetes orchestration, and comprehensive monitoring for enterprise document processing workflows.
Microservices Integration
Build scalable document processing microservices with DeDOC, supporting distributed architectures, service mesh integration, and cloud-native deployment patterns.
Performance Monitoring
Implement comprehensive monitoring for DeDOC systems with metrics collection, alerting, and performance optimization for production workloads.
Production Best Practices
✅ Do
- • Implement circuit breaker patterns
- • Use async processing for large files
- • Set up comprehensive logging
- • Monitor memory usage per worker
- • Implement graceful degradation
- • Use health checks for containers
- • Cache frequently accessed documents
❌ Don't
- • Process very large files synchronously
- • Skip input validation and sanitization
- • Ignore memory leaks in long-running workers
- • Use blocking I/O in the API layer
- • Store sensitive data in logs
- • Deploy without proper error handling
- • Neglect worker resource limits
Scaling Strategies
Horizontal Scaling
Scale DeDOC workers horizontally with Kubernetes HPA based on queue length and CPU utilization. Each worker handles 10-20 documents concurrently.
Resource Optimization
Optimize memory usage with document streaming, temporary file cleanup, and worker process recycling. Use GPU acceleration for OCR-heavy workloads.
Geographic Distribution
Deploy DeDOC clusters across multiple regions with document replication and intelligent routing for low-latency global document processing.