Deployment overview
DeskDox deployments should be planned around user count, document volume, search/OCR workload, storage growth, security policy, administrator maturity, and required network restrictions.
Deployment
Use this page to evaluate deployment models, reference architecture, service dependencies, typical ports, infrastructure sizing, security hardening, and production readiness.
DeskDox deployments should be planned around user count, document volume, search/OCR workload, storage growth, security policy, administrator maturity, and required network restrictions.
A typical production architecture places web traffic behind a reverse proxy, keeps API and database services internal, runs conversion and OCR work through workers, and stores files in managed object or filesystem-backed storage.
Exact sizing depends on document volume, OCR workload, concurrent users, retention policy, preview generation, and backup strategy. A pilot can usually start smaller, while production environments should reserve capacity for database growth, file storage, and worker queues.
Plan storage for original files, converted previews, thumbnails, OCR output, backups, and retention growth. Storage should be monitored and expandable before production onboarding.
Production readiness requires database backups, file storage backups, restore testing, retention policy, administrator ownership, and a documented recovery procedure.
Notification delivery, workflow updates, password or account messaging, and support communications require a trusted SMTP relay with appropriate sender identity and delivery monitoring.
Use stable DNS names, valid TLS certificates, and reverse proxy rules that route web and API traffic predictably. Certificate renewal should be operationally owned.
Emii planning should cover model access, permission-aware retrieval, data routing, restricted-network behavior, and whether AI services are cloud-based, private, or hybrid.