The platform uses Cloudflare as the public edge, backed by layered traffic management and regional load balancing. This gives the system a controlled entry point for request routing, regional distribution, and failure isolation before traffic reaches application infrastructure.
Multi-region design reduces operational risk
The regional model separates a primary Helsinki footprint from a Nuremberg disaster recovery footprint. Each region carries its own API layer, local balancing, and supporting infrastructure so that the system is not dependent on a single runtime surface.
This matters in enterprise F&B because failure is rarely graceful. The question is not whether something breaks, but whether the platform continues operating cleanly when a region, service, or dependency is degraded.
Data architecture is built for continuity
The database layer uses Postgres with Timescale, PgBouncer, and Patroni to balance transactional consistency, pooling, and cluster control. Replication from the primary cluster to the secondary cluster gives the platform a clear continuity path across regions.
Redis is also treated as part of the resilience model rather than an isolated performance accessory. Master-slave replication allows the cache layer to participate in recovery planning for production-grade workflows.
Observability is part of the architecture, not an afterthought
The stack includes Grafana, Prometheus, Loki, Tempo, and Portainer so the system can be operated with visibility across metrics, logs, traces, and container management. A watchdog layer monitors deployments and failure states across both regions.
For a platform designed around 0.5M to 1M orders per day, observability is not a reporting convenience. It is part of the control plane that allows teams to maintain uptime, isolate regressions, and meet enterprise operating expectations.