Large‑scale user bases
Scale to millions with a per‑installation license — no per‑user caps. Run horizontally with zero‑downtime upgrades at customer sites or in your cloud.
Industry Context
Archetype: Platforms with very large, intermittently active user populations
E‑commerce, financial services, and insurance portals where many users log in infrequently, but the total population is huge.
Challenges
Maintain predictable costs and performance at very large user counts without per‑user licensing, while meeting enterprise reliability expectations.
- • Avoid runaway license costs at high user counts
- • Scale horizontally with HA and zero‑downtime updates
- • Meet compliance and residency constraints by running in customer infrastructure
Solution Approach
ProAuth’s flat‑rate, self‑hosted model runs in your infrastructure and scales on Kubernetes without per‑user limits.
Enterprise license with no user or application caps
Kubernetes horizontal scaling and autoscaling
Deploy at customer sites or in your cloud with the same architecture
Architecture & Operations
Customer‑hosted or first‑party cloud Kubernetes with replicated services.
- • ProAuth core services with HA configuration
- • Observability (metrics, logs, traces) and auditing
- • Config‑as‑code and CLI for repeatable operations
Zero‑downtime upgrades and rolling strategies; tenant‑aware partitioning where needed.
Implementation
Timeline: Typically weeks, depending on federation and data migration requirements.
- P0: Capacity and HA planning
- P1: Kubernetes deployment and automation
- P2: Federation/SCIM and tenant partitioning
- P3: Cutover and production hardening
Results & Benefits
- • Predictable costs for high‑volume, low‑frequency usage patterns
- • Operational continuity during updates
- • Control over data residency and compliance
Future Expansion
- • Broader federation catalog
- • Expanded autoscaling playbooks
Why ProAuth
- • Enterprise license with no user or application limits
- • Kubernetes horizontal scaling and autoscaling
- • Tenant‑aware user stores and federation patterns that scale
How it fits
- • Deploy containerized and scale replicas for throughput and high availability
- • Partition per tenant with dedicated stores or federate to external IdPs
Outcomes
- • Predictable costs for high‑volume workloads
- • Operational continuity during updates