Building a multi-tenant SaaS application on Azure involves architecture decisions that affect cost, isolation, compliance, and operational complexity for the life of the product.
The isolation models
Multi-tenant isolation exists on a spectrum: shared-everything (all tenants share the same database tables, differentiated by a tenant ID column), schema-per-tenant (separate database schemas in one server), database-per-tenant (separate databases), and deployment-per-tenant (separate infrastructure stacks). The right point on the spectrum depends on: compliance requirements (HIPAA, PCI require stronger isolation), customer expectations, and the operational cost of managing many databases or deployments.
Azure SQL elastic pools
For database-per-tenant models on Azure SQL, elastic pools provide the resource sharing that makes the model economical. A pool of compute and storage resources is shared across many small databases. Tenants that are active at the same time share the pool; tenants that are idle do not consume resources. The pool model can support hundreds of small tenant databases on the resources that would otherwise power one large shared database.
Feature flags and tenant configuration
Multi-tenant SaaS applications typically have tenant-specific configuration: different feature sets for different pricing tiers, custom branding, integration endpoints. Feature flag systems (LaunchDarkly, Azure App Configuration with feature management) provide the mechanism for controlling which features are available per tenant without code branching. The tenant configuration model is an architecture decision early in the product lifecycle that is expensive to change later.
Tenant-aware observability
Standard application monitoring loses tenant context in multi-tenant applications. Adding tenant ID to structured log events, to trace attributes, and to metrics dimensions provides the ability to diagnose tenant-specific issues, identify tenants with unusual usage patterns, and track SLO compliance per tenant. The investment in tenant-aware observability pays off every time a specific tenant reports a problem.