Multi-Tenant SaaS Architecture

Schema-per-tenant (separate database schema per customer) provides the strongest isolation, easier per-tenant backups and restores, and is preferred for enterprise/regulated customers. Row-level security (RLS) uses a single schema with a tenant_id column and Postgres policies — simpler operations, lower provisioning overhead, and scales to thousands of tenants more easily. The right choice depends on your compliance requirements and tenant count.

We implement defence in depth: tenant context is set at the start of every request, Postgres Row Level Security policies enforce isolation at the database level even if application code has a bug, all API responses are validated for tenant scope before returning, and we write automated tests specifically designed to probe for cross-tenant data access.

Yes, but it requires careful planning. We conduct a codebase audit to identify all places where data is fetched without tenant scoping, design a migration path that adds tenant context without breaking existing data, and implement the changes incrementally. It's more complex than greenfield multi-tenancy but very achievable with the right approach.

We implement a tenant configuration system — a JSON settings table per tenant that drives feature flags, UI customisation, integration credentials and workflow rules. This avoids custom code per tenant while giving tenants meaningful flexibility. For deeper customisation needs (custom fields, workflows), we build a proper extensibility layer.

With proper indexing on tenant_id columns and RLS policies, the performance overhead of multi-tenancy is minimal — typically under 5% compared to a single-tenant equivalent. The bigger risk is N+1 queries and missing indexes as data grows. We profile and optimize these during load testing, and set up query monitoring in production to catch regressions early.