Intermediate LevelCloud Computing (AWS/GCP/Azure)
What are Data Isolation Strategies for Multi-Tenant SaaS applications in the cloud?
❓ Interview Prompt: Compare Multi-Tenant SaaS isolation models: Silo (separate database), Bridge (separate schemas), and Pool (shared tables).
Designing multi-tenant SaaS applications requires choosing a data isolation pattern that balances security compliance against infrastructure operational cost:
1. Silo Model (Isolated Infrastructure per Tenant):
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Architecture: Separate database instance and VPC per customer tenant.
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Pros: Maximum security isolation, regulatory compliance, zero cross-tenant noisy neighbor impact.
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Cons: High infrastructure cost and management overhead.
2. Bridge Model (Shared Database, Separate Schemas):
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Architecture: Single database instance with isolated PostgreSQL schemas per tenant ('tenant_acme.orders', 'tenant_globex.orders').
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Pros: Moderate cost, good logical isolation.
3. Pool Model (Shared Tables & Shared Infrastructure):
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Architecture: All tenants share the exact same database tables, isolated logically by a 'tenant_id' partition column.
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Pros: Lowest cost, maximum resource efficiency. Requires strict RLS (Row Level Security) filters!
Code Implementation Example
sql
-- PostgreSQL Row Level Security (RLS) enforcing Pool model multi-tenant isolation
ALTER TABLE orders ENABLE ROW LEVEL SECURITY;
CREATE POLICY tenant_isolation_policy ON orders
USING (tenant_id = current_setting('app.current_tenant_id'));💡PostgreSQL Row Level Security policy isolating multi-tenant data in Pool model.
🎯 Interview Key Takeaway
Choose Silo model for maximum enterprise compliance isolation; choose Pool model with Row Level Security for cost-effective SaaS.
#Multi-Tenant#SaaS Architecture#Data Isolation#Databases#Intermediate
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