Multiple tenants in one house, each with their own privacy

감성러버 2025년 06월 13일

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One of the most complex challenges of running a SaaS service is the multi-tenancy design. Different customers have different needs, and it's too expensive to have separate servers for each, but mixing all the data together creates security and isolation issues.

At first, we thought, "Oh, we'll just add a company_id column to the database," but it turned out to be much more complicated than we thought. Customization, performance isolation, backup/recovery strategies... There were a lot of things to consider.

So I decided to take a systematic approach to designing a multi-tenancy architecture.

Prompt.

복사

# multitenancy architecture expert

Service Status:

- Customer size: [Estimated number of tenants and user size].

- Data characteristics: [customer-specific data sensitivity and isolation requirements].

- Customization: [Need for feature/UI differentiation by customer].

- Performance requirements: [SLAs and scalability goals].

Multi-tenancy design strategy:

◆ Step 1: Select isolation model

- Analyze the pros and cons of shared DB/schema isolation/full isolation

- Determine the optimal isolation level for [our service characteristics].

- Set data access control and security perimeter for each tenant

Step 2: Scalability architecture

- Horizontal scaling strategy through sharding and partitioning

- Resource usage monitoring and automatic scaling by tenant

- Balancing large and small tenants

Stage 3: Customization Framework

- Tenant-specific configuration management and feature toggle system

- Plugin architecture to extend customer-specific features

- Multi-branding and whitelabeling support structure

Step 4: Operational Efficiency

- Automate tenant onboarding and provisioning

- Handle tenant-level isolation of backups/restores

- Mechanisms to minimize impact in the event of performance issues

Please include real-world implementable code examples and performance optimization guides.

After 8 months of building a multi-tenancy architecture, we were able to create a really stable and scalable system, and the biggest achievement was that the 'cost of adding a tenant' was almost zero.

The key was to find the right level of isolation - we didn't apply the same isolation level to all tenants, but rather a sliding scale based on security requirements and cost, with logical isolation for business customers and physical isolation for enterprise customers.

Data isolation using Row-Level Security was particularly effective, as PostgreSQL's RLS feature allowed us to implement complete tenant isolation with very little modification to our application code.

Another game-changer was the per-tenant configuration system, which leverages JSON columns to provide different feature sets and UIs for each tenant, allowing us to customize our service offerings.

After a year, we saw that the number of tenants had increased tenfold, but the operational complexity had not increased significantly. Most importantly, we were able to flexibly respond to customer-specific requirements, which greatly improved customer satisfaction.

For teams considering multi-tenant SaaS development, I recommend taking an incremental approach and not trying to achieve complete isolation from the start!

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