From MVP to Scale: Engineering for Growth

The Scaling Challenge

Your MVP worked. Customers are signing up. Now the codebase that got you here is holding you back. Sound familiar?

Every successful startup faces this transition. Here's how to navigate it without a complete rewrite.

Identifying Scale Blockers

Database bottlenecks

Slow queries that worked fine with 1,000 users

Missing indexes

N+1 query problems

Monolithic database trying to do everything

Monolithic architecture

Deployments affect the entire system

Can't scale components independently

Single points of failure

Technical debt

Quick fixes that became permanent

Missing tests

Outdated dependencies

Copy-pasted code

The Strangler Fig Pattern

Don't rewrite—gradually replace. The Strangler Fig pattern:

Identify a bounded context (e.g., user authentication)

Build the new version alongside the old

Route traffic incrementally to the new system

Decommission the old code

Database Evolution

Step 1: Optimize what you have

Add strategic indexes

Implement query caching

Use read replicas

Step 2: Decompose data

Separate hot and cold data

Move specific domains to specialized stores

Consider CQRS for read-heavy workloads

Service Extraction

When to extract a service:

Clear domain boundary

Different scaling requirements

Different team ownership

Independent deployment needs

Start with one service. Learn the operational complexity before extracting more.

Technical Debt Strategy

Categorize debt:

**Critical:** Blocking scalability or causing incidents

**Strategic:** Worth addressing before it gets worse

**Tolerable:** Annoying but not worth the investment

Budget for debt repayment:

20% of engineering time on technical health

Tie debt fixes to feature work when possible

Conclusion

Scaling is a journey, not a destination. Build incrementally, measure constantly, and resist the urge to rewrite everything at once.