Scenario 05: Gradual Migration
Target Audience: Maintainers of legacy codebases, tech leads Difficulty: Intermediate to Advanced Keywords: migration, refactoring, legacy code, technical debt, incremental change
📋 The Problem
Migrating large sync codebases to async is risky:
Big Bang Rewrite:
Rewrite entire codebase at once
High risk of bugs and regressions
Long feature freeze
All-or-nothing deployment
Team must learn async all at once
Parallel Maintenance:
Maintain old sync and new async versions
Feature parity challenges
Double the work
Confusing for contributors
Delayed deprecation of old code
Common blockers:
Mixed sync/async dependencies
Can’t change public API (breaking change)
Some modules easy to convert, others hard
Need gradual rollout for safety
Team has varying async experience
💡 Solution with SmartAsync
Incremental migration path:
Phase 1: Add decorator to existing code
No behavior change
No breaking API changes
Sync code still works
Phase 2: Convert internal methods to async
Method by method
Keep public API unchanged
Each change is isolated and testable
Phase 3: Expose async capability
Users can opt-in to async usage
Sync usage still works
Zero breaking changes
Phase 4: Optimize
Remove sync-only paths (optional)
Document async-first approach
Maintain backward compatibility
Key advantage: Each step is deployable and reversible.
🎯 Migration Strategies
Strategy 1: Bottom-Up
Start with lowest-level utilities
Move up the stack
Public API last
Risk: Low (internal changes only)
Strategy 2: Top-Down
Start with public API
Add async support gradually
Internal sync code offloaded to threads
Risk: Medium (public changes early)
Strategy 3: Critical Path
Identify performance bottlenecks
Convert hot paths first
Leave cold paths sync
Risk: Low (focused changes)
Strategy 4: Feature Branches
New features async-first
Legacy features stay sync
Gradual codebase evolution
Risk: Very low (isolated)
🎯 When to Use
Ideal for:
Large legacy codebases
Public libraries with stable APIs
Teams transitioning to async
Risk-averse organizations
Continuous delivery environments
Perfect when:
Breaking changes are unacceptable
Need to ship features during migration
Team has mixed async expertise
Testing async thoroughly is challenging
Want data on async benefits before full commit
⚠️ Considerations
Migration Planning
Timeline expectations:
Small project (< 10K LOC): Weeks
Medium project (10-100K LOC): Months
Large project (> 100K LOC): Quarters to years
Team training:
Async fundamentals
Event loop concepts
Testing async code
Debugging async issues
Technical debt:
SmartAsync adds small overhead
May remove decorator later if all-async
Document migration progress
Monitoring
Track metrics:
Percentage of async methods
Performance improvements
Error rates during migration
User adoption of async mode
Rollback plan:
Each phase independently reversible
Feature flags for async paths
Monitoring and alerting
When NOT to Use
Avoid if:
Small codebase (full rewrite faster)
No async expertise available
No performance benefit expected
Dependencies don’t support async
Better alternatives:
Full rewrite for small projects
Separate async-only version (major version bump)
Stay sync-only if no async benefit
📚 Case Studies
Projects that could benefit:
Django ORM - Async support being added gradually
SQLAlchemy - Added async support over multiple versions
Celery - Gradual async worker support
Flask - Adding async support while maintaining sync compatibility
🎯 Success Criteria
Migration is successful when:
No user-facing breaking changes
Performance improved in async mode
Sync mode still works (backward compatibility)
Team confident with async patterns
Production stable throughout migration
Can remove SmartAsync if desired (fully async)
Next Steps:
See 04: Unified Library API for API design
Check 03: Testing for testing strategies