Migrating from REST to GraphQL: Lessons Learned
Key Takeaways
- Plan a gradual migration strategy to minimize risk
- Design GraphQL schemas with evolution in mind
- Solve N+1 query problems with DataLoader
- Invest in proper tooling and team training early
Why We Migrated to GraphQL
After years of building and maintaining REST APIs, we decided to migrate to GraphQL to solve several persistent pain points: over-fetching data, under-fetching requiring multiple requests, and the complexity of maintaining multiple API versions. This is our migration story with lessons learned.
Initial Assessment
Before starting the migration, we thoroughly evaluated several key factors:
- API usage patternsAnalyzed current pain points and inefficiencies
- Team expertiseAssessed learning curve and training needs
- Ecosystem maturityEvaluated tooling and library support
- Performance implicationsBenchmarked GraphQL vs REST performance
- Migration strategyPlanned timeline and rollout approach
Gradual Migration Strategy
We chose a gradual, low-risk approach that allowed us to learn and adapt while maintaining our existing REST API for stability.
- •Start with new features implemented in GraphQL to gain experience
- •Wrap existing REST endpoints with GraphQL resolvers for quick wins
- •Migrate high-value, frequently-used endpoints first for maximum impact
- •Maintain REST API during transition period for backward compatibility
- •Deprecate REST endpoints gradually with clear communication to clients
Schema Design Principles
We learned to design effective, evolvable GraphQL schemas:
- Think in graphsModel relationships naturally, not as endpoints
- Consistent namingUse clear, predictable naming conventions
- Proper paginationImplement cursor-based pagination for scalability
- Design for evolutionUse nullable fields and avoid breaking changes
- PolymorphismLeverage interfaces and unions for flexible types
Performance Challenges
We encountered and solved several critical performance issues:
- N+1 QueriesSolved with DataLoader for batching and caching
- Complex QueriesImplemented query complexity analysis and limits
- Large ResponsesAdded pagination and field limiting
- Caching StrategyImplemented persisted queries and CDN caching
Client-Side Benefits
Frontend teams saw immediate productivity improvements:
- Precise data fetchingRequest exactly the data needed, nothing more
- Fewer API callsCombine multiple REST calls into single GraphQL query
- Strong typingGenerate TypeScript types from schema automatically
- Better DXGraphQL Playground and IDE integration
- Complex UIsEasier to build sophisticated interfaces
Challenges and Solutions
Problems we faced and how we overcame them:
- Learning CurveInvested in comprehensive training and documentation
- Caching ComplexityUsed Apollo Cache with normalized data structure
- File UploadsImplemented GraphQL multipart request specification
- Real-time UpdatesAdded GraphQL subscriptions over WebSocket
- Error HandlingStandardized error format and error codes
Conclusion
Migrating to GraphQL was challenging but ultimately worthwhile. The improved developer experience, eliminated over-fetching, and better frontend-backend collaboration have made our team significantly more productive. If you're considering GraphQL, start with a pilot project, learn from the experience, and don't rush the migration process.
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