Designing Scalable AWS Architectures: Lessons from Production
Key principles and patterns I've learned from building and scaling production systems on AWS, from ECS clusters to serverless architectures.
Building production-grade systems on AWS requires more than just knowing the services. It demands a deep understanding of how those services interact, fail, and scale under real-world conditions.
Start with the Fundamentals
Every scalable architecture I've built starts with three core principles:
- Design for failure — Assume every component will fail and build redundancy accordingly.
- Decouple aggressively — Use queues, events, and well-defined interfaces to keep services independent.
- Observe everything — You can't fix what you can't see. Invest in logging, metrics, and tracing from day one.
Choosing the Right Compute Model
The decision between ECS, Lambda, and EC2 is rarely straightforward. Here's how I think about it:
- Lambda excels for event-driven workloads with variable traffic patterns. The cold start trade-off is often acceptable for background processing.
- ECS with Fargate is my default for HTTP APIs that need predictable latency and steady throughput.
- EC2 still makes sense for specialized workloads that need specific instance types or GPU access.
Database Strategy
Multi-database strategies are increasingly common in production. I typically recommend:
- PostgreSQL (RDS) for your primary transactional data.
- DynamoDB for high-throughput, key-value access patterns.
- Redis (ElastiCache) for caching, sessions, and real-time features.
The key is defining clear boundaries for each data store and using the right tool for each access pattern.
Infrastructure as Code
Terraform has been my go-to for infrastructure management. The ability to review infrastructure changes in pull requests, track state, and maintain environments consistently is invaluable for production systems.
Every module should be versioned, tested, and documented. Treat your infrastructure code with the same rigor as your application code.
Conclusion
Scalable AWS architectures aren't built overnight. They evolve through iterative improvements, production incidents, and a relentless focus on reliability. Start simple, measure everything, and let real-world data drive your architectural decisions.