Scaling Systems
Roadmaps, checklists, and mental models for scaling backend systems from early stage to high traffic.
Scaling to 1 Million Users: A Practical Roadmap for Backend Engineers
There is no silver bullet for scaling. Learn the predictable progression of bottlenecks and how to solve them at each stage of growth.
Why Scaling Backend Systems is 90% Decision-Making, Not Code
Scaling systems isn’t just about infrastructure. It’s about the decisions, trade-offs, and mental models behind them.
Backend System Scaling Checklist: Find Bottlenecks and Stabilize Performance
Backend System Scaling checklist to stabilize APIs and data pipelines. Identify bottlenecks, fix query and caching issues, and implement measurable SLOs.
The Distributed Monolith: Why the Microservices Hype is Killing Early-Stage Velocity
Microservices aren't free. Learn how to identify if you've accidentally built a distributed monolith and why a modular monolith is the superior choice for growth.
Scaling Beyond the Monolith: When (and How) to Introduce Microservices Safely
Is a monolith slowing you down? Learn the strategic roadmap for moving to microservices without crashing your production system, focusing on data consistency and observability.
API Design Mistakes That Kill Scale (and How to Fix Them)
API Design & Architecture mistakes that break evolution: unclear contracts, missing failure modes, and performance-unaware endpoints. Fix it with production-grade design.
Fix & Scale Existing Systems: Stabilize First, Then Scale
Fix & Scale Existing Systems guide: how to audit bottlenecks, remove fragile failure modes, optimize databases/caching, and implement guardrails.