Table of contents:
Caching at Scale: The Freshness vs. Performance Trade-off
The Problem: Fresh Data Is Expensive
Our Architecture: From Browser to Database
What Happens When Traffic Scales?
Finding the Real Bottlenecks
The Three Constraints: Freshness, Cost, and Resilience
Why SSR Changes the Equation
The Solution: Cache at Every Layer
Redis: Taking the Pressure Off SSR
Pre-render What Doesn't Need to Be Rendered
Different Data, Different TTLs
Making Kubernetes Absorb the Spikes
Fine-Tuning: Finding the Right Cache Boundaries
What We Learned in Production
The Takeaway: Caching Is an Architectural Discipline
This talk has been presented at JSNation US 2026, check out the latest edition of this JavaScript Conference.
























