Talks

Horizontal scaling sounds simple in a README, but the reality of a Spring Boot fleet on ECS can quickly turn into "Fleeticide." We've all seen it: connection pools saturate, health checks flap, and suddenly your auto-scaling policy becomes an auto-failing policy.

In this session, we go behind the scenes of a real-world scaling disaster. We'll dissect our initial naive assumptions and dive into the technical shifts that saved our production environment. We will move beyond "CPU/Memory 101" to look at:

The Observability Gap: Tracking the "hidden" metrics (Thread pools, DB connections) that actually dictate survival.

AWS Patterns for the Real World: Moving beyond basic CloudWatch alarms to custom metrics and predictive scaling that respects Spring Boot's startup overhead.

Architecting for Elasticity: How to bake scaling-awareness into the developer workflow to prevent connection storms and cascading failures.

You'll leave with a battle-tested checklist of what to monitor, architectural patterns for graceful scale-out, and the hard-won wisdom of why you must control your application's failure points before they control you.
Stephen Galbraith
Capital One
Staff Engineer at CapitalOne Uk, using Java for 25 years
Jack Gough
Capital One
I am a Staff Software Engineer at Capital One UK. I primary work on Java backend services deployed in AWS with an interest in performance optimisations and scalability