Tag
A walkthrough of taking a monolithic Java backend through the scaling journey — what we changed at each stage, what broke, and the concrete decisions that moved the needle when traffic grew 50×.
How distributed systems stay up when traffic moves from hundreds to hundreds of thousands of requests per second — the architectural decisions, trade-offs, and failure modes that actually matter at scale.
What actually breaks when a Java backend grows from hundreds of users to hundreds of thousands — and the concrete patterns, code, and trade-offs that keep it standing.
Why averages lie, what p95/p99/p999 actually tell you, and how to pick SLO targets that match real user experience.
The real trade-offs of native-image compilation for Java services — startup, memory, throughput — and the friction that stops most teams from adopting it universally.
What actually happens when you flip the virtual threads switch on a Spring Boot service — the wins, the sharp edges, and when the old thread-pool model still beats them.