Are you still loading everything into memory? Let me ask you something. How many times have you seen this in a codebase? repository.findAll() ☠️ Looks harmless, right? Until it isn’t. That single line can: • Pull millions of records into memory • Fill your Hibernate context • Trigger massive GC pressure • And eventually… crash your application This is not a performance issue. This is an architectural flaw. Most systems don’t fail because of complexity. They fail because of unbounded data processing. You are not controlling how much data your system loads, processes, or returns. And memory… has limits. So what’s the right approach? Stop thinking: "How do I get all the data?" Start thinking: "How do I guarantee I NEVER load too much?" The solution is simple (but often ignored): • Use pagination for APIs • Use streaming for large exports • Process data in controlled chunks • Return DTOs instead of heavy entities • Set hard limits Golden rule: Never load, process, or serialize everything at once. Always paginate, stream, or limit. Most production outages I’ve seen had one thing in common: Someone assumed the data would always be small. It never is. #SoftwareArchitecture #Java #SpringBoot #DistributedSystems #SoftwareEngineering #DesignPatterns
Great reminder — always design APIs and services with bounded data contracts, streaming, and backpressure in mind.
Absolutely—design APIs and services to process bounded batches, using streaming and pagination to prevent unbounded memory usage.
Great reminder — enforce backpressure via pagination, streaming, and bounded batch processing to prevent unbounded memory growth.