Scaling up infrastructure is the easy fix—but if your code has deep bottlenecks, it just delays failure and multiplies cost. Reflecting on my work across mobile, web, embedded and cloud systems, I can say: fixing code pays far more than more servers.
A study of serverless workflows found that for data-intensive functions, data transfer and state management costs contribute up to 75% of cloud provider costs—indicating that code patterns matter.
In an Android/VoIP project I identified and refactored synchronous blocking I/O that was forcing more compute to mask the latency. After optimization, infrastructure requirement dropped while performance improved.
Before buying more hardware, profile your code. Identify bottlenecks—data flows, I/O, threading—and optimise.
#BottleneckAnalysis #Refactoring #PerformanceEngineering #CloudComputing #SoftwareDevelopment #Efficiency #EnterpriseTechnology