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Building a Rate Limiter and Throttling Layer Using Spring Boot and Redis
Imagine your backend API is stable, performant and deployed to production. Then someone writes a buggy frontend loop or a bot goes rogue, and suddenly your endpoint gets hit 100 times a second.
That’s how your server’s CPU spikes, your database becomes overloaded, response times shoot up, and eventually your application turns unusable for real users. Even well-architected systems can crumble under this kind of stress, which leads to unhappy customers and costly incidents.