Potta Vijay Kumar

In today’s connected world, APIs are the backbone of modern applications. But with growing user bases and interconnected services, the risk of server overload, abuse, or system crashes becomes real. That’s where rate limiting and throttling step in — to ensure performance , security , and fair usage . What Is API Rate Limiting? API rate limiting controls how many requests a client can make to an API within a specific time frame . It helps prevent abuse (like DDoS attacks), ensures fair access among users, and safeguards infrastructure from being overwhelmed. Example: A public API may allow 1000 requests per hour per user. After that, users receive a 429 Too Many Requests error until the limit resets. What Is API Throttling? Throttling is a dynamic form of rate limiting. Instead of outright rejecting requests, it slows down or queues them when usage exceeds safe thresholds. It ensures graceful degradation rather than abrupt denial. Key Differences Minimize image Edit image Delete ...

  Source: https://github.com/pottavijay/edge-computing-app In today’s digital world, speed and user experience are critical. No one wants to wait for a website or application to load, and milliseconds can make a big difference. One powerful solution that’s reshaping how we deliver APIs efficiently is Edge Computing . But what exactly is Edge Computing, and how can it optimize your APIs? Let's break it down! What is Edge Computing? Edge Computing refers to moving computation and data storage closer to the location where it's needed, rather than relying solely on centralized servers. Instead of your request traveling all the way to a remote data center, it's processed at the "edge" of the network—closer to the user. In API optimization , Edge Computing means serving data and handling API requests near the client’s location, resulting in faster response times, reduced latency, and improved reliability. Why Edge Computing Matters for APIs ...