API Response Optimization
In the early days of a startup, "functional" is the goal. You write a query, you get the data, and you send it to the frontend. But as we scaled past 50,000 users, that "functional" code became a m...
Source: DEV Community
In the early days of a startup, "functional" is the goal. You write a query, you get the data, and you send it to the frontend. But as we scaled past 50,000 users, that "functional" code became a massive liability. We realized that frontend performance means nothing if your backend is bloated. When every millisecond counts, your API response strategy is the difference between a smooth user experience and a hanging loading spinner. The Invisible Cost of SELECT The most common mistake Node.js developers make is over-fetching. We often use SELECT * or return entire Mongoose documents because it’s "easier." However, at scale, this is devastating. Every extra field you send adds to the payload size, which increases network latency. More importantly, it increases the time the Node.js process spends on JSON serialization. Converting a massive object into a JSON string is a CPU-intensive, synchronous operation. If your CPU is busy stringifying a 2MB response for User A, User B’s request is sit
