Lately, I’ve been digging into what actually slows down APIs. Here are a few bottlenecks that changed how I think about performance

• It’s not always the database, sometimes it’s how we call it. Sending multiple small requests instead of batching them adds network overhead. • Connections are expensive. Rebuilding them on every request means repeated handshakes that could’ve been avoided with reuse. • Even logging can slow you down. Synchronous logs make the system wait after every write. • Repeated data fetching is often self-inflicted. If the same response is requested again and again, caching at the right layer can remove unnecessary load. • Payload size matters more than expected. Uncompressed JSON responses increase latency, especially at scale. • Database connections are costly to create. Without pooling, each request pays the setup cost • And sometimes it’s just the format. JSON is convenient, but not always efficient when compared to something like Protobuf