Which of the following techniques can help reduce network latency for large payloads?

Compressing payloads is an effective technique for reducing network latency when dealing with large payloads. By applying compression to the data being transmitted, the overall size of the payload is significantly reduced. This smaller size means that data can travel over the network more quickly, leading to faster transmission times and reduced latency. Compression algorithms are designed to efficiently reduce the amount of data that needs to be sent without losing the integrity of the information, making it an optimal choice for improving performance in data-heavy applications and services.

In contrast, increasing the payload size results in more data being transmitted, which would likely increase network latency rather than decrease it. Synchronous processing can introduce delays since it requires a response to be received before proceeding with further actions, potentially leading to higher latency overall. Frequent database calls can also add to latency, as each call incurs network overhead and response time, which may not contribute positively to reducing total processing time. Therefore, compressing payloads stands out as the most effective and efficient method for minimizing network latency in this context.