Published on November 1, 2023

Improving API Performance

Suppose you noticed that the latency of your API service is slowly creeping up in line with the increase in traffic. You have added additional compute to the load balancing pool to help distribute the load, but it may be time to explore some optimization at the code level. This article will explore 5 of infinite techniques on how to increase the performance of an API service. They are caching, minimizing N + 1 queries, paginating large results, data compression, and avoiding synchronous logging.


Starting with caching, which usually lives between the middle tier and the database. The idea is to store the results of expensive computations to be reused at a later request. This can help reduce the number of database hits for frequently accessed endpoints with the same parameters.

Minimize N+1 Queries

Minimizing N + 1 queries against the database can significantly improve API performance. Often time this problem appears in hierarchical data where you might query for data at one level, then make another query for each of the results. For example, this could mean one query to get a list of posts, and then another query for each of the posts to retrieve a list of comments per post.


Instead of returning the full dataset per query, consider paginating the results and returning a subset of the full dataset. This will improve query time on the data layer, processing time in the middle tier, and network load.

Data Compression

Data compression can help reduce the size of the response payload and the amount of data being transferred over the network. The client will need to decompress the response payload before using it. Similarly, this will help reduce network load.

Avoid Synchronous Logging

Lastly, avoid synchronous logging in favor of fire and forget. Synchronous logging will add to the round trip time of an API request. The time it takes to write one log entry is insignificant, it can add up in a high throughput system, especially if the request has multiple points of logging.

These are five examples of how to improve an API’s performance. Keep in mind that premature optimization can lead to unnecessary complexity.

CacheCode OptimizationData CompressionLatency OptimizationN+1 QueriesPaginationTech