API Performance

Src: systemdesigncodex.com

Caching

Store frequently accessed data in a cache so you can access it faster.

If there’s a cache miss, fetch the data from the database.

It’s pretty effective, but it can be challenging to invalidate and decide on the caching strategy.

Scale-out with Load Balancing

You can consider scaling your API to multiple servers if one server instance isn't enough. Horizontal scaling is the way to achieve this.

The challenge will be to find a way to distribute requests between these multiple instances.

Load Balancing

It not only helps with performance but also makes your application more reliable.

However, load balancers work best when your application is stateless and easy to scale horizontally.

Pagination

If your API returns many records, you need to explore Pagination.

You limit the number of records per request.

This improves the response time of your API for the consumer.

Async Processing

With async processing, you can let the clients know that their requests are registered and under process.

Then, you process the requests individually and communicate the results to the client later.

This allows your application server to take a breather and give its best performance.

But of course, async processing may not be possible for every requirement.

Connection Pooling

An API often needs to connect to the database to fetch some data.

Creating a new connection for each request can degrade performance.

It’s a good idea to use connection pooling to set up a pool of database connections that can be reused across requests.

This is a subtle aspect, but connection pooling can dramatically impact performance in highly concurrent systems.