What are the best practices for invalidating and updating REST API caches?

1 Cache-Control Headers

One of the simplest and most widely supported ways to control the caching behavior of your REST API is to use the HTTP cache-control headers. These headers allow you to specify how long and where your responses can be cached, and whether they need to be validated before being served. For example, you can use the max-age directive to indicate how long a response can be cached, the no-cache directive to force a validation with the server before using a cached response, or the no-store directive to prevent any caching at all. You can also use the ETag and Last-Modified headers to provide a way to check if a cached response has changed, and use the If-None-Match and If-Modified-Since headers to request a conditional GET that only returns a response if the cached one is stale.

2 Cache Invalidation Strategies

Another aspect of caching is how to invalidate or update the cached data when the underlying data changes. There are two main strategies for cache invalidation: push and pull. Push-based invalidation means that the server notifies the cache or the client when a data change occurs, and triggers an update or a deletion of the cached response. This can be done using mechanisms such as webhooks, messaging queues, or web sockets. Pull-based invalidation means that the cache or the client periodically checks with the server for any data changes, and updates or deletes the cached response accordingly. This can be done using mechanisms such as polling, long polling, or HTTP/2 server push.

3 Cache Granularity and Partitioning

Another factor that affects the caching efficiency and freshness is the granularity and partitioning of the cached data. Granularity refers to how much data is cached in a single unit, and partitioning refers to how the data is divided into different cache segments or regions. Generally, the finer the granularity and the more partitions, the more flexible and precise the cache control, but also the more overhead and complexity. For example, if you cache the entire response of a resource collection, you can avoid multiple requests and reduce latency, but you also have to invalidate or update the whole cache whenever any item in the collection changes. On the other hand, if you cache each individual resource separately, you can have more fine-grained control over the cache invalidation and update, but you also have to make more requests and deal with more cache segments.

4 Cache Consistency Models

Another consideration for caching is how to ensure the consistency between the cached data and the underlying data. Consistency refers to how accurate and up to date the cached data reflects the actual state of the data source. There are different levels of consistency that can be achieved, depending on the requirements and trade-offs of your application. For example, strong consistency means that the cached data is always identical to the data source, and any change is immediately reflected in the cache. This can be achieved by using synchronous invalidation or update mechanisms, but it also introduces more latency and complexity. Weak consistency means that the cached data may be different from the data source, and any change may take some time to propagate to the cache. This can be achieved by using asynchronous or periodic invalidation or update mechanisms, but it also introduces more staleness and uncertainty.

5 Cache Testing and Monitoring

The last but not least best practice for caching is to test and monitor your caching performance and behavior. Testing and monitoring can help you identify and fix any issues or errors with your caching logic, such as cache misses, cache corruption, or cache leaks. They can also help you measure and optimize your caching efficiency and effectiveness, such as cache hit rate, cache size, or cache latency. You can use various tools and methods to test and monitor your caching, such as load testing, benchmarking, logging, tracing, or profiling.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?