Cache Validity
You can control the freshness of your cached data by applying a time to live (TTL) or expiration to your cached keys. After the set time has passed, the key is deleted from the cache, and access to the origin data store is required along with reaching the updated data.
Two principles can help you determine the appropriate TTLs to apply and the types of caching patterns to implement. First, it’s important that you understand the rate of change of the underlying data. Second, it’s important that you evaluate the risk of outdated data being returned back to your application instead of its updated counterpart.
For example, it might make sense to keep static or reference data (that is, data that is seldom updated) valid for longer periods of time with write-throughs to the cache when the underlying data gets updated.
With dynamic data that changes often, you might want to apply lower TTLs that expire the data at a rate of change that matches that of the primary database. This lowers the risk of returning outdated data while still providing a buffer to offload database requests.
It’s also important to recognize that, even if you are only caching data for minutes or seconds versus longer durations, appropriately applying TTLs to your cached keys can result in a huge performance boost and an overall better user experience with your application.
Another best practice when applying TTLs to your cache keys is to add some time jitter to your TTLs. This reduces the possibility of heavy database load occurring when your cached data expires. Take, for example, the scenario of caching product information. If all your product data expires at the same time and your application is under heavy load, then your backend database has to fulfill all the product requests. Depending on the load, that could generate too much pressure on your database, resulting in poor performance. By adding slight jitter to your TTLs, a randomly-generated time value (for example, TTL = your initial TTL value in seconds + jitter) would reduce the pressure on your backend database and also reduce the CPU use on your cache engine as a result of deleting expired keys.
