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However, we don't recommend that you use the cache as the authoritative store of critical information.
Instead, ensure that all changes that your application cannot afford to lose are always saved to a persistent data store.
Additionally, if the database becomes unavailable, client applications might be able to continue by using the data that's held in the cache.
Consider caching data that is read frequently but modified infrequently (for example, data that has a higher proportion of read operations than write operations).
Often an analysis of usage patterns can help you decide whether to fully or partially prepopulate a cache, and to choose the data to cache.
For example, it can be useful to seed the cache with the static user profile data for customers who use the application regularly (perhaps every day), but not for customers who use the application only once a week.
This means that if the cache is unavailable, your application can still continue to operate by using the data store, and you won't lose important information.
The key to using a cache effectively lies in determining the most appropriate data to cache, and caching it at the appropriate time.
Think of a cache as a snapshot of the original data at some point in the past.
Using a shared cache can help alleviate concerns that data might differ in each cache, which can occur with in-memory caching.
Shared caching ensures that different application instances see the same view of cached data.
Alternatively, a cache can be partially or fully populated with data in advance, typically when the application starts (an approach known as seeding).
However, it might not be advisable to implement seeding for a large cache because this approach can impose a sudden, high load on the original data store when the application starts running.