The gist of this pattern is to load data on demand into a cache from a data store. This pattern can improve performance and also helps to maintain consistency between data held in the cache and the data in the data store. Applications use a cache to optimize repeated access to information held in a data store. However, it is usually impractical to expect that cached data will always be completely consistent with the data in the data store.

There are many commercial caching systems providing read-through and write-through/write-behind operations. In these systems, an application retrieves data by referencing the cache. If the data is not available in the cache, it is transparently retrieved from the distant data store and added to the cache. Any modifications to data held in the cache are automatically written back to the data store as well. For caches that do not provide this functionality, it is the responsibility of the applications that use the cache to maintain the data in the cache. An application can emulate the functionality of read-through caching by implementing the cache-aside strategy. This strategy effectively loads data into the cache on demand.

Cloud application performance is often questioned by many. Hence, there is a bevy of performance enhancement techniques and tips being unearthed and promoted. This pattern is one such breakthrough solution technique in order to supply all the right and relevant information for application designers to substantially increase cloud performance.

The usage scenarios include:

• A cache doesn't provide native read-through and write-through operations
• Resource demand is unpredictable