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When choosing a caching strategy, always consider the rate of data change and choose the correct time-to-live (TTL) of the data in the cache, to match the rate of change of the data. Data on an e-commerce site such as item descriptions, reviews, and images are unlikely to change frequently, but data such as item stock and price might not be suitable for caching at all. Always keep this in mind when selecting an answer on the exam.
ElastiCache is a managed service that can deploy clusters of in-memory data stores. They can be used to perform server-side and database caching.
A typical use case is database offloading with an application-managed sideloaded cache, as described in the previous section. Most applications that work with a database have a high read-to-write ratio—somewhere in the range of 80–90 percent reads to 10–20 percent writes. This means that offloading the reads from the database could save as much as 60–80 percent of the load on the database. For example, if the read-to-write ratio is 90–10 percent, each write (10 percent resources) requires a subsequent read (at least 10 percent resources), and if the rest of the reads are cached, up to 80 percent of the read load can be offloaded to the cache.
An additional benefit of caching with ElastiCache is that the two engines used, Memcached and Redis, are both in-memory datastores. In comparison with databases where response latencies are measured in milliseconds to seconds, the response times from in-memory databases are measured in microseconds to milliseconds. That can mean that any cached data can be delivered 10, 100, or potentially even 1000 times faster than it would be if the request were read from the database. Figure 4.10 contrasts latency of Redis versus S3.
FIGURE 4.10 Redis vs. S3 GET latencies
One of the engines supported by ElastiCache is Memcached, a high-performance, distributed, in-memory key-value store. The service has a simple operational principle in which one key can have one or many nested values. All the data is served out of memory; thus, there is no indexing or data organization in the platform. When using Memcached, you can design either a single instance cache or a multi-instance cache where data is distributed into partitions. These partitions can be discovered by addressing the service and requesting a partition map. There is no resilience or high availability within the cluster because there is no replication of partitions.
Memcached is a great solution for offloading frequent identical database responses. Another use for Memcached is as a shared session store for multiple web instances. However, the lack of resilience within the Memcached design means that any failure of a node requires the application to rebuild the node from persistent database data or for the sessions with the users to be re-established. The benefit of Memcached is that it is linearly read and write scalable because all you need to do is add nodes to the cluster and remap the partitions.
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