Azure Redis Caching Essentials – 5 Practice Tests

• Redis is an advanced key-value store, where keys can contain data structures such as strings, hashes, lists, sets and sorted sets. Redis supports a set of atomic operations on these data types.

• Azure Redis Cache is based on the popular open-source Redis cache. It gives you access to a secure, dedicated Redis cache, managed by Microsoft and accessible from any application within Azure.

• Azure Redis Cache uses Redis authentication and also supports SSL connections to Redis.

• Azure Redis Cache is easy to use. Just provision a cache using the Microsoft Azure portal and call into its end point using any client that supports Redis.

• Azure Redis Cache is easy to manage. You can also easily monitor the health and performance of your cache through the Azure portal.

• Also, you can have Microsoft manage replication of the cache for you, helping increase the availability of your cache data across cache failures.

.NET applications can use the StackExchange.Redis cache client, which can be configured in Visual Studio using a NuGet package that simplifies the configuration of cache client applications.

Sample Client:

1. Get the Redis Connection String: Azure Portal à Redis Caches à Select the Cache Created à Settings à Access Keys à Copy to Notepad Primary Connection String to be used in code later.

2. Open Visual Studio 2017, and create a new console application called RedisCacheClient.

3. Add the StackExchange.Redis NuGet package to the application.

4. Add the Newtonsoft.Json.net NuGet package to the application.

5. Add the following to the Console Application.

Private caching

The most basic type of cache is an in-memory store. It's held in the address space of a single process and accessed directly by the code that runs in that process. This type of cache is very quick to access. It can also provide an extremely effective means for storing modest amounts of static data, since the size of a cache is typically constrained by the volume of memory that's available on the machine hosting the process.

If you need to cache more information than is physically possible in memory, you can write cached data to the local file system. This will be slower to access than data that's held in-memory but should still be faster and more dependable than retrieving data across a network. If you have multiple instances of an application that uses this model running concurrently, each application instance has its own independent cache holding its own copy of the data.

Think of a cache as a snapshot of the original data at a point in the past. If this data is not static, it is likely that different application instances hold different versions of the data in their caches. Therefore, the same query performed by these instances can return different results.