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Redis Cache Implementation In .NetCore Web API Using Distributed Caching Technique(Redis Docker Instance)

Redis Cache:

Redis is an open-source in-memory data structure store, used as a database, cache. It supports data structures such as strings, hashes, lists, sets, sorted sets with range queries, etc.

Setup Redis Docker Instance:

For this sample to use Redis instance locally we will use Docker. If you don't have any prior knowledge of docker, not a problem just follow the steps below. Click here for a video session on Redis docker setup
Note:
Skip this section if you already have redis direct instance or azure or any cloud provider that have redis
Step1:
Download docker into our local system "https://docs.docker.com/desktop/". Docker was available for all desktop operating systems.
Step2:
After downloading the docker installer, then install it. Now to run any docker containers(eg: Redis, MongoDB, PostgreSQL, etc) this docker instance we just installed should be active(should be running).
Step3:
Now we need to pull the docker Redis image from the docker hub "https://hub.docker.com/_/redis".
Command To Pull Redis Image:
docker pull redis
Step4:
The final step to run the docker Redis image container by mapping our local system port. By default, the Redis instance runs with the '6379' default port inside of the docker container. So to access the Redis we need to port mapping on starting off the container.
Command To Start Redis Container:
docker run --name your_containerName -p your_PortNumber:6379 -d redis
The '--name your_containerName' flag to specify the Redis container name. The '-p your_PortNumber:6379' mapping the Redis port '6379' to our local machine port all our application will use local machine port to communicate with Redis. The '-d' flag represents to run the container in the detached mode which means run in the background. At the last of the command 'redis' to specify the image to run in our container.
Step5:
After creating a docker container, it will be stored in our local machine so to start again the container any time run the following command
docker start your_container_name

Step6:(Optional Step)
Let test our Redis instance

Command To Use Redis CLI
docker exec -it your_docker_container_name redis-cli

Create A Sample API Project:

Let's understand the flow of Redis cache by implementing a sample API application.

Install StackExchange.Redis Package:

Package Manager:
Install-Package Microsoft.Extensions.Caching.StackExchangeRedis
CLI Command:
dotnet add pakcage Microsoft.Extensions.Caching.StackExchangeRedis

Sample Todos Endpoint:

Let's begin by creating a sample 'Todos' endpoint where we are going to integrate Redis cache in upcoming steps.
Controllers/TodosController.cs:
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text.Json;
using System.Threading.Tasks;
using Microsoft.AspNetCore.Http;
using Microsoft.AspNetCore.Mvc;
using Microsoft.Extensions.Caching.Distributed;

namespace Redis.Sample.Api.Controllers
{
  [Route("api/[controller]")]
  [ApiController]
  public class TodosController : ControllerBase
  {
	List<string> todos = new List<string> { "shopping", "Watch Movie", "Gardening" };
	
	[Route("all")]
	public async Task<IActionResult> GetAll()
	{
		List<string> myTodos = todos;
		bool IsCached = false;
		return Ok(new { IsCached, myTodos });
	}
  }
}
  • Here implemented endpoint that returns simple static todos list collection(in a real-time application we have to fetch data from a database, for demo purpose I'm simply using static todos collection). 
  • The 'IsCached' property helps to identify whether data loaded from the cache or not(we will make its value dynamic in upcoming steps)

Configure AddStackExchangeRedisCache Service:

To integrate Redis functionality configure the 'AddStackExchangeRedisCache()' service in startup file.
Startup.cs:(ConfigureServices Method)
services.AddStackExchangeRedisCache(options => {
 options.Configuration = "localhost:5003";
});
  • For 'Configuration' we passed the Redis connection string(Here my docker Redis instance exposed to my machine with port 5003).

IDistributedCache Interface:

IDistributedCache Interface is implemented from the 'Microsoft.Extensions.Caching.Distributed' library. IDistributeCache is not specific to Redis Cache, but it was implemented like generic which supports all kinds of Distributed Cache like Redis, SQL Server Cache, etc. IDistributeCache supports the default dependency inject of .NET Core, so it can be easily injected in the application where ever needed. IDistributedCache Interface holds a set of methods that helps to work with cache, some of the methods like as below.
  • Get, GetAsync, GetStringAsync - fetches the cached data by the key passed to the method.
  • Set, SetAsync, SetStringAsync - saves the data to the cache table with a specific key.
  • Remove, RemoveAsync - removes the cached data with specific to key passed.
Now inject the IDistributedCache interface into our Todos endpoint controller.
Controllers/TodosController.cs:
namespace Redis.Sample.Api.Controllers
{
  [Route("api/[controller]")]
  [ApiController]
  public class TodosController : ControllerBase
  {
    List<string> todos = new List<string> { "shopping", "Watch Movie", "Gardening" };
    private readonly IDistributedCache _distributedCache;
    public TodosController(IDistributedCache distributedCache)
    {
	 _distributedCache = distributedCache;
    }
  }
}

Use SetStringAsync And GetStringAsync:

SetStringAsync - This asynchronous method used to save the string of data with a key for it like a dictionary. If we intended to save any object or collection of an object into Redis then we can serialize them to string and store in the cache.

GetStringAsync - This asynchronous method used to fetch the stored string data from the cache-store using its respective key value.

Let us now store our todos data to Redis cache, so update our endpoint action method as below.
Controllers/TodosController.cs:
[HttpGet]
[Route("all")]
public async Task<IActionResult> GetAll()
{
  List<string> myTodos = new List<string>();
  bool IsCached = false;
  string cachedTodosString = string.Empty;
  cachedTodosString = await _distributedCache.GetStringAsync("_todos");
  if (!string.IsNullOrEmpty(cachedTodosString))
  {
   // loaded data from the redis cache.
   myTodos = JsonSerializer.Deserialize<List<string>>(cachedTodosString);
   IsCached = true;
  }
  else
  {
   // loading from code (in real-time from database)
   // then saving to the redis cache 
   myTodos = todos;
   IsCached = false;
   cachedTodosString = JsonSerializer.Serialize<List<string>>(todos);
   await _distributedCache.SetStringAsync("_todos", cachedTodosString);
  }
  return Ok(new { IsCached, myTodos });
}
  • (Line: 5) The 'myTodos' variable to store our final result of todos collection.
  • (Line: 6)  The 'IsCached' variable indicates data loaded from Redis cache or not. The variable added for understanding purposes.
  • (Line: 8) The 'GetStringAsync('your_key')' method to fetch the value Redis cache based on the key.
  • (Line: 9) Checks data exist in the cache-store.
  • (Line: 12) Since we get string data from the Redis cache, then we need to deserialize them to respective object types.
  • (Line: 15-23) If data doesn't exist in Redis.
  • (Line: 19) Assigning our static todo data to our result variable(in real-time application fetch data from database)
  • (Line: 21) Serializing our todos collection to string.
  • (Line: 22) The 'SetStringAsync('your_key','your_string_value')' method to store data to Redis with respective of the given key.
Now run the application, for the first time data will be loaded directly and store in the Redis cache
Now access endpoint again, now data gets loaded from the Redis cache.
You confirm data storing correctly or not in docker redis-cli.

InstanceName Option:

The 'key' name we used here like '_todos' to store data in Redis cache. In real-time we may build multiple applications that all are going to share Redis cache, in this case, simple key names(eg: '_todos') may get conflicted between the application. So to avoid this kind of issue dotnet provides as a global setting to set a key prefix which is like a namespace. The best value to assign value to a key prefix is the project name.
Startup.cs:
services.AddStackExchangeRedisCache(options => {
  options.Configuration = "localhost:5003";
  options.InstanceName = "Redis.Sample.Api";
});
  • (Line: 3) The 'InstanceName' will be prefixed to every Redis key while saving data and also prefix with the key to fetching the data.

Cache Expiration:

The cache should have an expiry date. To define expiration we have two options which are mandatory for a good coding approach.
  • Absolute Expiration.
  • Sliding Expiration.
Absolute Expiration - Maximum time period to store in the cache. After expiration Redis will automatically delete all keys and its values automatically.

Sliding Expiration - Maximum time period to store data without consuming by the applications. If an application not using any particular keys for a specific time it is always good to clear them from the cache before its Absolute Expiration. This type of expiration will be called a Sliding Expiration. One important thing to remember Sliding Expiration always less than Absolute Expiration time. If you set Sliding Expiration more than Absolute Expiration id doesn't make any sense because data will be cleared after the Absolute Expiration time.
Controllers/TodosController.cs:
[HttpGet]
[Route("all")]
public async Task<IActionResult> GetAll()
{
  List<string> myTodos = new List<string>();
  bool IsCached = false;
  string cachedTodosString = string.Empty;
  cachedTodosString = await _distributedCache.GetStringAsync("_todos");
  if (!string.IsNullOrEmpty(cachedTodosString))
  {
   // loaded data from the redis cache.
   myTodos = JsonSerializer.Deserialize<List<string>>(cachedTodosString);
   IsCached = true;
  }
  else
  {
   // loading from code (in real-time from database)
   // then saving to the redis cache 
   myTodos = todos;
   IsCached = false;
   cachedTodosString = JsonSerializer.Serialize<List<string>>(todos);
   var expiryOptions = new DistributedCacheEntryOptions()
   {
	AbsoluteExpirationRelativeToNow = TimeSpan.FromSeconds(60),
	SlidingExpiration = TimeSpan.FromSeconds(30)
   };
   await _distributedCache.SetStringAsync("_todos", cachedTodosString, expiryOptions);
  }
  return Ok(new { IsCached, myTodos });
}
  • (Line: 22-26) Creating 'Absolute Expiration' and 'Sliding Expiration'. The time specified for sliding expiration set less than absolute expiration.
  • (Line: 27) The 'SetStringAsync()' method is an overloaded method that takes expiration configuration as an input value.

Remove Cache:

It is always good to have an endpoint to clear the cache. The 'RemoveAsync' methods will remove our cached data with respect to the key passed to it.
Controllers/TodosController.cs:
[HttpGet]
[Route("clear-cache")]
public async Task<IActionResult> ClearCache(string key)
{
  await _distributedCache.RemoveAsync(key);
  return Ok(new { Message = $"cleared cache for key -{key}" });
}
That's all about the core topics and their implementation for integrating Redis cache into our API.

Wrapping Up:

Hopefully, I think this article delivered some useful information on setting up a Redis instance using docker and then consuming the Redis cache into our dotnet core API application. I love to have your feedback, suggestions, and better techniques in the comment section below.

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