![]() Sometimes you don’t want to retry something for a minute or so when it didn’t work.Īn example here could be fetching some data from an API.Īnother one would be logging interaction with your Cache. One example we could have here is that we want to cache something in case of exceptions. It does one thing well: Depending on your parameters the method is guarded by a cache. It is easy, it does what it should – but it is really general. The setup we created just now is really nice. So after finishing this part of the implementation your code should look like the one this branch: 2. If we want to change this behaviour we have to setup our CacheManager to have a default TTL, but more about this later. This means: They are stored inside the Redis Cache forever! In our current setup, the keys never get evicted. You can flush the cache by using redis-cli flushall and then run it again. It might be that your Redis Cache is still containing the value. Sidenote: If you run it multiple times don’t be surprised if Returning NOT from cache! goes away. We also put a with a proper cache name on top of it. What I did to get started is to create a class called CacheService which has a single method cacheThis. Luckily, the initializer has already done most of the work for us. Let’s hope our local Redis Cache installation is working and start connecting our Spring Boot Service to the local instance. Connect our Spring Boot Service to our local Redis Cache The result is a project opened in your IDE having all the necessary dependencies. If you are using IntelliJ IDEA, you also can just use the initializer from within IDEA itself. We just created a Spring Boot Service using Redis as a Cache. If you want to run without it – no issue at all, it might just be that in some places you need to generate a few more methods.Īlso make sure to give your project a nice name, I went with com.programmerfriend as group and ultimate-redis as Artifact name.Īdding the Redis and Cache dependency to our new project here will add the spring-boot-starter-data-redis and spring-boot-starter-cache as dependencies to our service. It is providing helpful annotations like and instead of generating getters and setters in our code itself. The last one is really optional, but I like to include it in most of my java projects since it makes our whole codebase much less verbose. Let’s add the dependencies Redis, Cache and Lombok. we will generate our Service independent from an IDE in 1.2 we will be using IntelliJ Idea (just to show you both ways and to be IDE-agnostic) 1.1 Head over to and create a Spring Boot Service Create our Spring Boot Redis Caching Service In case you need any help, or a quick sneak peek: The whole code is available on the GitHub-Repository. Now that we dealt with the “Infrastructure”: Let’s go for our service implementation using Spring Boot 2. Make sure that redis-server is running and maybe go to: for troubleshooting. I would advice you to go to and have a try on your own.įor all the people who don’t want to get off this page right now: Mac OS:Ĭould not connect to Redis at 127.0.0.1:6379: Connection refused. There are many ways of installing Redis on your machine. Lets get started – Redis Installation Guide Define after what time (TTL=time-to-live) our cached Entries are not valid anymore. ![]() Create dynamic CacheKeys: Cache depending on the input parameters of our methods.Gain more fine granular control by using the other available Annotations.Use Spring’s Integrated Annotation to cache results of method invocations using Spring Data Redis.Setting up the Redis Cache on your machine.To give you a short summary what we are about to do: In this Guide I want to give you the same powerful tools for your current and future Implementations. At the center of this is Spring Boot together with Redis. It has been a while since I wrote my article about ‘How We Made Our Spring Boot Applications More Robust with Redis Cache and Spring AOP‘, so I guess it is time to write another technical article about Redis and Spring Boot.ĭuring my last 2 years at work, I would say a lot of our current architecture is only possible by using Caching. The Ultimate Guide to Redis Cache with Spring Boot 2 will help you to fulfill all requirements. This article shows how you can use it for your caching needs. Spring Boot and Redis are a powerful combination.
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