Diego Pacheco Tech blog

Lettuce by far is the best Redis client out there for Java. In the java world, Annotations and Mappings are pretty popular. I build services using these concepts before however they were always under the service boundaries, never as shared libraries in order to avoid coupling. So today I record a video showing how we can use this feature and also extend the functionality to add custom enriched behavior.  We will be using Spring Boot 2, Spring Data Redis, and Lettuce as redis Client. We also will need to have redis running either as standalone / cluster or running on docker. We will create custom annotations in order to describe the behavior we want. I need to say that some people love and other people hate annotations, I have mixed feelings. Often for those that don't like it - check this out . Besides that, let's take a look. So Let's get started.

Keys is the default oss standard for K/V store for many use cases and solutions. When you need run low latency, high throughput IN Memory Persistence - Dynomite is your solution. I always wanted to have multi-thread support in redis like Memcached has. Now someone made it and call it KeyDB . The best thing is the fact that this is done supporting the redis RESP protocol, so all your tools, scripts and code using redis protocol directly still works. Another killer feature in KeyDB is the support for FLASH storage, only available on Redis Enterprise. KeyDB also supports backup to S3. For this post, I will show how to build and run KeyDB which is dead simple and also how to use it with Dynomite like it was Redis. KeyDB Benchmarks As you can see on the KeyDB benchmarks, KeyDB does 1.5x less latency and 50% more throughput . These numbers are pretty impressive. The best part is the fact that is all transparent. Running KeyDB Running KeyDB with Dynomite See the Results...

Lately, I'm working with custom redis-modules and I need to say: redis-modules kick ass. I started working with Cthulu and coding modules with javascript which was nice and very productive but given some of my current use cases I had to go to C. I recommend you take a look at my previous posts here:   -  Building Redis-Modules with JavaScript using Cthulhu   -  Dispatching Custom Commands with Lettuce and Redis-Modules Today I want to you how to do proper debug with Redis modules written in C language. I will be using eclipse Oxygen CPP in order to debug redis module and redis 4. Here there is a video which I recorded with a simple live demo about how to debug a redis-module project and redis. The source code is available on my GitHub . I hope this is useful for you.

Lettuce is a very efficient and extensible Redis client for Java.  Lettuce is interesting for many reasons but one of the big ones is the fact that provides an Observable / Flux API. So you can very efficient reactive programming with RxJava or Reactive-Streams power by Reactor . I'm using lettuce in production in the last 2 years and have been really great. For this blog post, I will how to dispatch custom commands to redis-modules via Lettuce.

Cthulhu is an interesting project. It allows you to code custom redis-modules in JavaScript . This is very interesting because JS is very productive and easy to write code. You might be wondering how they made this efficient? Well, the secret is a project called Duktape which is an efficient JS engine written in C. So Cthulhu + Duktape will pre-compile your javascript function and run it on C which will be efficient and will be able to talk with redis core. Unfortunately, not all functions are available -- you can check the ones that are available here: List of available APIS . You can so a simple comparison with a module In C I wrote some time ago in this blog post . C is way more powerful but also way more error-prone and might take more time to write if you are not used to it. So for this Blog Post, I will how to download and compile Cthulhu and they install in Redis 4 and code some custom function in JavaScript. Let's get started.

Redis is a great K/V store written in C. Redis can accomplish a lot for a single thread process. There are many applications for redis like for instance:  - Frontend Database - Real-time Counters - Ad Serving - Message Queue - Geo and TimeSeries DB - Session State - Cache That's all great but let's say I want more, how can we customize redis? There are some options like a Lua Script , Fork Redis, Tak to @Antirez or Create your own NoSQL database based on redis or not. Redis provided another solution - Redis added support for external modules in 2016.

Dynomite it's a great solution for clustering with NoSQL Databases like Redis . Eureka is a nice Registry & Discoverability Solution. We can get best of both worlds using Prana . Prana is a sidecar that enables non-JVM applications to register in Eureka. Sometimes we could easily use multiple discoverability solutions like DNS, ETCD, Eureka etc... However not all discoverability provide the same benefits some tools are better suited for some jobs them other. I like ETCD and make sense onKubernetes world but if you are doing Java Microservices eureka makes more sense. The triad(Eureka, Prana, Dynomite) is great, This is great because then you can do discoverability on your database nodes, this is not great for several reasons like: Use the same tool for Registry / Discoverability Enable all sorts of dynamic programming which is great for DevOps Engineering Avoid AWS Throttling issues Make dyno clients more dynamic and this is a better solution them DNS like route5...

Go is a simple, fast and powerful programing language. Go is growing a lot into the DevOps Engineering scene like Hashicorp Stack or even Kubernetes .  One of the main advantages of GO is the fact that you can generate a single binary with all you needed, bundled in a single file. This makes distribution so much easier. Go is also very compact for some use cases and you can write so less code and still very very efficient and get best of performance.  Today we will see how to create a very, very, very simple service in go. This service will access redis to increment how many times it was called.  We will use Minikube in order to run kubernetes locally and we will store our data in Redis.

Dynomite is brilliant. Kudos for NetflixOSS team because it kicks ass. First all they mixed several interesting, battle tested and sexy architectural ideas and deliver into a single solution. What would be Dynomite? You can think as a kick Ass Cluster for Memcached and Redis. But its way more than that. Dynomite is integrated with the Netflix Stack so you can use with Eureka and the rest of the stack. You dont need use Redis or Memcached if you dont want because Dynomite is modular so you can use the NoSQL or thing behind it. Dynomite is based on the Amazon Dynamo paper, so it implements the Consistence Hashing Ring, with quorum-like mechanisms, so you can have strong consistency and dont loss data(similar to Cassandra and Riak ) and also have some low latency and high throughput using Redis or Memcached Behind. Dynomite is written in C and its a proxy, it uses the twitter twemproxy as base solution. Replication is a aymetric, dynomite has a java client called Dyno with has...

First all i just want make clear a respect Redis and Salvatore a lot. This is just my view of the topic, no intention to create any kind of FUD or flame war here, just sharing my toughs and experiences. I use redis in production since 2011, its a great piece of technology. Redis has amazing throughput for single instance solution given the fact redis does not have threads(compared with Memcached). Do i recommend use Redis in production? Yes i do :-) Redis: The K/V Solution Whats is Redis? What is good for? Redis is a K/V store and its great for caching. Memcached have few key/set operations in comparison with Redis, there are lots of commands todo very precision operations. Redis cluster was added recently but originally redis was used more like a farm of servers like Memcached case, so replication and other tasks was carry out by the clients apps. Redis has a cluster now. Redis is written in C and has very fast and direct access do data structures like lists, sets and maps. Si...

NOSQL is a movement is around for long time ago but since 2009 is getting stronger and more consistency. Relation data based have they place and they always will have BUT besides the scalability that in some scenarios is more a matter of cost in other Relations Databases is really the wrong choice not just because scalability BUT is a matter of design and complexity X simplicity. The Right structure have a huge impact on the complexity/simplicity of the code and design and have said that this maybe or may not create performance issues. Is a common sens that Relational Databases have beens overused in this last 3 decades. There a debate about the name, my take on that is that is not only SQL and you must consider different databases or data structures in your solution toolbox.