Thoughts on my own. Posts not reflect the opinions of my past or current employers. More about me: diegopacheco.github.io
Feature Enrichment with Spring Data Redis and Lettuce
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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.
Video
Code
Model
Our model is pretty simple. Simple Person POJO with Getters/Setters, toString, equals/hashCode all generated by Idea. You can see there is a custom annotation called UpperCase. The idea is to add custom features enrichment and make sure some fields are stored in the Upper case.
Annotation
Now let's look at the annotation.
Custom Repository
Here is where the magic happens. I wrapped all CurdRepository operations and I'm delegating to the proper CrudRepository implementation at the end of the day. However I', also I have a reflection code that adds the feature enrichment I want based on the existence of the UpperCase annotation at the Entity fields.
Kafka Streams is a Streaming library similar to Spark and Flink which works with Apache Kafka. Kafka stream can be useful to process historical and near-real-time big data workloads but also for non-realtime analytical computations at scale for the online world as well. Kafka-Streams is elastic, highly scalable, fault-tolerant, and fully integrated with Kafka. You can use Kafka Stream with Java, Scala, Kotlin JVM applications and also have exactly-once processing semantics. Kafka-Streams is being used by the New York Times, Pinterest, Line, Trivago, Zalando, and many other companies. Today I want to share a video of Kafka-Streams running with Kafka 2.6 and Java JDK 15. So Let's get started.
Rust does not stop for one second to amaze me. It looks like Rust was designed to talk to every other language so easily. No kidding, it's clear way Web Assembly and rust have lots in common. Java is never an easy lang to interop with. Today I will show how easily we can interop Java & Rust. In order to do so, we will need to use the Java and Rust compilers. For Java, we will not require any other lib than the standard JDK. For Rust, we will need to create a lib project in cargo and we will need to use the crate JNI. I love this feature because java does not allow low-level code on the main language. So if we need to do something low level, efficiently Rust is my first choice, not only for safety reasons but because is really fast. Let's get started.
In 2018 AWS CTO(Vogels) said : "Security is everyone's job". For the last 2 years, there was so many famous and big data leaks and breaks that made that statement be very true more than ever. Security often could mean worst performance and worst user experience so in order to get it right you really need to think about the designs before jumping into to code and consider performance and user experience has main requirements. I was thinking about writing about how to do HMAC in Java for a while and recently Redis 6.0.0 come out and to my surprise, there was a refactoring on the password part in order to use HMAC. Security easily could scare engineers often because it is not something well spread yet but I believe this will change soon. It does not matter if you have to deal with PII Data or not, security is super relevant because everybody is running their workloads at the cloud or with IoT and Edge devices which means more distribution, more code, more points of fail
