Edson Yanaga
From Red Hat
Edson Yanaga, Red Hat's Director of Developer Experience, is a Java Champion and a Microsoft MVP. He is also a published author and a frequent speaker at international conferences, discussing Java, Microservices, Cloud Computing, DevOps, and Software Craftsmanship.
Yanaga considers himself a software craftsman, and is convinced that we all can create a better world for people with better software. His life's purpose is to deliver and help developers worldwide to deliver better software faster and safely - and he can even call that a job!
Blog: http://www.yanaga.me
Server Side Java
Scars from the Journey: Crafting Clean & Effective Java EE applications with DDD
Ever seen Service classes with hundreds or maybe thousands of LOC cluttered with validation logic, DAO access and some business code? Tired of getting NullPointerExceptions and having to check everything with if != null? Filled up of recurring bugs that could be prevented by unit tests, but your code is simply too clumsy to test effectively? Then you definitely should check this session.
We'll show how Domain-Driven Design, proper encapsulation, immutability, Value Objects, Entities and Aggregates, Repositories and Specifications can help you solve all of these problems. Already knew these concepts but never figured out how to proper apply them in production code? We have these answers with a lot of tips & tricks from the real world. Don't miss this 100% live code where we'll craft an application from the database to the view using Domain-Driven Design, Clean Code and Effective Java on top of Java 8 and Java EE 7. You'll never see your code the same way again.
REQUIREMENTS: https://github.com/yanaga/scars-from-the-journey
Architecture & Security
Migrating to Microservice Databases: From Relational Monolith to Distributed Data
"In a Microservices architecture with multiple moving parts we can’t allow that a single complement downtime breaks down the entire system. Dealing with stateless code is easy, but it gets much harder when we have to deal with persistent state. In this scenario, zero downtime migrations are paramount to guarantee integrity and consistency.
Within all the Microservices characteristics, undoubtedly the one that creates more perplexity is the “one database per Microservice”. However, very few teams have the privilege of starting something from scratch: most of the times they have a legacy database that will survive any new implementation.
In legacy systems you traditionally have a model that adopts transactions and CRUD. Now we must reassess some of these concepts. In this talk we’ll discuss consistency, CRUD and CQRS, Event Sourcing, and how these techniques relate to each other in many different integration strategies for databases. We’ll explore Views, Materialized Views, Mirror Tables, Event Sourcing, Data Virtualization, Change Data Capture, and how these strategies enable you to build up a Microservices architecture from a legacy monolithic relational database."
Architecture & Security
Migrating to Microservice Databases: From Relational Monolith to Distributed Data
In a Microservices architecture with multiple moving parts we can’t allow that a single complement downtime breaks down the entire system. Dealing with stateless code is easy, but it gets much harder when we have to deal with persistent state. In this scenario, zero downtime migrations are paramount to guarantee integrity and consistency.
Within all the Microservices characteristics, undoubtedly the one that creates more perplexity is the “one database per Microservice”. However, very few teams have the privilege of starting something from scratch: most of the times they have a legacy database that will survive any new implementation.
In legacy systems you traditionally have a model that adopts transactions and CRUD. Now we must reassess some of these concepts. In this talk we’ll discuss consistency, CRUD and CQRS, Event Sourcing, and how these techniques relate to each other in many different integration strategies for databases. We’ll explore Views, Materialized Views, Mirror Tables, Event Sourcing, Data Virtualization, Change Data Capture, and how these strategies enable you to build up a Microservices architecture from a legacy monolithic relational database.