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Ingénieurs études et développement Java Jee
Nous recrutons des ingénieurs JAVA/JEE ayant une expérience de 4 ans et plus. Technologies requises – J2EE : Spring, Spring-boot, Hibernate, JPA, Webservices Rest, Git, TestNG, Liquibase, Jenkins, Nexus, Unix, JavaScript, AngularJS
Envoyer vos CVs à l’adresse email : [email protected]
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Versiona tu base de datos con #Liquibase en Spring Boot. Te muestro cómo registrar cambios, automatizar migraciones y mantener tus BBDD siempre bajo control. Ideal para proyectos profesionales y microservicios. #Java https://youtu.be/PHHjj-r_2pQ Nota: imagen generada con IA generativa.
Getting Started with Liquibase and Spring Boot
Introduction Liquibase is a popular database schema version control tool that allows you to manage your database changes in a more efficient and automated way. Take a look at our tutorial to get more details about liquibase and database version control: Database Version Control with Liquibase: A Complete Guide. Spring Boot is a powerful Java framework for building microservices and web…
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Explore Liquibase, your database version control tool, for simplified database management and version control in software development.
Database Version Control with Liquibase: A Complete Guide
Introduction: In today’s fast-paced software development landscape, managing database schema changes efficiently is crucial for maintaining the integrity and consistency of applications. Liquibase, a popular open-source database version control tool, empowers developers to automate and streamline the process of managing database changes. In this detailed guide, we’ll explore Liquibase…
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This post is part of a new blog series about database migrations, which will cover a variety of database change management topics. In the ne
Evolutionary Database Design Retrospective
The team I work with has been using Liquibase to manage database refactoring for just over a year now, this is a summary of my impressions on that experience. Everything I write is just as applicable to Flyway or any other migration tool.
So some background... The idea of our PostgreSQL database migrations living along with the code became a big topic around the office about four years ago. Through some staff changes, working with our DBAs to apply migrations was becoming a deep slog through red tape. So right off the bat our target was to simplify deploys and work around DBA policies, not necessary implement any other tenants of continuous delivery, or necessarily adopt the requisite “best practices” around Evolutionary DB Design. Kick ass right.
So the tooling we implemented was simple. Allow a developer to spin-up a local Postgres instance with appropriate customization's using Docker and apply schema and test data through a DB project on the trunk. The developer can build migrations, apply them locally and write simple unit tests to verify them. The migrations and tests are checked in together. A CI job builds the DB project (just applies migrations and runs tests) and is a prerequisite to the code being promoted to an environment just like any other unit test. Deployments apply migrations through Liquibase and version information is available through the Liquibase table in the public schema.
I believe the implementation is good. Some pluses are:
+ Agile teams write and test DB migrations as the team see fit, without any DBA’s on the team. (some might see this as a minus, in my experience it is a plus)
+ Migrations are applied though the deployment pipeline the same way. Any issues typically show up before anything gets close to production.
+ DB’s have a definite version which can be quantified and labeled/branched/released.
+ Databases roll forward!
Some Minuses:
- Evolutionary DB Design works as a part of a continuous delivery strategy. To adopt one part of continuous delivery without working toward the goal of constantly pushing software complicates some of the design decisions of the tooling. For example:
- No Rollbacks! We don’t do rollbacks. They are impossibly hard to test and unpredictable, we only roll forward. This is an inconceivable concept to to someone who has not embraced agile development methodology. “You are giving the database a version, then why cant I go back to an older version? I don’t get it.” Its been a year plus and I still have to explain this to managers and other new engineers on a monthly basis.
- Long release cycles mean large numbers of migrations, this means longer test cycles and greater risk during deploys. Again, you should be pushing often.
- Developers don’t like to test. Maybe this is just my team but in general the majority of developers feel like writing tests is a waste of time for them. If we did more pairing and XP I don’t think this would not be an issue.
So overall its been very positive. I would suggest NOT adopting this practice as a first step to continuous delivery otherwise it’s pretty neat.
Full-Stack Automated Deployments
When we set out to create a standard development and delivery platform four years ago, providing Continuous Delivery-style automated application deployment was a key design requirement. This was for all the usual reasons: greater efficiency, increased velocity, reduced risk, lower cost, improved reliability.
Achieving automated deployment has been a multifaceted effort, and the first visible results came from employing Chef cookbooks and Jenkins jobs to manage deployment and configuration of our portfolio of custom Java applications. We presented on this topic at the 2014 Jenkins User Conference in Boston.
In parallel, we were laying the groundwork for automated database migrations with tools such as Liquibase and Gradle. Management of database schema changes is a source of difficulty for many organizations, and including it in our “push-button” deployment process has provided significant savings of time and effort. Recently we shared the database side of our automated deployment story at the 2015 Gradle Summit in Santa Clara. The slides and video recording are available.
Now we have full-stack automated deployments and are reaping the expected benefits:
Empowerment of individual product development teams via self-service deployments
Significant reduction in DEV-to-TEST time delay
Reduced workload for IT Operations team
More reliable and frequent software releases
Time to invest in additional high-value initiatives
Dan Stine CCC Platform Engineering
