spring

Writing better Spring applications using SpringFu

Writing better Spring applications using SpringFu

“Truth can only be found in one place: the code,” Robert C. Martin, Clean Code: A Handbook of Agile Software Craftsmanship.

The way we structure our code has a direct impact on how understandable is it. Code that is easy to follow with no or less hidden functionality is much easier to maintain. It also makes it easier for our fellow programmers to track down bugs in the code. This helps us to avoid Venkat’s Jesus Driven Development.

The way I write Spring applications comprises heavy use of Spring annotations. The problem with this approach is that partial flow of the application is controlled by annotations. The complete flow of my code is not in one place, that is, in my code. I need to look back to the documentation to understand the annotations’ behavior. By reading just the code, it is difficult to predict the flow of control.

Luckily, Spring has a new way to code to and it has been called Spring Functional or SpringFu. In this article, I will use Kotlin to showcase some of the benefits you get from SpringFu.

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Extending support to Spring Boot for Red Hat OpenShift Application Runtimes

Extending support to Spring Boot for Red Hat OpenShift Application Runtimes

What Red Hat is providing

Red Hat OpenShift Application Runtimes (RHOAR) is a recommended set of products, tools, and components for developing and maintaining cloud-native applications on the Red Hat OpenShift platform. As part of this offering, Red Hat is extending its support to Spring Boot and related frameworks for building modern, production-grade, Java-based cloud-native applications.

Spring Boot lets you create opinionated Spring-based standalone applications. The Spring Boot runtime also integrates with the OpenShift platform, allowing your services to externalize their configuration, implement health checks, provide resiliency and failover, and much more. To learn more about how Spring Boot applications integrate with the wider Red Hat portfolio, check out the following OpenShift Commons Briefing by Thomas Qvarnstrom:

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Camel Clustered File Ingestion with JDBC and Spring

Camel Clustered File Ingestion with JDBC and Spring

Reading a file is a common use for Apache Camel. From using a file to kick off a larger route to simply needing to store the file content, the ability to only read a file once is important. This is easy when you have a single server with your route deployed, but what about when you deploy your route to multiple servers. Thankfully, Camel has the concept of an Idempotent Consumer.

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The CoolStore Microservices Example: DevOps and OpenShift

The CoolStore Microservices Example: DevOps and OpenShift

An introduction to microservices through a complete example

Today I want to talk about the demo we presented @ OpenShift Container Platform Roadshow in Milan & Rome last week.

The demo was based on JBoss team’s great work available on this repo:
https://github.com/jbossdemocentral/coolstore-microservice

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