Getting Started with Red Hat Decision Manager 7

The all new and shiny Red Hat Decision Manager 7 has been recently released. Decision Manager 7 is the successor to Red Hat JBoss BRMS, our business rules and decision management platform. In this post we will have a look at the primary new features and provide instructions on how to get started with the new platform, either on your local machine or in an OpenShift Container Platform.

Red Hat Decision Manager 7 focuses on four main themes: Fit & Finish, Cloud-Native, Decision Model and Notation (DMN), and Business Optimizer.

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Next DevNation Live: Camel Riders in the Cloud, March 15th, 12pm EDT

The next online DevNation Live Tech Talk will be Thursday, March 15th at 12pm EDT. The topic is Camel Riders in the Cloud presented by Claus Ibsen

Apache Camel has fundamentally changed the way enterprise Java™ developers think about system-to-system integration. It makes it easy to apply enterprise integration patterns (EIP) using simple declarations. The result is a lightweight application that is wrapped and delivered as a single JAR.

In this session, we’ll show you how to apply the best practices from the enterprise integration world to build microservices that are deployed as Linux® containers, running on top of Kubernetes and Red Hat OpenShift. These integration applications will be both cloud-native and cloud-portable.

Register now and join the live presentation at 12pm EDT, Thursday, March 15th. 

Note: For those outside of the US, daylight savings time started this week, so the US East coast is now UTC – 4.

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Structured application logs in OpenShift

Logs are like gold dust. Taken alone they may not be worth much, but put together and worked by a skillful goldsmith they may become very valuable. OpenShift comes with The EFK stack: Elasticsearch, Fluentd, and Kibana. Applications running on OpenShift get their logs automatically aggregated to provide valuable information on their state and health during tests and in production.

The only requirement is that the application sends its logs to the standard output. OpenShift does the rest. Simple enough!

In this blog I am covering a few points that may help you with bringing your logs from raw material to a more valuable product.

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Containerizing SQL DB changes with Flyway, Kubernetes, and OpenShift

In DevOps projects, you are sometimes haunted by the practices inherited from the monolithic world. In a previous project, we were checking how to simply apply SQL updates and changes to a relational database management system (RDBMS) database in an OpenShift Cluster.

Micro database schema evolution patterns are perfectly described by Edson Yanaga in his brilliant free book: Migrating to Microservice Databases: From Relational Monolith to Distributed Data.  A video presentation of these patterns is also available on youtube.

In this blog post series we will show a simple approach to implement the described patterns in your Continuous Integration and Continuous Delivery (CI/CD) pipelines on OpenShift. The series is split in two parts:

  • This post shows how to handle SQL update automation using Flyway, Dockerfiles, and Kubernetes on OpenShift.
  • A future post will showcase application migration patterns, including database migration stages using OpenShift Jenkins2 pipelines.

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