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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Technical How-to Books for Developers – Microservices, Design Patterns, .NET, Reactive, Databases

Within Red Hat knowledge sharing and collaboration are important.  As a part of that many Red Hatters write books and we get the honor of sharing their knowledge with other developers.  We have 7 more books in queue for the coming year and thought we would share the books you can currently download.

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Unlock your Microsoft Excel data with Red Hat JBoss Data Virtualization

After Unlock your MariaDB/MySQL data, Unlock your PostgreSQL data, and Unlock your Hadoop data with Hortonworks episodes, let’s continue the journey with this new episode of the series: “Unlock your [….] data with Red Hat JBoss Data Virtualization.” Through this blog series, we will look at how to connect Red Hat JBoss Data Virtualization (JDV) to different and heterogeneous data sources.

JDV is a lean, virtual data integration solution that unlocks trapped data and delivers it as easily consumable, unified, and actionable information. It makes data spread across physically diverse systems — such as multiple databases, XML files, and Hadoop systems — appear as a set of tables in a local database. By providing the following functionality, JDV enables agile data use:

  1. Connect: Access data from multiple, heterogeneous data sources.
  2. Compose: Easily combine and transform data into reusable, business-friendly virtual data models and views.
  3. Consume: Makes unified data easily consumable through open standards interfaces.

It hides complexities, like the true locations of data or the mechanisms required to access or merge it. Data becomes easier for developers and users to work with.

This post will guide you step-by-step on how to connect JDV to a Microsoft Excel spreadsheet using Teiid Designer and the Microsoft Excel translator. A translator acts as the bridge between JBoss Data Virtualization and an external system. The Microsoft Excel translator provides a quick and easy way to read a Microsoft Excel spreadsheet and provides contents of the spreadsheet in the tabular form that can be integrated with other sources.

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Red Hat JBoss Data Virtualization on OpenShift: Part 4 – Bringing data from outside to inside the PaaS

Welcome to part 4 of Red Hat JBoss Data Virtualization (JDV) running on OpenShift.

JDV is a lean, virtual data integration solution that unlocks trapped data and delivers it as easily consumable, unified, and actionable information. JDV makes data spread across physically diverse systems such as multiple databases, XML files, and Hadoop systems appear as a set of tables in a local database.

Continue reading “Red Hat JBoss Data Virtualization on OpenShift: Part 4 – Bringing data from outside to inside the PaaS”

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Unlock your PostgreSQL data with Red Hat JBoss Data Virtualization

And here we go for another episode of the series: “Unlock your [….] data with Red Hat JBoss Data Virtualization.” Through this blog series, we will look at how to connect Red Hat JBoss Data Virtualization (JDV) to different and heterogeneous data sources.

JDV is a lean, virtual data integration solution that unlocks trapped data and delivers it as easily consumable, unified, and actionable information. It makes data spread across physically diverse systems — such as multiple databases, XML files, and Hadoop systems — appear as a set of tables in a local database. By providing the following functionality, JDV enables agile data use:

  1. Connect: Access data from multiple, heterogeneous data sources.
  2. Compose: Easily combine and transform data into reusable, business-friendly virtual data models and views.
  3. Consume: Makes unified data easily consumable through open standards interfaces.

It hides complexities, like the true locations of data or the mechanisms required to access or merge it. Data becomes easier for developers and users to work with. This post will guide you step-by-step on how to connect JDV to a PostgreSQL database using Teiid Designer. We will connect to a PostgreSQL database using the PostgreSQL JDBC driver.

Continue reading “Unlock your PostgreSQL data with Red Hat JBoss Data Virtualization”

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Unlock your MariaDB/MySQL data with Red Hat JBoss Data Virtualization

Welcome back to a new episode of the series: “Unlock your [….] data with Red Hat JBoss Data Virtualization.” Through this blog series, we will look at how to connect Red Hat JBoss Data Virtualization (JDV) to different and heterogenous data sources.

JDV is a lean, virtual data integration solution that unlocks trapped data and delivers it as easily consumable, unified, and actionable information. It makes data spread across physically diverse systems — such as multiple databases, XML files, and Hadoop systems — appear as a set of tables in a local database. By providing following functionality, JDV enables agile data use:

  1. Connect: Access data from multiple, heterogeneous data sources.
  2. Compose: Easily combine and transform data into reusable, business-friendly virtual data models and views.
  3. Consume: Make unified data easily consumable through open standards interfaces.

It hides complexities, like the true locations of data or the mechanisms required to access or merge it. Data becomes easier for developers and users to work with.

This post will guide you step-by-step how to connect JDV to a MariaDB/MySQL database using Teiid Designer. We will connect to a MariaDB 10.1 server using MySQL Connector/J 5.1, a JDBC driver for communicating with MariaDB/MySQL servers. Indeed, you can follow this same tutorial with a MySQL instance.

Continue reading “Unlock your MariaDB/MySQL data with Red Hat JBoss Data Virtualization”

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