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:
- Connect: Access data from multiple, heterogeneous data sources.
- Compose: Easily combine and transform data into reusable, business-friendly virtual data models and views.
- 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”
Welcome to part 3 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.
When deployed on OpenShift, JDV enables:
- Service enabling your data
- Bringing data from outside to inside the PaaS
- Breaking up monolithic data sources virtually for a microservices architecture
Together with the JDV for OpenShift image, we have made available several OpenShift templates that allow you to test and bootstrap JDV.
Continue reading “Red Hat JBoss Data Virtualization on OpenShift: Part 3 – Data federation”
One of the common requirements for Java based applications on OpenShift is to have these workloads connect back out to an enterprise database that resides outside of the OpenShift infrastructure. While OpenShift natively supports a variety of relational databases (including Postgres and MySQL) as Docker based deployments within the platform, connecting to an existing enterprise database infrastructure is preferred in many large organizations for a variety of reasons including:
- Inherent confidence in traditional databases due to in house experience around developing and managing these databases
- Ability to leverage existing backup/recovery procedures around these databases
- Technical limitations with these databases in being able to be deployed in a containerized model
One of the strengths of the OpenShift platform is its ability to accommodate these “traditional” workloads so that middleware operations can take advantage of the benefits/efficiencies gained from Dockeri’zed applications while giving development teams a platform to start designing/architecting applications that would fit into more of a Microservice based pattern that would leverage a datastore such as MongoDB or MySQL that OpenShift supports.
In addition to that, another common workflow in many organizations from a deployment point of view is to externalize the database connection information so that the application can be migrated from environment to environment (example Dev to QA to Prod) with the appropriate database connection information for the various environments. In addition, these teams typically work with the application binary (.war, .ear, .jar) deployment as the artifact thats promoted between environments as opposed to Docker based images.
In this article, I will walk through an example implementation for achieving this. A sensitive aspect of this migration process are the credentials to the database, where storing credentials in clear text is frowned upon. I will cover a variety of strategies in dealing with this in a follow on article. For this example, I will be using the following project which contains the source code that I will be covering in this article.
Lets get started!
Continue reading “Connecting to a Remote database from a JWS/Tomcat application on OpenShift”
New RHSCL-based Docker images that are now in beta let you easily build your own application containers even without writing any Dockerfiles. Here is an example of a Ruby on Rails application built with the Ruby 2.2 image using the PostgreSQL 9.4 image as a database backend.
Continue reading “Containerize your Ruby on Rails/PostgreSQL application with RHSCL Docker images”
“As a part of the Red Hat Software Collections offering, Red Hat provides a number of container images, which are based on the corresponding Software Collections. These include application, daemon, and database images. The provided images, currently available in the Beta version” (for more information see https://access.redhat.com/articles/1752723)
Red Hat Software Collections allows you to run newer versions of software on a stable Red Hat Enterprise Linux. These new images combine this feature with the benefits of containers.
In this post I would like to show you how to run database server from RHSCL in one command.
Continue reading “Database Docker images – now beta via Software Collections”
I’m very happy to announce that Docker images based on collections from Red Hat Software Collections (RHSCL) 2.0 are in beta testing. The images are available from the Red Hat Container Registry, and we’ve got the set of collections for language, databases and web servers covered – a complete list is below.
If you’ve not tried out the Docker package from RHEL7 Extras, you need to enable the Extras channel, install the docker page, and start the docker service; an extended guide for RHEL Docker is available here. Once you are set up, pulling the RHSCL Docker images is very simple… for example, you can fetch the Python 3.4 image as follows:
Continue reading “Red Hat Software Collections 2.0 Docker images, Beta release”
Excellent news – Red Hat has announced the general availability of Red Hat Software Collections 2.
You’ll see considerable additions to support multiple language versions. For example, it includes updates to “Python 2.7, continues to support Python 3.3 and also adds Python 3.4 – providing a fully-supported language library and blending developer agility with production stability.”
Continue reading “Red Hat Software Collections 2 – now generally available”