postgresql

Announcing GA for latest Software Collections, Developer Toolset, Compilers

Announcing GA for latest Software Collections, Developer Toolset, Compilers

We are pleased to announce the general availability of:

  • Red Hat Software Collections 3.1 (including Ruby 2.5, Perl 2.26, PHP 7.0.27, PostgreSQL 10, MongoDB 3.6, Varnish 5, HAProxy 1.8, Apache 2.4 update)
  • Red Hat Developer Toolset 7.1 (GCC 7.3)
  • Clang/LLVM 5.0, Go 1.8.7, Rust 1.25.0

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Red Hat open source databases in beta: Adds PostgreSQL 10, MongoDB 3.6; updates MySQL 5.7

Red Hat open source databases in beta: Adds PostgreSQL 10, MongoDB 3.6; updates MySQL 5.7

Twice a year, Red Hat distributes new versions of compiler toolsets, scripting languages, open source databases, and/or web tools, etc. so that application developers will have access to the latest, stable versions. These Red Hat supported offerings are packaged as Red Hat Software Collections (scripting languages, open source databases, web tools, etc.), Red Hat Developer Toolset (GCC), and the recently added compiler toolsets Clang/LLVM, Go, and Rust. All are yum installable, and are included in most Red Hat Enterprise Linux subscriptions and all Red Hat Enterprise Linux Developer Subscriptions. Most Red Hat Software Collections and Red Hat Developer Toolset components are also available as Linux container images for hybrid cloud development across Red Hat Enterprise Linux, Red Hat OpenShift Container Platform, etc.

Red Hat Software Collections 3.1 beta brings the following new/updated open source databases:

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Red Hat updates Python, PHP, Node.js, more; supports new arches

Red Hat updates Python, PHP, Node.js, more; supports new arches

I am pleased to announce the immediate availability of Red Hat Software Collections 3.0 Beta, Red Hat’s newest installment of open source development tools, dynamic languages, databases, and more. Delivered on a separate lifecycle from Red Hat Enterprise Linux with a more frequent release cadence, Red Hat Software Collections bridges development agility and production stability by helping you create modern applications that can be confidently deployed into production. Most of these components are also available in Linux container image format to streamline microservices development.

In addition to these new components having traditional support for x86_64, Red Hat Software Collection 3.0 Beta adds support for three new architectures: s390x, aarch64, and ppc64le.

NEW ADDITIONS to Red Hat Software Collections 3.0 Beta include:

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Unlock your PostgreSQL data with Red Hat JBoss Data Virtualization

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.

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Red Hat JBoss Data Virtualization on OpenShift: Part 3 – Data federation

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:

  1. Service enabling your data
  2. Bringing data from outside to inside the PaaS
  3. 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.

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Connecting to a Remote database from a JWS/Tomcat application on OpenShift

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!

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Containerize your Ruby on Rails/PostgreSQL application with RHSCL Docker images

Containerize your Ruby on Rails/PostgreSQL application with RHSCL Docker images

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.

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Database Docker images – now beta via Software Collections

Database Docker images – now beta via Software Collections

“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.

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Red Hat Software Collections 2.0 Docker images, Beta release

Red Hat Software Collections 2.0 Docker images, Beta release

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:

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