New Release of Red Hat JBoss Data Virtualization.

Red Hat is proud to announce the release of JBoss Data Virtualization (JDV) 6.4

Overview

JBoss Data Virtualization is a data integration solution that sits in front of multiple data sources and allows them to be treated as a single source, delivering the right data, in the required form, at the right time to any application and/or user.

JDV 6.4 Features

The JBoss Data Virtualization 6.4 release focuses on supporting new and updating existing cloud, big data, and in-memory data sources.

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JBoss Data Virtualization: Integrating with Impala on Cloudera

Cloudera Impala is a tool to rapidly query Hadoop data in HBase or HDFS using SQL syntax.  You can use Red Hat JBoss Data Virtualization to query that same data via Impala to take advantage of its optimization. You can also combine that data with other data sources in real time.  The goal of this guide is to import data from a Cloudera Impala instance, manipulate it, and then expose that data as a data service.  This guide includes access to a repository with example scripts, creating a custom base and view model, exposing it as a data service, and finally consuming that data via REST. This is a peer article to Unlock Your Cloudera Data with Red Hat JBoss Data Virtualization.

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Integrate RH-SSO 7.x with Liferay DXP using SAML

The aim of this tutorial is to configure Red Hat Single Sign On (RH-SSO) to work as an Identity Provider (IdP) for Liferay DXP through SAML.

Liferay DXP supports functionalities for Single Sign On (SSO) such as NTLM, OpenID, and Token-based and integration with IdPs like Google and Facebook. But when it comes to enterprise environments, the requirements may be stricter, especially regarding integration with externals IdPs.

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Enabling Byteman Script with Red Hat JBoss Fuse and AMQ – Part 2

In my previous article, Enabling Byteman Script with Red Hat JBoss Fuse and AMQ – Part 1, we found a basic use-case for Byteman scripts with Red Hat JBoss Fuse or Red Hat JBoss AMQ. However, the log file was generated separately and only limited operations were possible. In this article I will show you how to use a Java helper class. By using Java, we get advanced operations to view or modify the content. Also, using java.util.logging allows us to log the statements to fuse.log, avoiding the creation of any other log file.

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Which Camel DSL to Choose and Why?

Apache Camel is a powerful integration library that provides mainly three things: lot’s of integration connectors + implementation of multiple integration patterns + a higher-level Domain Specific Language (DSL) abstraction to glue all together nicely. While the connectors and pattern choices are use case and feature driven and easy to make, choosing which Camel DSL to use might be a little hard to reason about. I hope this article will help to guide you in your first Camel journey.

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Hexagonal Architecture as a Natural fit for Apache Camel

There are architectures and patterns that look cool on paper, and there are ones that are good in practice. Implementing the hexagonal architecture with Camel is both: cool to talk about, and a natural implementation outcome. I love going hexagonal with Camel because it is one of these combinations where the architecture and the tool come together naturally, and many end up doing it without realizing it. Let’s see why that is the case.

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