Enhanced containerized integration services on OpenShift: Red Hat JBoss Fuse Integration Services

Updated and enhanced integration services are now available on Red Hat OpenShift. A containerized, formatted version of Red Hat JBoss Fuse 6.3 is now available for simplified deployments on OpenShift instances.

Technology is shifting so rapidly — from cloud-based architectures, Internet of Things and a variety of devices for interaction, new data streams, and mobile apps, to name a few — that organizations have to be able to create and deploy applications and process data quickly. Traditional, monolithic systems and top-heavy ESB-style integration approaches tend to be too slow and rigid to enable this level rapid innovation.

That is where an agile integration framework like JBoss Fuse can be a foundational element in your IT and digital strategy. Agile integration has three core capabilities: distributed integration, containers, and an API-based architecture.

  1. JBoss Fuse uses the lightweight distributed integration patterns of the underlying Apache Camel project.
  2. As part of the JBoss middleware services on OpenShift, JBoss Fuse is available for rapid deployment within container and cloud environments. Red Hat OpenShift is based on Docker and Kubernetes. Container architectures allow developers to build and integrate traditional and microservices-based applications at scale quickly.
  3. JBoss Fuse can be used together with Red Hat 3scale API Management Platform as an engine to develop and deploy APIs, both internally to development groups and externally for customer and partner ecosystems.

Integration technologies help organizations build on their existing infrastructures even as they pivot to new cloud-based and service-based architectures.

Features (and Benefits) at a Glance

  • Spring Boot support
  • Custom-developed, containerized applications based on Apache Camel 2.18
  • Integration with Hystrix and Zipkin microservices frameworks
  • An optimized integration environment for microservices applications on Red Hat OpenShift
  • Path to transition off existing Apache Karake-based applications to cloud architectures
  • Consistent hybrid integration platform across their enterprise

More Information

Red Hat launches 3scale APIcast – faster, flexible, open source API gateway

Dockerized version of APIcast 2.0 deploys on OpenShift for easier installation and operation in microservice environments

Today we’re happy to announce the general availability of Red Hat 3scale APIcast gateway 2.0. The APIcast gateway (NGINX-based) is open source and has served hundreds of happy customers over the last four years. Now we’ve taken it to the next level, supporting both a cloud gateway or hybrid model with an on-prem gateway. In fact, the new on-premise version introduces significant upgrades in terms of performance and flexibility. 3scale was the first in market with on-prem and now we are pleased to offer the second generation.

The API gateway, which is configured within 3scale’s Admin Portal, is part of the 3scale API Management SaaS offering. The Admin Portal allows customers to define desired authentication methods, set rate limits, get analytics on the usage of their APIs, and create a developer portal for their API consumers. APIcast 2.0  is the first of two on-prem releases. With the upcoming 3scale on-premise release, customers will be able to deploy the entire 3scale API Management Platform on-premises. Stay tuned!

Companies are increasingly migrating to microservices architecture, so the average number of API services managed with 3scale have significantly increased, and continue to do so. To accommodate to these requirements, APIcast changes the way it pulls the configuration from the Admin Portal. For starters, now it’s now possible to pull the configuration for just a subset of services. In addition, it makes it easier to automate the deployment of multiple gateways by providing the gateway configuration via a JSON file which can be fetched by an API. It also supports two environments out-of-the-box (staging and production) with options to enable always-up-to-date configs in staging, and control of updates in production. For example, you can set the reload config variable to true so it reloads the API gateway configuration with each request, which comes in handy during development phases.

Another big change introduced with APIcast 2.0 is the enhanced integration with Red Hat’s OpenShift Container Platform, which leverages Docker and Kubernetes for an easier deployment and DevOps experience. The new OpenShift template pulls the dockerized image of APIcast from the Red Hat container registry and lets you enable/disable key features of the API gateway by just changing the value of the corresponding template parameter.

Get started with APIcast 2.0:

How to integrate business logic in processes with JBoss BPM

In June 2016 the Manning Early Access Program (MEAP) started for the book Effective Business Process Management with JBoss BPM.

What is a MEAP?

The Effective Business Process Management with JBoss BPM MEAP gives you full access to read chapters as they are written, get the finished eBook as soon as it’s ready, and receive the paper book long before it’s in bookstores.

You can also interact with the author, that’s me, on the forums to provided feedback as the book is being written. So come on over and get started today with Effective Business Process Management with JBoss BPM.

The way the MEAP works is that every month or so Manning puts a new chapter online. As of this week chapter 5 is available and those already in the MEAP will have access to start reading the chapter.

This is a large chapter and it is one of the harder topics to confine to a single chapter. I do expect to split this chapter up in the future so that you have the basics and then more advanced topics regarding learning to effectively implement your business logic with JBoss BPM.

To give you an idea of what’s available so far:

You can read this excerpt online before you decide, but I look forward to hearing from you on the content and stay tuned for more.

 

See more by Eric D. Schabell, contact him on Twitter for comments or visit his home site.

Announcing Red Hat JBoss Data Virtualization 6.3

We are excited to announce the release of Red Hat JBoss Data Virtualization 6.3.

Data integration has always been challenging. Modern technology trends like big data and cloud, coupled with the need for more real time data access and analysis, are adding to the complexity facing enterprises today.

JBoss Data Virtualization is a data access and integration solution that offers an alternative to physical data consolidation and data delivery by allowing flexibility and agility in data access. Data virtualization creates a single logical view of data from varied data sources, including transactional systems, relational databases, cloud data stores, and big data stores.

What’s New in JDV 6.3

JBoss Data Virtualization 6.3 adds capabilities to help organizations integrate big data and provide high performance data access in real time.  The release notes cover the full features and enhancements for JBoss Data Virtualization 6.3. There are a number of new features to enable expanded connectivity, enhanced security and developer productivity support.

Continue reading “Announcing Red Hat JBoss Data Virtualization 6.3”

Announcing Red Hat JBoss Data Grid 7.0

Red Hat JBoss Data Grid 7.0 is here.

This significant new release offers a variety of features which are designed for complex, distributed, and high-volume, velocity data requirements. JBoss Data Grid can support both on-premise and cloud-based infrastructures, and it can handle the near-instantaneous, complex demands of Internet of Things and big data environments.

What It Brings

JBoss Data Grid can be deployed in different architectures, depending on the needs of your environment. In addition to the traditional usage as distributed cache, in-memory data grids can function as the primary data store for applications or as a compute grid for distributed computing.

Data Storage

There are two use cases for using JBoss Data Grid as a data store:

  • Data caching and transient storage. As an in-memory data store for frequently accessed application data or for transient data, such as shopping cart information or session data. This avoids hitting transactional backend systems are frequently, which reduces operating costs.
  • Primary data store. Data Grid can function as a key-value store similar to a NoSQL database. This can be the primary data source for applications for rapid retrieval of in-memory data and to persist data for recovery and archiving. Applications can run data-intensive operations like queries, transaction management, and distributed workloads.

Computing Grid

Modern architectures require flexible, distributed, and scalable memory and data storage. Using JBoss Data Grid as a distributed computing grid can help support the most demanding architectures:

  • Scale-out compute grid and event-driven computing. Through storage node clusters, JBoss Data Grid can do a distributed architecture with application logic at each node for faster data processing and lower latency and traffic. This architecture also supports event-driven computing by executing application logic at the node as data are updated.
  • Big data and the Internet of Things. JBoss Data Grid can support massive data streams — hundreds of thousands of updates per second. The Internet of Things can have data streams from thousands of connected devices, updating frequently. Clustering and scale, application logic and processing, and both in-memory and persistent storage in JBoss Data Grid enable those big data architectures by managing those massive data streams.

Real-Time Analytics and Performance for Digital Business

DIgital transformation means that organizations are pushing into a new intersection between their physical goods or services and online, on-demand applications. This digital environment is reliant on data — and unlike previous generations, this technology uses -near live data streams rather than historical data collections.

JBoss Data Grid is a leading high-performance, highly-scalable, in-memory data grid. In-memory data grids provide a means of scalable memory so that even rapidly changing application data can be processed.  Better data processing and management enables organizations to make fast, accurate decisions using large data streams. JBoss Data Grid 7.0 offers a data foundation for real time analytics:

  • Low latency data processing through memory and distributed parallel execution
  • Data partitioning and distribution across cluster nodes for horizontal scalability
  • High availability through data replication
  • Shared data services for real-time and in-memory analytics and event processing

A Short List of Major Features

The release notes cover the full features and enhancements for JBoss Data Grid 7.0. There are a number of features for improved ease of use, real-time analytics, and language support:

  • Distributed streams, which uses the Java 8 Stream API to take complex collections of data and run defined analytics operations.
  • Resilient distributed dataset (RDD) and DStream integration with Apache Spark 1.6, allowing Data Grid to be a data source for Spark and to execute Spark and Spark Streaming operations on data in Data Grid.
  • Hadoop InputFormat/OutputFormat integration, so that Hadoop tooling and oeprations can be used with data stored in Data Grid.
  • New administrative consoles for cluster management to simplify common tasks for managing the cache, nodes, and remote tasks.
  • Control operations for clusters including graceful shutdowns and startup and restores from persistent storage.
  • A new Node.js Hot Rod client to support using Data Grid as a NoSQL database with Node.js applications.
  • Running remote tasks (business logic) on a Data Grid server from the Java Hot Rod client.
  • Support for a Cassandra cache store, which persists the entries of a distributed cache on a shared Apache Cassandra instance.

Additional Resources

Announcing Red Hat JBoss Data Grid 7.0 Beta

We are very excited to announce availability of Red Hat JBoss Data Grid (JDG) Version 7.0 Beta!

Based on the Infinispan project, JBoss Data Grid is a leading high-performance, highly-scalable, in-memory NoSQL store, which enables your enterprise to make fast, accurate decisions on large volumes of changing data and provides superior user experience for your customer-facing applications.

JDG 7.0 Beta introduces major new features in the areas of Real-time Data Analytics, ease of use and administration, and expanded polyglot support.

Real-Time Data Analytics

  • Distributed Streams: In JDG 7.0, we introduce a distributed version of the Java 8 Stream API which enables you to perform rich analytics operations on data stored in JDG using the functional expressions available in the Stream API.
  • Apache Spark and Hadoop Integration: JDG 7.0 features a new Resilient Distributed Dataset (RDD) and DStream integration with Apache Spark version 1.6. This enables you to use JDG as a highly scalable, high-performance data source for Apache Spark, executing Spark and Spark Streaming operations on data stored in JDG. We have also added a Hadoop InputFormat/OutputFormat integration, which enables use of tools from the Hadoop ecosystem on data stored in JDG.
  • Remote Task Execution: JDG 7.0 features the ability to execute tasks (business logic) on a JDG server from the Java Hot Rod client. The task can be expressed as a Java executable loaded on the JDG server or as a stored JavaScript procedure which executes on the Java 8 (Nashorn) scripting engine on the JDG server.

Ease of Use and Administration

In JDG 7.0, we have released a new administration console which enables you to view a JDG cluster and perform clustered operations across its nodes. Operations include creating new caches and cache templates, adding or removing nodes, and deploying or executing remote tasks. We have also added the ability to shut down or restart a cluster in a controlled manner, with data restore from persistent storage.

Expanded Polyglot Support

Node.js Hot Rod client: JDG 7.0 introduces a new Node.js (JavaScript) Hot Rod client, which enables you to use JDG as a high performance distributed in-memory NoSQL store from Node.js applications.

Cassandra Cache Store

Additionally, JDG 7.0 introduces a new out-of-the-box Cassandra cache store, which enables you to persist the entries of a distributed cache on a shared Apache Cassandra instance.

Try It Today

Red Hat JBoss Middleware customers can download JDG 7.0 Beta from the Customer Portal

Beta documentation, including release notes, is available on the documentation page in the Portal.