- Red Hat OpenShift Application Runtimes is now in public beta, meaning you can try it!
- Red Hat OpenShift Application Runtimes includes a collection of supported application runtimes.
- Each runtime is designed to simplify cloud-native development by using Red Hat OpenShift capabilities in a manner natural to the language runtime.
- Try it! Go to developers.redhat.com/rhoar. Choose an example and runtime, and watch it get forked to your github account and deployed to OpenShift. Feedback welcome on StackOverflow.
Continue reading “Introducing OpenShift Application Runtimes Public Beta”
If you’ve been following the news about Oracle’s new direction for Java EE, you’ll know that one of the motivations for changing the governance and process is to move Java EE forward in a more agile and responsive manner.
So it’s a good sign that within a month of initially announcing their intentions, Oracle (with help from IBM and Red Hat) have chosen the Eclipse Foundation as the future home for Java EE. You can read Oracle’s announcement here.
This is a pretty important, first, tangible step in moving Enterprise Java forward and it’s encouraging to see Oracle moving ahead at a rapid pace. Java EE is an established technology that many organizations depend on for their business critical applications. Java EE is also a large body of work with Technology Specifications, Reference Implementations and TCKs from multiple vendors and open source projects so there’s still a significant amount of work yet to happen – but this is a great start.
Oracle’s announcement to move Java EE to an Open Source foundation has already begun to energize the community, offering the opportunity to more quickly evolve the platform to meet modern workloads. The Eclipse Foundation will be significant enabler in that evolution and Red Hat fully supports Oracle’s decision. Eclipse already hosts many projects of a similar size and complexity as Java EE, and we’re confident that the many years of experience and expertise the Eclipse Foundation has with other Java technologies ensures that this will be a successful move.
MicroProfile is also an Eclipse Foundation project and Red Hat hopes this will make it easier to align Java EE and MicroProfile in the future. The MicroProfile project was started in June 2016 as a collaboration between Red Hat, IBM, Tomitribe, Payara and others in the Java community with the goal of making Enterprise Java more relevant to developers building cloud-native applications.
Red Hat is an Eclipse Foundation member and has worked with the Eclipse Foundation for many years on projects as diverse as JBossTools, IoT, Kapua, Vert.x and Che and we look forward to working with with Oracle, IBM, The Eclipse Foundation and others on the future of Java EE.
At this stage the future of Java EE looks brighter than it has for quite a while as Oracle, working with Red Hat, IBM, other vendors and the wider community to move the specifications, TCKs and overall innovation to an open source foundation. I think in general most people in the Java community see this as positive but there are a few naysayers, even more of them in other non-JVM areas. The common thread throughout is along the lines of “who cares these days?” or “it’s far quicker and easier to accomplish the same things with framework X or language Y, anyway.” I’m not going to try to address all of the concerns which have been raised because many of the comments I’ve seen have clearly been subjective and bordering on click bait. However, I’m writing this piece to reiterate some things I’ve said over the years and which remain just as relevant today, in my opinion
I want to start though by saying that in all of this I am trying to remain objective. Of course in my current role I and Red Hat have a vested interest in Java EE but if you’ve known me long enough over the years you’ll know that I’m also a scientist and as such I base my opinions on observations and facts born out by those observations. If a fact or piece of data goes against a theory then I don’t ignore it, I review and likely update or replace the theory to match the facts. I’ve changed my opinion on many things throughout my career and I’m sure I will do so again.
OK so back to Java EE. Does this move to open source help the wider community? Is Java EE still relevant or has it had its day like so many technologies before it? I’m not going to link to other things I’ve written on Java EE and its future over the years as they’re easily searchable through your favourite engine. But in short, many people forget that Java EE represents an evolution of essential middleware capabilities which many mission critical applications require. It’s had a lot of bad press since its inception, some of it accurate and some of it less so. I think one of its big failings is that, like my favourite topic of transactions, it has been used and misused in environments where it wasn’t really appropriate. No stack or framework is going to be applicable to every problem space and of course developers are going to get frustrated if they try it and find it wanting and failing as a result.
Continue reading “The future of Java EE”
This year in Boston, MA you can attend the Red Hat Summit 2017, the event to get your updates on open source technologies and meet with all the experts you follow throughout the year.
It’s taking place from May 2-4 and is full of interesting sessions, keynotes, and labs.
This year I was part of the process of selecting the labs you are going to experience at Red Hat Summit and wanted to share here some to help you plan your JBoss labs experience. These labs are for you to spend time with the experts who will teach you hands-on how to get the most out of your JBoss middleware products.
Each lab is a 2-hour session, so planning is essential to getting the most out of your days at Red Hat Summit.
As you might be struggling to find and plan your sessions together with some lab time, here is an overview of the labs you can find in the session catalog for exact room and times. Each entry includes the lab number, title, abstract, instructors and is linked to the session catalog entry:
Continue reading “Red Hat Summit 2017 – Planning your JBoss labs”
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. Lost a bit in the holidays, but chapter 6 was made available and those already in the MEAP will have had access to start reading the chapter.
As mentioned when chapter 5 released, I expected to split out the chapter into a second as the content covered was too expansive. I divided it into the simpler basics of creating business logic with rules and moved on into more advanced topics.
Enjoy topics such as modeling complex domains with domain specific languages (DSL), capturing complex logic in decision tables and leveraging DSLs in your guided rules. All this takes you a step closer to effectively implementing 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.
For more than 10 years, Red Hat JBoss Middleware has been a successful business that deeply represented the Red Hat DNA: open source software. We expanded our product portfolio with projects created and imagined by the open source community; we decided to support other projects with contributors; and we also opened the source of technologies we acquired. Somewhere along the way, Linux containers, Kubernetes, and docker happened which made us realize that containerization of applications is the base for your next 20 years. The caveat in this is that a platform is only as important as the applications you run on top of it. In other words, a platform not running applications is not realizing its value. With that in mind, we made an important decision and investment to evolve our application portfolio in similar ways that we ask our customers to do to theirs: let’s take our Red Hat JBoss Middleware products, commonly deployed on Linux and Windows machines, and make them available as containerized deployments.
With the announcement of the availability of JBoss Data Virtualization for OpenShift we now have 100 percent of our Red Hat JBoss Middleware runtime portfolio containerized and available in Red Hat OpenShift, an enterprise-ready Kubernetes distribution with value-added capabilities that go from deploying your already packaged container images, to delivering a DevOps pipeline for an iterative development process.
Continue reading “Bringing Containerized Services and DevOps Closer to (Your) Reality”
JBoss Enterprise Application Server 7 has been out since June, and if you build and deliver using a Java EE environment and haven’t yet upgraded to EAP7, it’s time to make the jump.
Here’s a look at what’s new in JBoss EAP 7, what has changed since JBoss EAP 6, and how to get the most out of JBoss EAP 7 as your Java EE7 server.
JBoss EAP 7 is based on WildFly Application Server 10, which provides a complete implementation of the Java EE 7 Full and Web Profile standards. WildFly 10 does much to simplify modern application delivery based on containers and microservices.
JBoss EAP 7 features certified support for Java EE7 and Java 8 SE. The WildFly integration brings experimental Java 9 support, too. It also supports current development snapshots of Java 9, which is expected for release this fall.
The JBoss EAP 7 release is available for download from JBoss.org.
Continue reading “Five features of JBoss EAP that will help get you production ready”
Gartner has a term for information which is routinely gathered, but not really used: dark data. This is information which is collected for a direct purpose (like processing an online transaction), but then never really used for anything else. By IDC estimates, dark data represent about 90% of the data collected and stored by organizations.
The Internet of Things (specifically) and digital transformation (more generally) are business initiatives that try to harness that dark data by incorporating new or previously untapped data streams into larger business processes.
Big data refers to that new influx of data. The “big” adjective can be a bit misleading — it doesn’t necessarily mean that these are massive amounts of data. Some organizations may be dealing with petabytes of data, but some may only be gigabytes. It’s not a given amount of data, but rather the scale of increase from previous data streams.
Continue reading “What Are You Getting from (Big) Data?”
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.
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.
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.