Next week is Red Hat Summit / DevNation in San Francisco. And you can still register!
My last highlight post touched on the many sessions and labs related to Red Hat middleware that will be at Summit this year, but (for the eagle-eyed reader) there was something missing: any sessions related to Red Hat JBoss Enterprise Application Platform.
There is a reason. Back in December, JBoss EAP 7 Beta was released, and this marked a significant technology advancement. JBoss EAP 7 is based on the Java EE 7 spec, which introduces a number of improvements in data handling, transactions, and other performance and development areas. Additionally, JBoss EAP 7 itself adds a lot of new features and continues down its previous path for lightweight, modular, and highly-configurable server instances.
Continue reading “Summit Preview: JBoss EAP Highlights”
When we go to the Red Hat Summit this year in San Francisco, we have planned to attend sessions, labs, evening events and even maybe a few good seafood restaurants. Little did you know that there is a gem you might want to fit into your busy schedule, as it is a chance to meet some of the rock stars that are backing the Red Hat Open Innovation Labs.
There will be a series of sessions hosted by experts to showcase use of Red Hat technologies and demonstrate the best practices with interactive white boarding. That is a personal touch session where you can interact with the storytellers and will be taking place in the West Lobby of M0scone Center on level 2.
Continue reading “Red Hat Summit Preview – Discovery session series”
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.
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
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.
There is “A Defense of Java” post over on DZone, which is an interesting enough post itself, by a guy from AppDynamics. What verges into very cool reading is the comment section (which made it DZone’s #1 commented article on Monday). There is a strong debate about the future of Java, other languages like Python and Node.js, and how major enterprises are building apps for high-traffic sites.
An increasingly common buzzword in cloud computing is microservices. Like a lot of things associated with cloud technologies, a precise definition is difficult to find — and it can mean a lot of things to a lot of different people, depending on the context. Since this is a blog devoted to middleware issues, I want to define microservices within the context of that middle layer in computing, for application development.
Microservices is an architectural approach for a software system. Meaning, it defines how individual services fit together and how those services are constructed (like, general constraints or best practices). What sets microservices apart from other architectural approaches is that it treats each service as a discrete and independent part of the architecture. That means that services themselves (within that system) have very clear definitions:
Continue reading “Intro to Microservices”
Part 1 looks at a handful of business considerations that you need to account for when you’re looking at Java EE application platforms — but that is only a part of selecting anything for your IT environment. In addition to treating an IT decision as a capital asset, your planning has to include technical factors: current and future development models, different types of applications, even rapid data processing.
Success today depends on achieving high levels of agility and flexibility. Major technology trends like mobile, the Internet of Things, and big data rely on lightweight, iterative environments like virtualization, cloud, and containers. This is forcing organizations to rethink their application development and deployment processes, application architecture designs, and choice of technologies used to build and run applications.
Continue reading “Choosing a Java EE Application Platform, Pt. 2: Technical Considerations”
Historically, choosing a Java EE application platform was like any major capital planning — it was driven by a clear business logic:
- Support for your current platform was expiring.
- You had to standardize your systems.
- You needed to accommodate a legacy system.
- You needed to reduce costs.
- You needed to take advantage of a specific advancement in Java technology.
Those are still primary factors, but there are a lot of additional factors to consider for something as foundational as an application platform. Part one of this series covers the business questions; part 2 will be out later this week to look at some of the technical considerations. [UPDATE: Part 2 is now live.]
Business considerations have a significant role in IT decision-making because your partnerships and budget commitments directly impact your company’s development agility, ability to adopt new technologies, and internal and external design decisions. When you start weighing your options, aside from transaction costs, there are a handful of questions you must ask to make sure that you maintain business agility.
Continue reading “Choosing a Java EE Application Platform, Pt. 1: Business Considerations”
The convergence of Mobile, Social, Big Data, and Cloud has placed increasing demands on today’s applications to react instantaneously to changes in data at a large scale. A delay of a few seconds can mean the difference between engaging or losing a customer for a retailer, increased liquidity or fraud risk for a financial institution, or escalation of an adverse occurrence in a manufacturing process or IoT network.
Continue reading “Event-driven computing with Red Hat JBoss Data Grid”
There are a few Open Source technologies and products that have spearheaded the drive of Open Source into the enterprise and managed to overcome historical objections – Linux, Apache Web Server, MySQL, Postgres, WordPress, Hadoop, to name some of the better known technologies. Those technologies paved the way for the open source revolution of the last decade; every enterprise vendor and every organization has adopted open source to some degree. Open Source has won; get over it.
Continue reading “JBoss EAP – Spearheading OSS adoption”