Performance, scale, and real-time analytics: Red Hat JBoss Data Grid 7.1

I am excited to announce the general availability of Red Hat JBoss Data Grid 7.1!  This is the only Red Hat software ranked highly in two separate Forrester waves categories: In-Memory Data Grid and In-Memory Database. On top of that, no other vendor offers any unified in-memory data management solution that is recognized in both waves — JBoss Data Grid is the one product with the versatility to span both categories.

In-memory computing is all about high performance and scale-out architecture. The primary focus of this release to enhance the performance of JBoss Data Grid as an in-memory data management platform for hybrid transactional and analytical (HTAP) workloads.

New Capabilities and Features

  • Performance improvements. JBoss Data Grid 7.1 features core performance improvements, especially in clustered write operations. Current tests have shown up to 60% increase in write throughput under load. (We have modified various default settings to improve JBoss Data Grid performance.)
  • Elastic scale external state management for JBoss Web Server (Tomcat) and Spring applications (on-premise or cloud/Openshift). JBoss Data Grid 7.1 features the ability to externalize HTTP sessions from a JBoss Web Server node to a remote JBoss Data Grid cluster. This helps make the JBoss Web layer stateless and enables a rolling update of the application layer, while retrieving the session data from the JBoss Data Grid layer. Additionally, JBoss Data Grid 7.1 features Spring session support, which enables you to externalize HTTP session from a Spring (or Spring Boot) deployment to a remote JBoss Data Grid cluster.
  • Real-time analytics, through Apache Spark 2.x integration supporting RDD and DStream interfaces.
  • New string-based querying with Ickle (tech preview). JBoss Data Grid 7.1 introduces a new string-based querying language, Ickle, as technology preview,  which enables you to specify combinations of relational and full-text predicates (based on Apache Lucene). This enhances the querying feature-set available in client-server mode by bringing several additional operations that were previously available only in library mode.
  • Ease of administration. Update and save node-level configurations are now available through the administration console.
  • Feature enhancements to Hot Rod clients, including streaming large-sized objects in chunks from the JBoss Data Grid server to a Java client and adding cross-site failover for C++, C# and Node.js clients.

More Resources

Red Hat Summit 2017 – Planning your JBoss labs

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”

Webinar Now: In-Memory Computing and Real-Time Analytics

In-memory data grids provide a distributed network (or “grid”) of nodes that work as an elastic data store. This is an approach to distributed computing which can work as a foundation for systems which require rapid scale, responsiveness, and high loads, like Internet of Things and mobile applications.

In-memory computing (like any distributed architecture) can be very complex, and understanding how to map the functionality of your existing infrastructure to a distributed computing infrastructure is critical.

So we have a webinar for that! “Real-time advantages of an in-memory data platform” with Cojan van Ballegooijen and Thomas Qvarnstrom (both JBoss technology evangelist at Red Hat) will be covering:

  • An introduction to in-memory computing
  • In-memory data grid use cases
  • How data access can affect business decision making, application responsiveness, and customer / revenue opportunities

Details

  • Tuesday, Dec. 6
  • 11a.m. Eastern time (US)
  • Presenters: Cojan van Ballegooijen and Thomas Qvarnstrom

register_now

Upcoming Webinar: Highly Available and Horizontally Scalable Complex Event Processing

What if you could take the streams of information coming into your business and use it to recognize potential opportunities or issues almost immediately? Fabio Marinelli (senior architect) and Syed Rasheed (product marketing manager) will be conducting a webinar on complex event processing. Complex event processing helps you recognize important patterns within your data streams in near real-time.

There are two parts to understanding complex event processing. First is looking at the data itself, from a variety of sources (such as social media, devices, web or mobile applications, monitoring applications). Being able to take different types of information from unrelated sources and get a holistic view is important. The second part is designing an architectural framework that supports that level of data and processing. This webinar looks at an in-memory data grid as a complex event processing engine and using a distributed architecture for dynamic scalability.

Registration is open. The webinar is August 23 at 11:00am Eastern Time (US).

register_now

Fun Follow Up: Webinar Q&A

I will collect any questions asked during the webinar, and I’ll do a follow-up post on Friday, June 24, to try to capture the most interesting questions that arise.

What Are You Getting from (Big) Data?

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?”

Intro to In-Memory Data Grids

Some of the biggest technology trends aren’t necessarily about doing something new. Things like cloud computing (as an environment) and design patterns for the Internet of Things and mobile applications (as business drivers) are building on existing conceptual foundations — virtualization, centralized databases, client-based applications. What is new is the scale of these applications and the performance expected from them.

That demand for performance and scalability has inspired an architectural design called distributed computing. Technologies within that larger umbrella used distributed physical resources to create a shared pool for that service.

One of those technologies is the purpose of this post — in-memory data grids. It takes the concept of a centralized, single database and breaks it into numerous individual nodes, working together to create a grid. Gartner defines an in-memory data grid as “a distributed, reliable, scalable and … consistent in-memory NoSQL data store[,] shareable across multiple and distributed applications.” That nails the purpose of distributed computing services: scalable, reliable, and shareable across multiple applications.

Continue reading “Intro to In-Memory Data Grids”

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

Thank you JBoss partners

Thank you JBoss partners. You made our decade.

In the open source world (and I would say increasingly in the software world in general), the success of a new technology begins with active and vibrant communities that crank out compelling and useful technologies.

When the technology gets out and increases in popularity, early customers begin to trust it and it faces the challenge of being adopted by the mainstream market, which is composed predominantly by customers who are pragmatists in nature and that find it difficult to use a new product unless it has support in the market (other customers) and it has an ecosystem of partnerships and alliances with other vendors that serve their industry.

That’s why partners are key to technology products. The larger the partner ecosystem, the more trust customers can have and the better the chances of widespread adoption.

JBoss had started to create that partner ecosystem before it became part of the Red Hat family back in 2006. Many things have happened since those early years, and we’ve probably done a few right things along the way, as Red Hat has become the first open source company to surpass the two-billion-dollar revenue mark, and for the fourth consecutive year we have been awarded a 5-Star rating in the CRN 2016 Partner Program Guide – where vendor applications are assessed based on investments in program offerings, partner profitability, partner training, education and support, marketing programs and resources, sales support, and communication.

However, at the end of the day, it is really the partners who decide which technology partners they choose to pursue success in the marketplace.

In anticipation of the launch of Red Hat JBoss Enterprise Application Platform 7 (JBoss EAP), and of the 10th anniversary of JBoss becoming part of the Red Hat family, we offered our partners the opportunity to tell the world about out our collaboration.

So don’t take our word for it. Let our partners do the talking.

We are fortunate to have partners that have worked with JBoss for a long, long time. Some of them, such as Vizuri, were a JBoss partner before it became part of the Red Hat product family. Joe Dickman, senior vice president, explains that the widespread adoption of JBoss in the marketplace, especially among Fortune 500 companies, is “a testament to the ‘power of community collaboration and innovation’ that Red Hat embodies, which has forever changed the way that software is developed and businesses operate.”

Another JBoss veteran is Viada in Germany. In words of Daniel Braunsdorf, CEO of Viada in Germany, “Ten years ago JBoss was the first open source application server being really ‘enterprise-ready’”, and today “we are talking about a full stack of middleware suite products serving our customers needs by giving them more flexibility, agility, and speed to deliver innovative applications.”

James Chinn, CEO of Shadow-Soft, sums it up well: “Over the last decade, JBoss has come a long way in terms of improving performance as well as truly innovating in regards to the way applications run and are managed. With the release of JBoss EAP 7 comes a host of new features including full support of Java EE 7 and Java SE 8 (…) Furthermore, JBoss EAP 7 has also been upgraded to reduce start-up time and optimize networking port utilization making it truly ideal for running within Linux containers.”

SCSK from Japan trust the power of JBoss EAP 7 to drive open standardization and TCO reduction. In the words of Hisanao Takei, Senior Executive Officer, “SCSK thinks JBoss EAP 7 is the best choice that customers want for building open and standard infrastructure and especially expects system TCO reduction for virtual and cloud environment.”

Red Hat JBoss Middleware is at the core of many mission critical systems. And being intimately related with the other Red Hat middleware products, such as JBoss Fuse, enables our partners to support many different types of business customer needs. Hiroyuki Yamamoto, director at monoplus, Inc. in Japan, makes the point that “As business environments continue to evolve, we believe that JBoss Middleware will seamlessly contribute and support in the integration, co-operation and collaboration within businesses”.

Driven by the dynamism of information based sectors, it may be easy to forget that traditional businesses also need advanced enterprise systems to be successful. In such a traditional business as printing, our Japanese partner WingArc1st makes the point that “An enterprise printing platform needs to be highly reliable, stable and provide high performance for seamless operations,” and believe that “Red Hat Enterprise Linux and JBoss EAP 7 are important platforms” for the company’s SVF offering.

Matt Pavlovich, co-founder of Media Driver, abounds on how JBoss EAP 7 helps developers “to be more efficient by focusing their time on delivering business value versus fiddling with tech stacks.” No small feat, as he continues, “Whether it is deployed on-premise, in the cloud or via containers, JBoss EAP 7 provides deployment flexibility that can help DevOps teams avoid having to navigate tricky hurdles to get their environments up and running quickly.”

Regis Kuzel, senior vice president at LCN Services, takes pride at being an unbiased trusted advisor to their customers. “For LCN, the bottom line is you can’t do better than Red Hat JBoss EAP 7. It’s a well-thought-out platform. And it’s gaining market share because it works! We believe Red Hat JBoss EAP 7 is the best technology available at its core!”

In terms of innovation, Farhan Hussain, Founder and CEO, Open Source Architect has a clear view of the contribution of the new EAP7. “This new platform will help us provide reliable, cost-efficient and high-performing container-based solutions for on-site and cloud deployments, while enabling our joint customers to innovate and meet strict compliance, security, and regulatory requirements simultaneously!” says Farhan.

Heinz Wilming, Director, Red Hat JBoss Competence Center for our German partner akquinet, makes a point about the value that long term support provides to our common customers. As you are possibly aware, Red Hat JBoss Middleware product life cycles are generally three, five, or seven years in length, and for certain products can be extended by three (3) additional years (up to ten!), something not many vendors actually provide. In his words, “Long-lasting support, regular updates and interoperability ensure protection of investment and guaranteed future for both our customers and akquinet.”

Some of our partners have been supporting JBoss for a long time, and others have made investments more recently. This is the case of Opticca in Canada. Owner Ivan Cardona shares that “We’ve been deploying Middleware, SOA, and BPM platforms from the major providers for the past eight years. We’ve recently made a large investment In Red Hat’s JBoss solutions because our customers’ feedback led us to conclude open source is now a real option.”

A last word…

We are really happy we are getting this support from our partners. Many others share us in the 10th anniversary and you can learn more from our strategic alliances here. And find more in the JBoss partner ecosystem press release, here.

And for those that are still not in the ecosystem, please join us. We’re here to help you grow.

So let me conclude as I began.

Thank you, Red Hat partners. You made our decade. Ready for more?

PD: Keep reading here for blogs and additional quotes from partners worldwide about the new EAP7!

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.

Intro to Scalability

Scalability is one of those words that can mean very different things to different people, even in the same context or the same project. It’s not so much nuanced as it is that the definition matters on perspective — scale can be different for different goals.

There will be upcoming posts on data virtualization, in-memory data grids, integration methods — all areas where an understanding of your current and future needs, resourcing, and loads are critical for planning. Going into those concepts, it helps to understand scale — not just “make it bigger,” but how you make it bigger and when and why.

Continue reading “Intro to Scalability”

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