Five Links: Make Me Feel Safe Edition

Happy Friday, everyone.

The last few weeks have seen a series of DDOS attacks taking out major services through vulnerabilities in IoT security, outages from human error, and data breaches from major players like Yahoo and less reputable ones as well. There are a lot of different attack vectors and different types of information that is vulnerable — and this highlights the thin line between security and risk. Security is not exactly a buzzword and it doesn’t get a lot of attention until (like insurance, a warm coat, or a full tank of gas) you really need it. That’s this week’s theme — data security and privacy.

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Five Links: The More You Know Edition

Happy Friday, everyone.

There have been a couple of events lately that, at least tangentially, made me think about information and what we do with it. There have been a series of DDOS attacks on popular sites, at least one of which was driven by a blind army of smart devices. The other is the volatile and ultimately inaccurate polling leading into the US Presidential election. Both of these hint at the Wild West nature of technology — its flexibility and newness offers a lot of promise and a lot of unknown risks. So the theme for this week is — what is the quality of data and analytics and how do we do it “right.”

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Five Links: Embrace the Change Edition

Happy Friday, everyone.

As we come upon the glorious time change weekend, I’ve been seeing a lot of posts lately on changes — planning, designing, trying to understand what needs to change and how. Change is inevitable, but the question seems to be how far can we control it or define it. Within technology, we talk a lot about disruptive companies or key innovators, and sometimes it’s easy to begin looking at change for change’s sake. Disruptors and innovators don’t (only) change because it’s fun — they do something new with purpose. So this week’s posts look at change, design, and transformation as means to an end — chaotic yet intentional.

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Five Links: A Big Cup of Joe Edition

Happy Friday, everyone.

This week started off great with a bout on Monday with a lot of people talking about AI and virtual reality (links picked at random). I’m not saying I started a trend, I am simply observing a certain zeitgeist. This is week, I’ve been looking at more familiar worlds: Java, Java EE, and app development. This is the heart of what we do in middleware.

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Image credit: Headline Shirts. Also, the shirt is on sale now.

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Five Links: How Virtual Is Reality Edition

Happy Friday, everyone.

As always, the “Internets” is a fascinating place (assuming a massive denial of service attack hasn’t cut you off from Twitter and Spotify) and there is a new trend in the things I was clicking. This is probably inspired by my recent obsession with Westworld, but I have been thinking in general about the essence of reality and how far technology can go to both conceal reality and create it. So this week’s theme is reality-bending technology: virtual reality, augmented reality, artificial intelligence, and the technologies behind it.

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Five Links: We Are All Connected Edition

Happy Friday, everyone.

This has been a cool week on the web, and I noticed a trend in the things I was clicking. I saw a lot of articles and images that show relationships — mainly with the Internet of Things (relationships between devices, software, and people), but a couple of interesting ones on group dynamics.

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Why Group Brainstorming Doesn’t Work (Trello blog)

This deserves the top spot because of how counterintuitive it is, but the post makes some excellent points about how to get group ideas more effectively. Along with pointing out a lot of the pitfalls of group brainstorming sessions, it also has advice on how to be more effective in eliciting the best ideas from a group — including creating time for independent brainstorming, providing better structure to the process, and having a final decision.

Interactive Map of Internet of Things Companies (The Pointy Haired Manager blog, via IoT LinkedIn group)

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Winner! Best Data Virtualization Solution

Database Trends and Applications (DBTA) announced its data solutions winners earlier this August, and one of our middleware products was honored! Red Hat JBoss Data Virtualization won best data virtualization solution.

DBTA’s awards were reader’s choice, meaning that it was the community of data virtualization users who voted for JBoss Data Virtualization. According to DBTA’s announcements, the hallmarks of a winning data virtualization solution include three characteristics:

  • Agile development
  • A secure virtual data layer
  • Real-time data access and provisioning

It’s a combination of security and speed.

Data virtualization provides a layer over existing, separate data sources, which integrates the data in those sources without have to manually copy or convert that data. Data virtualization can support a lot of potential business benefits, including reducing duplicate data, improving data consistency, and reducing architectural complexity. Data virtualizations can provide that comprehensive view and access to data, without having to replace existing applications.
Find out more about Red Hat JBoss Data Virtualization here.

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).

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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.

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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.

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