In the six years since I first visited Red Hat’s user show,  open source software has become the default choice for enterprise applications and the cloud infrastructures on which they run. This year’s Red Hat Summit provided a  good look at how the open source vendor’s products are evolving and being marketed as it prepares for its $34 billion acquisition by IBM.

Open source means users can view and modify the code to fix bugs and meet new needs. This means a  global pool of enthusiasts improve the software 24/7/365 rather than waiting for a vendor’s next release cycle. But big customers still want enterprise-level support and a single vendor’s “throat to choke.” Hence the rise of Red Hat Software, which grew to a $3.4 billion company by providing support and standard versions of a blizzard of products tailored to the needs of major enterprises.

I came away impressed with the breadth and scale of how open source is replacing more traditional software, and how Red Hat’s roots in the open source community shape its messaging.

My takeaways:

Open Source Is Big

The Boston Convention and Exposition Center was buzzing with a record attendance of about 9,000 and a show floor filled with vendors from startups to industry stalwarts such as HP, Dell EMC, and SAP.  IBM CEO Ginni Rometty showed up to hug Red Hat CEO James Whitehurst, which might have been expected given the upcoming acquisition. What impressed the audience more was CEO Satya Nadella of Microsoft endorsing, in person, Red Hat’s OpenShift cloud management platform running on Microsoft’s Azure cloud platform. (OpenShift is based not on Microsoft Windows, but Linux, which former Microsoft CEO Steve Ballmer once called a “cancer”.)

Open source is also big in terms of the companies it serves and the applications it runs. Ken Finnerty, president of IT for UPS, described why the global shipper chose Open Shift for its 59 million user My Choice online tracking and shipping platform.  Other featured customers included HCA Healthcare, BMW, and Deutsche Bank. Red Hat has invested heavily in technologies ranging from load balancing to middleware (and worked closely with the big cloud providers) to allow once-fringe open source to run workloads that once would have taken a mainframe.

Know Thy Customer

Who, in this case, is very, very technical. Think jeans and t-shirts, command-line interfaces  and dense architectural diagrams even for keynotes. One demonstration that drew applause and whistles  was the real time capture of movement data from the audience’s smartphones as they waved them in the air (video here) with Red Hat’s infrastructure instantly scaling up to capture and display the data flow.

Red Hat also had something I’d never seen at a trade show: Dedicated, staffed booths where any customer, developer or partner could share their likes and dislikes. There were even tablets (see screen at right) asking for feedback about how  Red Hat listens and communicates. I don’t know what happens to this feedback but asking for it loudly and clearly sends a powerful message.

Love Thy Customer

Most customer endorsements somehow feel more about the vendor than the customer. Red Hat lined the halls with big photos of customers describing how Red Hat helped them, with comments often focused more on Red Hat’s commitment to them then the speeds, feeds, and features of its software. Even ads featuring Red Hat’s new logo took pains to assure the reader that the company’s “soul” is unchanged. How tech companies even claim to have a “soul” these days with a straight face?

Automate and Simplify

With the exploding size and complexity of enterprise clouds, there was a lot of talk about the use of artificial intelligence (AI) to create automated and even self-healing systems. As is the case in AI- aided security, there’s a lot of hype to watch for but also some signs of real results. One was Federator.ai from ProphetStor Data Services, Inc. which the company claims uses AI to choose just the right amount of compute, networks and storage from the right public clouds for OpenShift environments and fine tunes those recommendations over time.

Another major theme was point and click interfaces for everything from building AI machine learning models to troubleshooting cloud performance problems. Longtime application performance monitoring vendor Dynatrace now offers a platform that clearly describes not only the nature of a problem, but the number and even the identity of the affected users. This not only bridge the infamous gap between IT and the business but expands Dynatrace’s user base from system administrators to mere mortals who run the business.

The Next Marketing Frontier

Moving forward, marketers would do well to clearly explain open source tools such as operators, sidecars, Akka clusters, hyper converged infrastructure and service meshes to both techie and business types, prove vendor claims of AI-enabled everything and explain how automation and more user friendly interfaces can help not just the geeks in the back room but the bottom line.

Author: Bob Scheier
Visit Bob's Website - Email Bob
I'm a veteran IT trade press reporter and editor with a passion for clear writing that explains how technology can help businesses. To learn more about my content marketing services, email bob@scheierassociates.com or call me at 508 725-7258.

Busting the AI/Security Hype Cycle

Whenever a buzzword gets hot, you can expect lazy marketers to start pasting it on every product or service in sight. When two buzzwords get popular at the same time, expect double the hype.

So it is with the two hot high-profile trends of security and artificial intelligence (AI). Security is a big deal because more than 50 years into the computer age we still haven’t figured out how to protect our applications and data well enough, and the problem is only getting worse. AI is on everyone’s lips because of its potential to analyze massive amounts of data more quickly and accurately than a human could to identify, and possibly predict, events.

Smart Machines Fighting Bad People

The AI play in security is that algorithms can do a much better job than people at picking out potential threats from the thousands, tens of thousands or millions of clues in your network traffic and among your devices.  At the very least, the pitch goes, AI can sift out the most likely real signs of threats among from everyday shifts in network traffic or whether a repeated log-in attempt is a user who forgot their password or an automated bot trying to guess that password.

That all sounds reasonable, but I’m hearing (even from some of my security clients) that too many security vendors are pasting the “AI” label on their offerings without delivering the goods. As a marketer, if you’re knowingly complicit with this you’re not only misleading the end consumer but setting yourself and your client up for failure when customers realize the client can’t deliver.

I get it that AI story is a rapidly evolving field, your client may still be growing their own AI expertise, and that security customers are justifiably reluctant to share their successes or, even worse, their failures. We still owe it to our clients and their customers to push for real proof that their AI security solutions can do what they claim.

Some tough questions to answer before pumping out more AI/security fluff:

AI/Security Reality Checks

  • What algorithms is the vendor using to sift through the network or device data they are collecting? How have they been proven to be useful?
  • How accurate (numbers, please) is the AI-enabled assessment of real security events vs. false positives? How are those results improving over time?
  • How big is your client’s AI staff and how quickly is it expanding? If they are partnering with other/bigger AI experts, who are they and how strategic is the partnership?
  • What does the solution do to ensure it is being fed correct samples, to avoid the “garbage, in, garbage out” syndrome?
  • How does it guard against hackers turning AI against the enterprise, such as feeding bogus samples into the machine learning data pool, using AI to gather information about the target and identify vulnerabilities, and using AI chatbots to fish for information?
  • Does the vendor recognize the limits of AI and make it easy to bring people with their fuller understanding of context (and common sense) into the decision-making process?
  • And, as always, push for customer case studies, even if anonymous.

We’ve all been to this rodeo – of vendors trying to jump on a new technology trend before they can really deliver – many times before. Curious for your thoughts on:

  • What percent of AI/security claims can your clients back up?
  • What other proof points can they provide for their claims than what I’ve mentioned here? and
  • How willing are your clients to go the extra mile to tell a provable AI/security story?
Author: Bob Scheier
Visit Bob's Website - Email Bob
I'm a veteran IT trade press reporter and editor with a passion for clear writing that explains how technology can help businesses. To learn more about my content marketing services, email bob@scheierassociates.com or call me at 508 725-7258.