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Gil Peleg of Model 9: “Cloud is an ally to the mainframe”

Cloud is an ally to the mainframe. The natural inclination for gradual change over revolutionary disruption is a good excuse for a middle ground. Embrace cloud not as a threat to the status quo but a true opportunity. Mainframe organizations are hesitant to move data management workloads to the cloud. We are showing enterprises a […]

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Cloud is an ally to the mainframe. The natural inclination for gradual change over revolutionary disruption is a good excuse for a middle ground. Embrace cloud not as a threat to the status quo but a true opportunity. Mainframe organizations are hesitant to move data management workloads to the cloud. We are showing enterprises a middle ground that embraces the best of both worlds.


As part of our series about “How To Use Digital Transformation To Take Your Company To The Next Level”, I had the pleasure of interviewing Gil Peleg.

After spending more than two decades designing mainframe architectures, Gil Peleg founded Model9 to bring a new layer of enterprise data intelligence to the mainframe market. He is a co-author of eight IBM Redbooks on z/OS Implementation and has authored four patents as part of his work at Model9. He holds a BSc in Computer Science and Mathematics.


Thank you so much for joining us in this interview series. Before we dive in, our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started?

Can you share a story about the funniest mistake you made when you were first starting? Can you tell us what lessons or ‘take aways’ you learned from that?

I compiled a program into my sources directory because my programs directory was out of space. It’s funny because in the mainframe (MF) filesystem doing this completely ruins all the sources and is considered a “rookie mistake,” but when you’re a PC kid and have no clue about MF filesystem, it seems like a logical thing to do….

None of us are able to achieve success without some help along the way. Is there a particular person who you are grateful towards who helped get you to where you are? Can you share a story?

My army commander, who encouraged self-learning, dumped a whole bookshelf on me on my first day, and always challenged me to do the next thing I still hadn’t learned. Years later, I realized that when you see potential in someone you should always encourage them to stretch their limits to get the most out of them.

Is there a particular book, podcast, or film that made a significant impact on you? Can you share a story or explain why it resonated with you so much?

The Mythical Man-month by Fred Brooks, who was also the manager of the first IBM MF development. It’s a great software engineering book, and the MF angel helps me appreciate, relate, and really understand where he is coming from.

Extensive research suggests that “purpose driven businesses” are more successful in many areas. When your company started, what was its vision, what was its purpose?

Our mission has always been to unlock mainframe data intelligence by leveraging the cloud’s economies of scale. 
The modern enterprise has a black box that is perceived to be a self-contained “Island of Big Iron.” Enterprises are tapping into that precious resource of mainframe data using legacy infrastructure that limits access. By unlocking mainframe data in the cloud, we are not only accelerating modernization initiatives within the mainframe but also supporting the broader needs of the business around data intelligence.

Are you working on any new, exciting projects now? How do you think that might help people?

Yes, we are working on two new projects now: Cloud Data Sets and improved data transformation capabilities for integration with business intelligence / artificial intelligence. We started out by enabling IT teams to transfer data from legacy storage platforms to cloud-native deployments cost effectively. The next evolutionary leap is to write directly to the cloud, bypassing these legacy platforms altogether. Model9’s new cloud-native capability to intercept existing job control language (JCL) code running in the mainframe and write data sets directly to the cloud makes sense — our customers now know to ask for it. Once the data has been transferred to the cloud, we transform it from proprietary mainframe formats to universal formats that can be integrated with BI and analytics in the cloud.

Thank you for all that. Let’s now turn to the main focus of our discussion about Digital Transformation. For the benefit of our readers, can you help explain what exactly Digital Transformation means? On a practical level what does it look like to engage in a Digital Transformation?

Digital transformation is about leveraging the capabilities that new technologies have to offer for the benefit of the business. While that may sound self-evident, the reality is that business culture tends to lag behind technology. So, in the case of Model9, for example, simply liberating mainframe data and making it massively accessible is just a first step. The real transformation is about leveraging that data throughout the enterprise — data engineers, data scientists, and decision makers. Just because you have an AI play doesn’t mean you realize your ML models can access decades of data locked away in proprietary formats. In a world where one in two AI initiatives fail, executives need to ask how improved access to data and analytics pipelines could change business processes.

Which companies can most benefit from a Digital Transformation?

Any organization that has been in business since before the turn of the century must reinvent itself to stay relevant.

Digital transformation is the technological framework that enables innovation with the goal of delivering improved processes with measurable impact. It’s a cut and dried choice — innovate or become obsolete. Change is risky to be sure, but stagnation is even riskier, so it’s a question of balance. Where is that low hanging fruit? In the case of mainframes, I think everyone sees the value of the platform. The challenge is to leverage its strengths and innovate where it lags behind the times. The Model9 mainframe modernization journey suggests combining the best of both worlds: keeping mainframe as the core system and at the same time modernizing the mainframe infrastructure and leveraging the cloud for BI / AI / machine learning and analytics.

We’d love to hear about your experiences helping others with Digital Transformation. In your experience, how has Digital Transformation helped improve operations, processes and customer experiences? We’d love to hear some stories if possible.

We helped a leading transportation company in the US modernize their mainframe infrastructure and connect their mainframe data to the AWS cloud and snowflake for BI and analytics. We also helped a leading U.S. credit union in consolidate their mainframe data management together with their “distributed” data all under one platform, eliminate the need for virtual tape libraries, and save massively on operational data management costs.

Enterprises using the Model9 transform technology can leverage their mainframe data to analyze buyer intent, create sales forecasts, and demand prediction. Each industry presents its own AI use cases that can leverage historical mainframe data for insights.

As soon as our customers actually see we can reduce costs while increasing data transfer efficiencies by as much as 10X, they realize the depth of disruption we offer. Those who realize they can also gain insights from the data once it’s been unlocked can find the value is beyond operational efficiency and cost reduction.

Has integrating Digital Transformation been a challenging process for some companies? What are the challenges? How do you help resolve them?

Digital transformation means tearing down organizational barriers and technological silos, which, of course, have deep roots in traditional business practices. The imperative is to connect the new opportunities technology can unlock to tangible business goals. A good case in point is AI, which we know is a top priority for most CIOs. In fact, some organizations are even appointing C-level AI officers. The reason is simple. According to Gartner, half of AI initiatives fail. The very task of explaining why is a challenge, let alone addressing the problem and fixing it.

If you think about the layers of organizational engagement that AI initiatives require, you need to collect the data for ML training, engineer the analytics pipeline, and finally operationalize the models to plug all those data points into applications in production. If the problem can be addressed by unlocking massive data sets buried in the mainframe, the AI officer may not even know that is an option. The challenge is connecting organizational resources that aren’t accustomed to collaborating so tightly.

Ok. Thank you. Here is the primary question of our discussion. Based on your experience and success, what are “Five Ways a Company Can Use Digital Transformation To Take It To The Next Level”? Please share a story or an example for each.

  1. Challenge the “death of mainframe” myth to jumpstart organizations from stagnation to transformation. The NJ unemployment fiasco is a prime example. Everything seemed to be fine with the mainframe until COVID, and millions of people filed for unemployment at the same time, and the legacy infrastructure could not handle the load. Out of the blue, the governor of NJ was speaking publicly about a “COBOL programmer” crisis. At Model9, our argument is that you don’t need to rewrite the business logic. Modernize the infrastructure by leveraging new economies of scale. Don’t rehaul the engine, simply lighten the load, and that same business logic performs at a whole new level.
  2. Cloud is an ally to the mainframe
    The natural inclination for gradual change over revolutionary disruption is a good excuse for a middle ground. Embrace cloud not as a threat to the status quo but a true opportunity. Mainframe organizations are hesitant to move data management workloads to the cloud. We are showing enterprises a middle ground that embraces the best of both worlds.
  3. Expand the AI conversation beyond real time data
    When talking about innovation and AI initiatives, the conversation tends to focus on real-time data. We keep having to remind leaders that the power of mainframe is about the longevity of the platform. It’s been around for as long as computing has been in business — so has the data it’s generated. That’s a priceless and severely undervalued resource that enterprises tend to ignore.
  4. Don’t be a legacy hoarder
    Model9 is a proponent of the mainframe platform. For that reason precisely, we are focusing on data management as a way to embrace what I like to think of as a “Mainframe Renaissance.” To benefit from the power of the mainframe, focus on the business logic that has worked so well over the decades. Monetize the data that business logic has generated. Finally, if you can chart a course to modernization that lets you do all that by rehauling the data management layer, understand that the proposed solution is technology driven. The concepts of storage and data management are so tightly coupled, that when we tell mainframe practitioners that they can eliminate the tape, their gut response is to ask what they should do with all that tape. Change takes time to wrap your head around.
  5. Thinking outside the box is hard
    Think of the mainframe as a box. We are telling people to think outside the box. The ones in the trenches have trouble imagining that the outside even exists. Those outside have never been given a tour. We are connecting the best of both worlds.

In your opinion, how can companies best create a “culture of innovation” in order to create new competitive advantages?

Digital transformation by definition is about building bridges and new connections. It’s exactly why a startup like Model9 offers such transformational value to Fortune 500 market leaders.

Can you please give us your favorite “Life Lesson Quote”? Can you share how that was relevant to you in your life?

Yes, as someone who has worked for many years to grasp the full breadth of mainframe architecture and practice and to connect that to the innovations in the cloud, I always like a comment made by computer pioneer Grace Hopper, who invented the concept of the compiler and helped create the COBOL language. She said, “The most dangerous phrase in language is ‘We’ve always done it this way.’” Given her history, it makes me smile to think about how innovations can become traditions that are hard to change!

How can our readers further follow your work?

https://www.linkedin.com/company/model-9/

Model9.io

Thank you so much for sharing these important insights. We wish you continued success and good health!

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