
SVG Sit-Down: CEO Jamie Lerner on Quantum's Future and Leveraging M&E Prowess for Other Industries By Jason Dachman, Chief Editor
Monday, December 10, 2018 - 5:39 pm
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It has been nearly six months since Jamie Lerner came aboard as president/CEO of Quantum, and the veteran tech exec is well on his way in plotting a new course for the video- and data-storage outfit, which has struggled recently. After cycling through five CEOs in less than a year, Quantum is looking for Lerner, along with recently named CFO Michael Dodson, to establish stability at the top of the ranks.
Quantum President & CEO Jamie Lerner
Lerner, who previously led a turnaround of three business units in Cisco's Cloud and Systems Technology Group and also served in top executive roles at Seagate and Pivot3, aims to expand to new market verticals by leveraging the leading-edge technology that Quantum has developed for media and entertainment (M&E) and exporting it to a variety of other industries. As the cloud and virtualization become more than just buzzwords, he seeks to embrace next-generation workflows and evolve Quantum's product portfolio to serve media companies' rapidly evolving needs.
SVG sat down with Lerner for an in-depth discussion to address his roadmap for the company, including expanding to markets beyond M&E, what to expect in Quantum's next generation of products, the rise of AI and machine learning, how the company is adapting to the demand for virtualized infrastructure, the power of NVMe for storage, the enduring viability of LTO tape, and, perhaps most interestingly, his proposal for a subscription-based, managed service for storage hardware.
What have you learned in your first few months as CEO at Quantum?
I've spent the past few months learning what our customers do with our technology. What I've come away with is that Quantum is woven so deeply into the fabric of our society that you interact with it almost daily. It's pretty hard to watch television or online content without seeing something produced on our gear: whether it's films, [episodic] shows, news, sports, or anything else.
The work that we do in media and entertainment, especially in sports, is informing everything that we're going to do in this company across every [vertical].
Our analysis shows that, by 2025, 80% of the world's data will be video. About 50% of that is media and entertainment, and about 50% of that is going to be surveillance data. We believe we are the world's best-positioned company to handle this deluge of new data. All we think about is rich media and video. Traditional IT storage technology is totally inappropriate for video. If you're in the video world, we are going to build this from the ground just for you.
So, how does Quantum plan to use the video-production tools developed for M&E in other verticals?
We are starting to realize that, in terms of video needs, police departments look exactly like a television studio. A hospital looks like a television studio. And a manufacturing plant looks like a television studio. When a police officer comes off a beat, his department is going ingest his video from his car and his body camera, take the bits that are of interest and distribute them to lawyers, district attorneys, and courts. And they're going to archive it for 30 or 40 years in case there's an appeal. There's no sound editing or colorizing, but that certainly sounds similar to our experience in media and entertainment.
But, you remain committed to the M&E market?
Yes, absolutely. That is our core use case that all these other use cases are being built from. Our strength in M&E will continue to propel us for the foreseeable future.
What enhancements do you plan for Quantum's core products, such as StorNext?
StorNext lends itself to really high-speed-media workflows. The first thing we're doing with the core file systems is make them even faster by moving to all-NVMe-based architectures. We're making the absolute world's fastest hardware, and we will be all NVMe end-to-end.
NVMe is hands-down the world's fastest editing and postproduction platform, but it's also really expensive. So creating a top-to-bottom NVMe environment is unviable economically. What makes it work is really intelligent tiering. Most data will be sitting on a disk tier, so you can do the bulk of your storage spend in disk and a very thin sliver of NVMe. The whole architecture comes down to how intelligently you put the right content on the NVMe tier at the right time.
The next thing we're doing [with our portfolio] is hyper-converging: we want to bring the storage as close as we can to the CPU and GPUs, so we can analyze at extremely high speed. We're moving all of our storage technology into virtual machines and into containers and hyper-converging.
We're also starting to bring the analytic software down to the boxes to improve metadata analysis. A lot of the metadata tagging on video files is just not accurate. I see dozens of [loggers] just looking at a piece of video, confirming it is what we think it is, and typing that in. I think it's obvious that it all should be machine learning. Catalogues are getting so big that human logging - typing what each pitch was in a baseball game, for example - is totally non-viable. If a picture is a thousand words, then a video is a million words, and there's just no way to type fast enough to capture all that. So our core hardware infrastructure is being designed to bring machine learning to the forefront.
And finally, we're completely revamping our management interfaces. StorNext is a de facto standard and is incredibly performant, but most people would say it's very hard to manage. Today, the world's most modern products have be
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