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Quantum Exec Outlines "Massive Data Growth" Challenge
Storage Company Addresses Cloud, Big Data & Analytics, IoT

Storage is part of cloud computing's brain, as essential as the microprocessors that work with it to bring cloud computing alive. Along these lines, I was engaged in a short, interesting conversation with Quantum Corp.'s SVP of Strategy Janae Lee in the days before our recent Cloud Expo in New York.

Janae's been in the storage business a long time, having put in stints at IBM as well as two companies that were acquired by EMC. She's been at Quantum since 2007.

I asked her a bunch of questions as I was preparing for New York, and she provided a bunch of detailed answers. Now that I've had some time to recover from New York (even as we prepare for Cloud Expo Silicon Valley in November), it seems like a good time to report on what she said:

Cloud Computing Journal: Could you briefly describe where Quantum is at with regard to cloud computing and big data? How does its current vision and strategy connect to the company's history?

Janae Lee: Quantum has long been in the business of intelligently capturing, managing and protecting data on a variety of storage devices so it can be retrieved/accessed when needed. As an example, we provide high-performance file management and policy-based tiering to disk, object store or tape (for cost-effectiveness) through our StorNext solutions.

We see the storage cloud as a very interesting, new, high-growth opportunity for leveraging our intelligence value-add to help customers. As a result, we are deploying a range of private and public cloud models, including:

In a product reference architecture using StorNext and our Lattus object storage, for customers wanting flexible, low-cost storage in a private cloud.

As a set of cloud backup and DR products and services which we enable with partner MSPs, based on our DXi deduplication and vmPRO virtual data protection technology.

As a set of services we intend to offer directly to customers which – when released – will focus on specific use cases. We demonstrated an example of one such service at this year’s NAB (National Association of Broadcasters) show in conjunction with several partners (Adobe, Reach Engine and Telestream). This demonstration showed an entire film editing workflow completed in the cloud using StorNext, Lattus and partner products.

While these models sound discrete, our expectation based on customer input to date is that most of our cloud deployments will be hybrids of a customer onsite and offsite model, with some of the onsite systems being managed by the customer while others are fully managed services by Quantum or its partners.

We will have a number of new offerings in this space this year. However, rather than the vanilla commodity storage offerings frequently announced in press releases, the Quantum solutions will be configured to enable specific customer use cases, thereby maximizing the value and ease of use to the customer.

CCJ: You recently wrote a brief item about Data vs. Information. This is an age-old challenge, as enterprise IT tries to turn data and information into knowledge and wisdom. How does Quantum address this challenge for its customers in an age of massive amounts of real-time data starting to emerge?

Janae: Quantum has been working at the heart of this issue for over 20 years with our scale-out storage business around the StorNext file system. Two of the industries where our deployment of StorNext is strongest are Media and Entertainment and National Intelligence.

Both of these customer sets are on the leading edge of the issues that other, more general Big Data customers are only now beginning to see (massive data capture from devices – cameras and/or sensors - with the need to capture/analyze metadata). This experience has given us an appreciation of the challenges – and the expertise to deal with them. Our strong engagement with these communities is precisely what caused us to become an early proponent of object storage (now embedded in our Lattus system).

StorNext’s natural support for workflow-based architectures has also enabled (and even driven) us to build strong partnerships with vendors who specialize in collection, creation and policy-based management of business metadata, such as media asset management, lab information systems companies, etc.

We leverage our API integration with these systems to enable a full end-to-end data workflow automation capability for customers – a capability that historically has enabled use cases such as multi-use editing or real-time human analytics, even with massive data volumes.

Moving forward, I believe a broader set of customers are going to need this capability, particularly as they capture, store and manage data which must be shared between traditional business systems and Big Data analytics.

We even selectively invest in key metadata technology companies: a couple years ago we invested in a startup company called NerVve Technologies which has some very unique technology for indexing and searching video by defined images rather than text.

CCJ: How is the Internet of Things affecting your thinking and effecting your strategy? How do you simultaneously focus on the big issues as well as the challenges of what could be exponential leaps in the number of devices hooked to the Internet and the data that flows through them?

Janae: Great question. Our strategy is a mix of executing more of what we know, guided by input from our customers, partners and suppliers; and some brand new innovations.

On the one hand, we see the IoT as just our classic environment on steroids. Understand that we’ve been dealing with hundreds of very rich endpoints (e.g., cameras) streaming high volume data – and keeping it - for a long time. Quantum has customers, for example, storing and using over 30PB of environmental data, pulled down from devices like satellites, on-ground sensors, mobile cameras, etc.

So on one level it’s just an extension of what we’ve always done. As a result we have continued to invest - and expanded the scalability of our products – performance scale, capacity scale, “number of things” scale and management scale (also known as ease of use).

This was a key driver of our three plus-year development to release StorNext 5, which takes us to over 5+ billion files in a file system, and also a key driver of our investment in object storage with Lattus, which enables customers to grow their data exponentially over time without the need to ever worry about doing a forklift system migration.

At the same time, there are challenges in this massive end point and data growth that require brand new approaches – innovations in both product and go to market. New levels of data distribution and distributed user collaboration are driving the need for innovation in distributed data management.

This again is a metadata problem – how do you make sure everyone has the same view of the data? Or, more likely given that the physical and economic realities of the network won’t allow for this, how do you address the data coherency in a way which is practical and useful

As a market example: flexibility, ease of administration and cost effectiveness are driving the cloud. For Quantum this means delivering more end-to-end services than we have in the past.

 

About Roger Strukhoff
Roger Strukhoff (@IoT2040) is Executive Director of the Tau Institute for Global ICT Research, with offices in Illinois and Manila. He is Conference Chair of @CloudExpo & @ThingsExpo, and Editor of SYS-CON Media's CloudComputing BigData & IoT Journals. He holds a BA from Knox College & conducted MBA studies at CSU-East Bay.

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