Cisco’s Cloud CTO Clarifies Strategy, Describes Datacenters of the Future

By Nicole Hemsoth

January 24, 2011

Lew Tucker discusses the datacenter of the future, sheds light on the “many clouds” theory, and describes the perfect storm in computing that is leading to new paradigms in IT.

Although Cisco has a viable stake in the future of cloud computing, its position has been difficult to pin down, despite the fact that their Unified Computing System (UCS) server architecture and network commitments present a solid chance for them to have an impact on the market.

Other than a few scattered announcements and the publicized positioning of Lew Tucker (of Sun and Salesforce fame) as Cloud CTO nearly six months ago, Cisco has been reluctant to announce a full-blown strategy around how it plans to stake its claim in the arena. The relative silence was broken this past week, when the company finally revealed its approach somewhat formally in a video interview with Tucker.

In something of a “coming out party” for Cisco’s cloud roadmap for the future, Lew Tucker chatted at length about what role the company might play in a space that is still shaking out its winners and losers on the cloud computing front.

At the beginning of his tenure, Tucker restated the value of the network as the heart of cloud—a fact that he claims is overlooked in all of the hype and excitement over cloud computing. In the strategy interview, however, he expands on the role of the network in securely delivering applications and gives us a glimpse into his view of the datacenter of the future.

A World of Many Clouds

When asked about the vendor shakeout that is inevitable as the cloud market matures in coming years, Tucker stated that instead of seeing the mega-providers who stake a claim in all verticals, there will be a development of industry-specific clouds.

He notes that clouds will form around needs and communities, thus for example within the healthcare industry there will be a small throng of HIPPA-compliant clouds as well as similarly fine-tuned offerings with a keen eye on the regulatory and security needs of government, financial services and others.

In light of this concept of specialized clouds, Tucker stated that some of Cisco’s enterprise-class customers are looking at what types of enterprise-class private clouds can be hosted by service providers now.

Despite this focus on “many clouds” serving disparate needs-based communities, Lew Tucker feels that in the future there is a “much larger cloud on the horizon” that is visible when we step back and look at the breadth of connected devices that are available at the present—a number that is sure to grow. From automobiles to sensors to mobile devices of all shapes and sizes, this complexity and range provides “the greatest example for why networking is so critical to the cloud” and how security is now an even more pressing issue.

In Tucker’s view, “if we look at the growing number of connected devices, whether mobile devices or even sensors with electrical power meters or even in the automobile itself, those devices are increasingly connected to the internet. So now you have in essence a  mini-cloud driving around on the highway—this is the greatest example for why networking is so critical to the cloud, now we need to have the security associated with these networked devices”

The Datacenter of the Future

Revealing Cisco’s general strategy in cloud computing over the coming years, Tucker emphasized the dual, complimentary roles of networking and system architecture as key to changing the way datacenters are built.

In addition to providing a rough approach to helping new customers build clouds using a “building blocks” approach wherein the essential infrastructure components are provided as well as looking at the broad range of devices to see the diverse array of end users and needs, one of the most striking elements of Tucker’s talk was his vision of how datacenters, based on the cloud model, are set to change.

In Lew Tucker’s opinion, there are certain points of dramatic inefficiency in the way datacenters are built and managed. As he described:

“When you build out internal architectures where you put an application on a server with an operating system, and then you move to the next application—as you add more and more applications into the datacenter, each with their own individual architectures, you don’t get economies of scale, you get very low utilization, and you get enormous complexity because you’ve tied the applications to the infrastructure.

Instead, what we’re doing with cloud is we’re saying build a cloud over the infrastructure…turn the infrastructure itself into a service—in which now the applications become virtualized so they can pick whatever operating system they need, they’re running on a virtual machine, they can be turned on or off—they are essentially being provided on-demand.

This means that the IT organization at these future datacenters can scale large to get efficiencies that way and can become totally automated since the infrastructure’s main goal is simply to provide a pool of resources to be used by the applications. This is a much more efficient way to build out datacenters and drive down cost as well as increase agility.”

Tucker also explained the concept of the network as a platform, which in essence means “creating a network platform driven by programmatic APIs we can do things like automate and build systems like UCS which is driven by APIs. Now software itself can do all the provisioning. It’s no longer the individual switch or router, it’s the system that comprises the network that drives it.”

While it is not difficult to see the position of Cisco’s UCS in the cloud strategy-wise, Tucker explains that part of the strategy is to actually build APIs into any networkable product the company sells that will touch the cloud.

A Perfect Storm in Computing

Perhaps not surprisingly, Tucker sees the cloud as the product of a natural course in computing evolution, all with the network at the heart of progress.  He briefly tracks the crescendo in network and architecture innovation that has led to cloud computing on a ten-year graph, beginning in the 1960s with mainframes, the minicomputer in the 70s, the client server to web transition that took place from the 80s into the 90s, followed by virtualization in 2000—and into this new decade that is defined by cloud.

This progression on a decade-long chart is, in Tucker’s view, a movement that is simply the manifestation of the new internet, a natural extension of a movement that has been building and compounding, just as it has with other technological paradigm shifts.
 
In addition to faster, more ubiquitous access to networked devices that are providing this next opportunity in computing, Tucker describes the “perfect storm” that is brewing. These storm clouds are “forming between the continued advance of Moore’s Law, which is driving down the cost of computing, coupled with the explosive growth of the Internet, as well as technology advances like virtualization.” While he acknowledges that this new era is still dawning, there are signs that cloud computing is the next major shift in IT by pointing to cloud service providers like Amazon Web Services (AWS). 

Tucker argues that AWS is at the forefront of making it possible for web developers and small companies to get into cloud computing—and that this is changing the economics of computing in yet another way.

As Cisco’s Cloud CTO claims, “If you’re going to Sandhill Road to get money as a startup they’re not going to give you money for infrastructure; they’re going to say you go and buy it from the cloud—that way they lower their risk and there’s the pay-as-you-go model.”

In addition to seeing public cloud resources as driving business forward, Tucker also sees rapid movement in enterprise adoption of private clouds as companies see this trend, which is driven by economies of scale, and seek to take advantage of it.

The problem is, until this more refined model of datacenter innovation takes place as described, it will be difficult for enterprise datacenters to achieve the same cost benefit. This is where Cisco is making its play—in refining datacenter architecture to look more like the large cloud service providers versus the traditional model of infrastructure as the carrier of applications.

You can view the full interview with Tucker here.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

DARPA Continues Investment in Post-Moore’s Technologies

July 24, 2017

The U.S. military long ago ceded dominance in electronics innovation to Silicon Valley, the DoD-backed powerhouse that has driven microelectronic generation for decades. With Moore's Law clearly running out of steam, the Read more…

By George Leopold

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in 2017 with scale-up production for enterprise datacenters and Read more…

By Tiffany Trader

Trinity Supercomputer’s Haswell and KNL Partitions Are Merged

July 19, 2017

Trinity supercomputer’s two partitions – one based on Intel Xeon Haswell processors and the other on Xeon Phi Knights Landing – have been fully integrated are now available for use on classified work in the Nationa Read more…

By HPCwire Staff

Fujitsu Continues HPC, AI Push

July 19, 2017

Summer is well under way, but the so-called summertime slowdown, linked with hot temperatures and longer vacations, does not seem to have impacted Fujitsu's output. The Japanese multinational has made a raft of HPC and A Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

HPE Servers Deliver High Performance Remote Visualization

Whether generating seismic simulations, locating new productive oil reservoirs, or constructing complex models of the earth’s subsurface, energy, oil, and gas (EO&G) is a highly data-driven industry. Read more…

Researchers Use DNA to Store and Retrieve Digital Movie

July 18, 2017

From abacus to pencil and paper to semiconductor chips, the technology of computing has always been an ever-changing target. The human brain is probably the computer we use most (hopefully) and understand least. This mon Read more…

By John Russell

The Exascale FY18 Budget – The Next Step

July 17, 2017

On July 12, 2017, the U.S. federal budget for its Exascale Computing Initiative (ECI) took its next step forward. On that day, the full Appropriations Committee of the House of Representatives voted to accept the recomme Read more…

By Alex R. Larzelere

Summer Reading: IEEE Spectrum’s Chip Hall of Fame

July 17, 2017

Take a trip down memory lane – the Mostek MK4096 4-kilobit DRAM, for instance. Perhaps processors are more to your liking. Remember the Sh-Boom processor (1988), created by Russell Fish and Chuck Moore, and named after Read more…

By John Russell

Women in HPC Luncheon Shines Light on Female-Friendly Hiring Practices

July 13, 2017

The second annual Women in HPC luncheon was held on June 20, 2017, during the International Supercomputing Conference in Frankfurt, Germany. The luncheon provides participants the opportunity to network with industry lea Read more…

By Tiffany Trader

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

Fujitsu Continues HPC, AI Push

July 19, 2017

Summer is well under way, but the so-called summertime slowdown, linked with hot temperatures and longer vacations, does not seem to have impacted Fujitsu's out Read more…

By Tiffany Trader

Researchers Use DNA to Store and Retrieve Digital Movie

July 18, 2017

From abacus to pencil and paper to semiconductor chips, the technology of computing has always been an ever-changing target. The human brain is probably the com Read more…

By John Russell

The Exascale FY18 Budget – The Next Step

July 17, 2017

On July 12, 2017, the U.S. federal budget for its Exascale Computing Initiative (ECI) took its next step forward. On that day, the full Appropriations Committee Read more…

By Alex R. Larzelere

Women in HPC Luncheon Shines Light on Female-Friendly Hiring Practices

July 13, 2017

The second annual Women in HPC luncheon was held on June 20, 2017, during the International Supercomputing Conference in Frankfurt, Germany. The luncheon provid Read more…

By Tiffany Trader

Satellite Advances, NSF Computation Power Rapid Mapping of Earth’s Surface

July 13, 2017

New satellite technologies have completely changed the game in mapping and geographical data gathering, reducing costs and placing a new emphasis on time series Read more…

By Ken Chiacchia and Tiffany Jolley

Intel Skylake: Xeon Goes from Chip to Platform

July 13, 2017

With yesterday’s New York unveiling of the new “Skylake” Xeon Scalable processors, Intel made multiple runs at multiple competitive threats and strategic Read more…

By Doug Black

Perverse Incentives? How Economics (Mis-)shaped Academic Science

July 12, 2017

The unintended consequences of how we fund academic research—in the U.S. and elsewhere—are strangling innovation, putting universities into debt and creatin Read more…

By Ken Chiacchia, Senior Science Writer, Pittsburgh Supercomputing Center

Google Pulls Back the Covers on Its First Machine Learning Chip

April 6, 2017

This week Google released a report detailing the design and performance characteristics of the Tensor Processing Unit (TPU), its custom ASIC for the inference Read more…

By Tiffany Trader

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Just how close real-wo Read more…

By John Russell

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its a Read more…

By Tiffany Trader

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the cam Read more…

By John Russell

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

Nvidia’s Mammoth Volta GPU Aims High for AI, HPC

May 10, 2017

At Nvidia's GPU Technology Conference (GTC17) in San Jose, Calif., this morning, CEO Jensen Huang announced the company's much-anticipated Volta architecture a Read more…

By Tiffany Trader

Facebook Open Sources Caffe2; Nvidia, Intel Rush to Optimize

April 18, 2017

From its F8 developer conference in San Jose, Calif., today, Facebook announced Caffe2, a new open-source, cross-platform framework for deep learning. Caffe2 is the successor to Caffe, the deep learning framework developed by Berkeley AI Research and community contributors. Read more…

By Tiffany Trader

Leading Solution Providers

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

Russian Researchers Claim First Quantum-Safe Blockchain

May 25, 2017

The Russian Quantum Center today announced it has overcome the threat of quantum cryptography by creating the first quantum-safe blockchain, securing cryptocurrencies like Bitcoin, along with classified government communications and other sensitive digital transfers. Read more…

By Doug Black

MIT Mathematician Spins Up 220,000-Core Google Compute Cluster

April 21, 2017

On Thursday, Google announced that MIT math professor and computational number theorist Andrew V. Sutherland had set a record for the largest Google Compute Engine (GCE) job. Sutherland ran the massive mathematics workload on 220,000 GCE cores using preemptible virtual machine instances. Read more…

By Tiffany Trader

Google Debuts TPU v2 and will Add to Google Cloud

May 25, 2017

Not long after stirring attention in the deep learning/AI community by revealing the details of its Tensor Processing Unit (TPU), Google last week announced the Read more…

By John Russell

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of Read more…

By Alex Woodie

Six Exascale PathForward Vendors Selected; DoE Providing $258M

June 15, 2017

The much-anticipated PathForward awards for hardware R&D in support of the Exascale Computing Project were announced today with six vendors selected – AMD Read more…

By John Russell

Top500 Results: Latest List Trends and What’s in Store

June 19, 2017

Greetings from Frankfurt and the 2017 International Supercomputing Conference where the latest Top500 list has just been revealed. Although there were no major Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Share This