Microsoft’s Azure Chief Tallies, Evaluates Cloud User Patterns

By Nicole Hemsoth

June 7, 2010

Last week Microsoft announced that around 10,000 customers were using their relatively new Azure platform. The company’s general manager for Azure, Doug Hauger, was careful to address the fact that while that is the approximate tally of customers, many are running services for a large set of users, thus the number of users likely far surpasses this figure. Still, this is an impressive number for a platform that only went out of its year-long beta in February of this past year.

While this is still a far cry from the anticipated many millions of technical computing users that exist in the much-discussed missing middle of HPC who could be ushered in by the promise of its developer-friendly cloud, the news here does not reside in the numbers necessarily, but how they are translated into practical use.

What Microsoft is noticing about these 10,000 customers and their associated use patterns is worth noting for the sake of everyone from potential end users in the technical and enterprise computing space to ISVs to, quite frankly, anyone who wishes to compete for the same broad base of users. HPC and enterprise are converging and accordingly, what’s relevant news for one is equally so for the other as far as cloud platforms and application development challenges and successes are concerned.

Let the Revelations Begin

In an address at the Cowan and Company Technology, Media and Telecom Conference in New York last week, Hauger (Microsoft’s General Manager for Windows Azure) provided a critical breakdown of who their customers were, at least in the general sense, and how they seemed to be deploying its cloud offering. Predictably, end user details were somewhat vague in terms of application-specific details, but actually offered more in the way of end user adoption uses than other companies in the space are willing to divulge. The company was able to shed some light on the current state of cloud adoption models and general use patterns by providing these details, which actually makes it far easier to comprehend real cloud deployment outside of the rhetoric about adoption that is usually offered when companies with similar offerings discuss their cloud products.

The following is a description of what Microsoft has been noticing with Azure, which is categorized into five key use patterns: on-and-off batch job computing; resource gains for small start-up operations; predictable bursting; unpredictable bursting; and perhaps most surprising, steady state operations.

Azure for On and Off Batch Job Computing

To put this in appropriate context, Microsoft uses the example of risk analysis and management and the deployment of a Monte Carlo simulation on trading data. One unnamed company was previously running this exclusively on Windows Server High Performance Computing Edition and now instead of that exclusivity, it still runs on Windows sometimes but on occasion it is batched out to the Azure platform where they can then scale out to thousands of instances at a time for a sort of “burst” mode but only for this one specific application.

Startups and Azure

It’s always a pleasure when cloud vendors name names in the case of startups being enabled by the cloud, and Microsoft mentions French retail analytics company Lokad to highlight Azure’s capability for the small business that has the capacity to scale. This firm started off very small, not wishing to invest in its own datacenter, and has now grown exponentially, thus making the scalability coupled with the lack of up-front costs to invest in its own cluster a perfect scenario. This appears to be one of the key areas for cloud in general outside of what we think of as traditional HPC, especially as the volumes of data continue to mount.

Unpredictable and Predictable Bursting in Azure

Although Hauger lists these two separately, they have so much in common that coupling them together allows these two possible uses to play off one another rather nicely. In terms of unpredictable bursting and the advantage it grants, Microsoft cites Kelly Blue Book which is a vast database of prices that is dynamic in nature. During the U.S. Cash for Clunkers program, suddenly everyone wanted to check on the real-time value of new cars. The way the company structured its Azure platform was rather interesting because instead of handling the entire traffic flow in the cloud or only utilizing it for certain workloads, one in four visitors was directed to Azure and if demand increased dramatically, the potential to scale out their front end was granted seamlessly. This case highlights perfectly the strategy for many Web 2.0 businesses who are looking to the cloud to handle peak workflow and unexpected hikes in visitors or customers.

Conversely, some businesses are able to anticipate surges like Domino’s pizza, for instance. While yes, pizza is a bit of out of the scope for HPC the example — whether we’re talking about food delivery based on online ordering systems or engineering-related simulations delivered as a service during expected times of the year when demand is higher — this is all important. Having the ability to provision for known events like audits, for example is one of the more widely-discussed advantages to being able to scale out to a platform like Azure, among others.

The Big Surprise

Hauger says Microsoft estimates that close to half of all current usage of Azure is “steady run-rate usage, where companies are moving their applications onto the platform, and just having them run in steady state.” In other words, their customers are simply shutting down their on-site machinery and migrating to Azure, presumably to remain running something in steady state for the long haul.

What Early Analysis of Azure Use Indicates for HPC

In summarizing the use patterns for the first 10,000 customers (and who knows how many users) Hauger indicated that in his opinion adoption has been very good and surprising, “in that I expected the adoption at the lower-end with the startups and with sort of individual developers and small business ISVs as they get in to the VAS business. Where we’re also seeing adoption is at the high end where we’re seeing enterprise companies coming in and actually moving into cloud computing.” He attributes this surprising finding to the economic situation, especially as it existed at the launch of Azure suggesting that this force prompted enterprise to look carefully at the challenges, benefits and risks of a multitenant environment. With this powerful economic incentive they were more willing to look closer at what the regulatory and compliance environment was in practical context versus overlooking cloud alternatives out of fear and misinformation.

Why Emphasis on HPC and Azure is Critical to Microsoft

Hauger notes that in terms of the better-than-expected adoption at the high end, Microsoft is seeing Azure as a suitable place for HPC applications. “It’s actually net additive for Microsoft because we’re selling our highest end server SKU on premises and we’re able to leverage our economies of scale and we have the the benefits of us running this highly efficient platform out in the cloud. And so we get the benefit of both.”

One of the questions that naturally emerges is how to move existing workloads into this cloud, which is a particularly relevant one in the HPC space. Hauger waffles for a moment, giving the standard answer to this question for any cloud vendor—that the ease of transition is dependent on too many variables to address in generalities—but then does make a few succinct points, claiming that “if your application is a big, huge hairball and very expensive to run, it’s still going to be a big, huge hairball over here in this IaaS space and be difficult to run and expensive. And that’s where if your application is architected and then sort of specific to Azure, if you have a stateless well-architected service-oriented application that’s written in .NET on premises, moving that over to the Windows Azure platform is a simple thing.”

Well, okay…”if” is the key word here, but this is an expected barrier for cloud adoption more generally, which is why Microsoft does seem to be doing a decent job through its Visual Studio offerings, for example, of making these things a bit more palatable. In terms of this issue, Hauger states that despite some of these challenges, the advantage they have with their Azure offering is based distinctly on the developer community. “We’ve come at this as being truly committed to building a platform, a cloud platform, for developers. For Microsoft, I think, more than anything else, our DNA is developers. And we’ve built a platform that really addresses their needs, making their lives easier to get into the cloud computing space. And there very few, I would actually say probably no other companies out there, that have built a cloud platform that are truly developer companies.”

If Microsoft is looking to differentiate itself by the value it provides to the developer, it will be interesting to see how their competition steps up to the plate to address similar concerns. Without a doubt, the sticky issue of getting applications into the cloud — which may sound basic now that there’s already a platform for them to run on — seems like a top topic to tackle as we continue to evaluate how the cloud is being deployed in more application-specific contexts.

Note: The full webcast of the interview with Doug Hauger can be found 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!

UK to Launch Six Major HPC Centers

March 27, 2017

Six high performance computing centers will be formally launched in the U.K. later this week intended to provide wider access to HPC resources to U.K. Read more…

By John Russell

AI in the News: Rao in at Intel, Ng out at Baidu, Nvidia on at Tencent Cloud

March 26, 2017

Just as AI has become the leitmotif of the advanced scale computing market, infusing much of the conversation about HPC in commercial and industrial spheres, it also is impacting high-level management changes in the industry. Read more…

By Doug Black

Scalable Informatics Ceases Operations

March 23, 2017

On the same day we reported on the uncertain future for HPC compiler company PathScale, we are sad to learn that another HPC vendor, Scalable Informatics, is closing its doors. Read more…

By Tiffany Trader

‘Strategies in Biomedical Data Science’ Advances IT-Research Synergies

March 23, 2017

“Strategies in Biomedical Data Science: Driving Force for Innovation” by Jay A. Etchings is both an introductory text and a field guide for anyone working with biomedical data. Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

Quants Achieving Maximum Compute Power without the Learning Curve

The financial services industry is a fast-paced and data-intensive environment, and financial firms are realizing that they must modernize their IT infrastructures and invest in high performance computing (HPC) tools in order to survive. Read more…

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 assets. Read more…

By Tiffany Trader

Google Launches New Machine Learning Journal

March 22, 2017

On Monday, Google announced plans to launch a new peer review journal and “ecosystem” Read more…

By John Russell

Swiss Researchers Peer Inside Chips with Improved X-Ray Imaging

March 22, 2017

Peering inside semiconductor chips using x-ray imaging isn’t new, but the technique hasn’t been especially good or easy to accomplish. Read more…

By John Russell

LANL Simulation Shows Massive Black Holes Break ‘Speed Limit’

March 21, 2017

A new computer simulation based on codes developed at Los Alamos National Laboratory (LANL) is shedding light on how supermassive black holes could have formed in the early universe contrary to most prior models which impose a limit on how fast these massive ‘objects’ can form. Read more…

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 assets. 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. Read more…

By John Russell

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 campaign. 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

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

New Japanese Supercomputing Project Targets Exascale

March 14, 2017

Another Japanese supercomputing project was revealed this week, this one from emerging supercomputer maker, ExaScaler Inc., and Keio University. The partners are working on an original supercomputer design with exascale aspirations. Read more…

By Tiffany Trader

Nvidia Debuts HGX-1 for Cloud; Announces Fujitsu AI Deal

March 9, 2017

On Monday Nvidia announced a major deal with Fujitsu to help build an AI supercomputer for RIKEN using 24 DGX-1 servers. Read more…

By John Russell

HPC4Mfg Advances State-of-the-Art for American Manufacturing

March 9, 2017

Last Friday (March 3, 2017), the High Performance Computing for Manufacturing (HPC4Mfg) program held an industry engagement day workshop in San Diego, bringing together members of the US manufacturing community, national laboratories and universities to discuss the role of high-performance computing as an innovation engine for American manufacturing. Read more…

By Tiffany Trader

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. Read more…

By John Russell

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 campaign. Read more…

By John Russell

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. Read more…

By John Russell

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

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 assets. Read more…

By Tiffany Trader

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular offerings such as Caffe, Theano, and Torch. Read more…

By John Russell

Lighting up Aurora: Behind the Scenes at the Creation of the DOE’s Upcoming 200 Petaflops Supercomputer

December 1, 2016

In April 2015, U.S. Department of Energy Undersecretary Franklin Orr announced that Intel would be the prime contractor for Aurora: Read more…

By Jan Rowell

Leading Solution Providers

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

Enlisting Deep Learning in the War on Cancer

December 7, 2016

Sometime in Q2 2017 the first ‘results’ of the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) will become publicly available according to Rick Stevens. He leads one of three JDACS4C pilot projects pressing deep learning (DL) into service in the War on Cancer. Read more…

By John Russell

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn’t made the task of parallel programming any easier. Read more…

By Tiffany Trader

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. Read more…

By Tiffany Trader

CPU Benchmarking: Haswell Versus POWER8

June 2, 2015

With OpenPOWER activity ramping up and IBM’s prominent role in the upcoming DOE machines Summit and Sierra, it’s a good time to look at how the IBM POWER CPU stacks up against the x86 Xeon Haswell CPU from Intel. Read more…

By Tiffany Trader

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

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