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!

Geospatial Data Research Leverages GPUs

August 17, 2017

MapD Technologies, the GPU-accelerated database specialist, said it is working with university researchers on leveraging graphics processors to advance geospatial analytics. The San Francisco-based company is collabor Read more…

By George Leopold

Intel, NERSC and University Partners Launch New Big Data Center

August 17, 2017

A collaboration between the Department of Energy’s National Energy Research Scientific Computing Center (NERSC), Intel and five Intel Parallel Computing Centers (IPCCs) has resulted in a new Big Data Center (BDC) that Read more…

By Linda Barney

Google Releases Deeplearn.js to Further Democratize Machine Learning

August 17, 2017

Spreading the use of machine learning tools is one of the goals of Google’s PAIR (People + AI Research) initiative, which was introduced in early July. Last week the cloud giant released deeplearn.js as part of that in Read more…

By John Russell

HPE Extreme Performance Solutions

Leveraging Deep Learning for Fraud Detection

Advancements in computing technologies and the expanding use of e-commerce platforms have dramatically increased the risk of fraud for financial services companies and their customers. Read more…

Spoiler Alert: Glimpse Next Week’s Solar Eclipse Via Simulation from TACC, SDSC, and NASA

August 17, 2017

Can’t wait to see next week’s solar eclipse? You can at least catch glimpses of what scientists expect it will look like. A team from Predictive Science Inc. (PSI), based in San Diego, working with Stampede2 at the Read more…

By John Russell

Microsoft Bolsters Azure With Cloud HPC Deal

August 15, 2017

Microsoft has acquired cloud computing software vendor Cycle Computing in a move designed to bring orchestration tools along with high-end computing access capabilities to the cloud. Terms of the acquisition were not disclosed. Read more…

By George Leopold

HPE Ships Supercomputer to Space Station, Final Destination Mars

August 14, 2017

With a manned mission to Mars on the horizon, the demand for space-based supercomputing is at hand. Today HPE and NASA sent the first off-the-shelf HPC system i Read more…

By Tiffany Trader

AMD EPYC Video Takes Aim at Intel’s Broadwell

August 14, 2017

Let the benchmarking begin. Last week, AMD posted a YouTube video in which one of its EPYC-based systems outperformed a ‘comparable’ Intel Broadwell-based s Read more…

By John Russell

Deep Learning Thrives in Cancer Moonshot

August 8, 2017

The U.S. War on Cancer, certainly a worthy cause, is a collection of programs stretching back more than 40 years and abiding under many banners. The latest is t Read more…

By John Russell

IBM Raises the Bar for Distributed Deep Learning

August 8, 2017

IBM is announcing today an enhancement to its PowerAI software platform aimed at facilitating the practical scaling of AI models on today’s fastest GPUs. Scal Read more…

By Tiffany Trader

IBM Storage Breakthrough Paves Way for 330TB Tape Cartridges

August 3, 2017

IBM announced yesterday a new record for magnetic tape storage that it says will keep tape storage density on a Moore's law-like path far into the next decade. Read more…

By Tiffany Trader

AMD Stuffs a Petaflops of Machine Intelligence into 20-Node Rack

August 1, 2017

With its Radeon “Vega” Instinct datacenter GPUs and EPYC “Naples” server chips entering the market this summer, AMD has positioned itself for a two-head Read more…

By Tiffany Trader

Cray Moves to Acquire the Seagate ClusterStor Line

July 28, 2017

This week Cray announced that it is picking up Seagate's ClusterStor HPC storage array business for an undisclosed sum. "In short we're effectively transitioning the bulk of the ClusterStor product line to Cray," said CEO Peter Ungaro. Read more…

By Tiffany Trader

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

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

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

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

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

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

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

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

Leading Solution Providers

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

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

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

IBM Clears Path to 5nm with Silicon Nanosheets

June 5, 2017

Two years since announcing the industry’s first 7nm node test chip, IBM and its research alliance partners GlobalFoundries and Samsung have developed a proces Read more…

By Tiffany Trader

Messina Update: The US Path to Exascale in 16 Slides

April 26, 2017

Paul Messina, director of the U.S. Exascale Computing Project, provided a wide-ranging review of ECP’s evolving plans last week at the HPC User Forum. Read more…

By John Russell

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

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