Comparing the Cost Continued...

The next step was to select our benchmarks and calculate their costs. We extracted two workloads that are common to many product development companies: a regression workload that arises when a team collaborates on the same development task, and a technical workload when an individual is using computer models to generate new insight/knowledge.

The regression workload can be generated by a software design team developing a new application, a financial engineering team back testing new trading strategies, or a mechanical design team designing a new combustion engine that runs on alternative fuels.

The technical workload can be a new rendering algorithm to model fur on an animated character, or a new economic model that drives critical risk parameters in a trading strategy, or an acoustic characterization of a automobile cabin.

The first workload is characterized by a collection of tests that are run to guarantee correctness of the product during development. Our test case for a typical regression run is a 1000 tests that run at an average of 15 minutes each. Each developer typically runs two such regressions per day, and for a 50 person design team this yields 100 regression runs per day. The total workload equates to roughly 1050 cpu hours per hour and would keep a 1000 processor cluster 100% occupied.

The second workload shifts the focus from capacity to capability. The computational task is a single simulation that requires 5 cpu hours to complete. The benchmark workload is the work created by a ten person research team that runs five simulations per day. Many of these algorithms can actually run in parallel and such a task could run in 30 minutes when executed in parallel on ten processors. Latency to solution is a major driver on R&D team productivity and this workload would have priority over the regression workload particularly during the work day. The total workload equates to roughly 31 cpu hours per hour because this workload runs just in the eight hour work day.

Running these two workloads on our cloud computing providers we get the following costs per day:

Benchmark	Amazon	Rackspace/Mosso
Regression Workload	$25,075.17	$18,250.25
Knowledge Discovery	$265.09	$230.13

The total cost of $20-25k per day makes the regression workload too expensive for outsourcing to today's cloud providers. A 1000 processor on-premise x86 cluster costs roughly $10k/day including overhead and amortization. The cost of bulk computes like the regression workload needs to go down by at least a factor of 5x before cloud computing can bring in small and medium-sized enterprises. However, the technical workload at $250/day is very attractive to move to the cloud since this workload is periodical with respect to the development cycle and it moves CapEx to OpEx to frees up capital for other purposes.

The big cost difference between Rackspace/Mosso and Amazon is the Disk I/O charge. It doesn't appear that Rackspace monetizes this cost. From the cost models, this appears to be a liability for them since the Disk I/O cost (moving the VM image and data sets to and from disk) represents roughly 20% of the total costs. Fast storage is notoriously expensive so this appears to be a weakness of Rackspace.

In a future article we will dissect these costs further.

Comparing Costs of Different Cloud Computing Providers

The past month we have been trying to quantify the cost of moving some of our workloads into the cloud. It has been a very painful experience. Each vendor insists on mixing up the pricing in such a way that direct comparisons require major mental gymnastics. On top of that, the big three, IBM Blue Cloud, HP Adaptive Infrastructure as a Service, or AIaaS (who in the marketing department came up with that one?), and Sun Network.com are so incredibly opaque that we have just given up. Furthermore, Sun started out at $1/cpu hour and that simply is not competitive. Sun has taken the site down and the home page of the site claims that they are working on something else. Out of sheer frustration, we have ditched IBM and HP as well. It appear that they are catering to their existing deep-pocket customers and we do not expect their solutions to be cost competitive for the disruptive cloud computing concept that will usher in the new economics.

Many activities at the US National Labs are directed to evaluate if it is cost effective to move to AWS or similar services. To be able to compare our results to that research we decided to map all costs into AWS compatible pricing units. This yielded the following very short list:

Provider	CPU $/cpu-hr	Disk I/O $/GB	Internet I/O $/GB	Storage $GB-month
Amazon	$0.80	$0.10	$0.17	$0.15
Rackspace/Mosso	$0.72	$0.00	$0.25	$0.50

The reason for the short list is that there are very few providers that actually sell computes. Most of the vendors that use the label cloud provider are actually just hosting companies of standard web services. Companies like 3Tera, Bungee Labs, Appistry, and Google cast their services in terms of web application services, not generic compute services. This makes these services not applicable to the value-add computes that are common during the research and development phase of product companies.

In the next article we are going to quantify the cost of different IT workloads.

Dynamic IT

CIO Magazine just surveyed 173 IT business leaders to gauge what the common attitudes are towards cloud computing in the enterprise. 58 percent indicated that cloud computing will dramatically change the IT business, and 47 percent said they are already using it. On the other side, 18 percent think that cloud computing is a fad. survey

CIO used the broad definition of cloud computing: "a style of computing where massively scalable IT-related capabilities are provided 'as a service' using Internet technologies to multiple external customers". Other terms used are "on-demand services", "cloud services", "Software-as-a-Service".

The survey confirmed that cloud computing is a solution to the need for flexibility in IT resource management. IT needs flexibility and cost savings, but is unwilling to jump in with both feet until some lingering concerns are addressed: the top concern being security.

Cloud computing will be used in many pilot/proof-of-concept projects by the incumbents, and it will be experimented with as full blown business models by a growing cadre of start-ups. We have described this many times in this blog that the cloud computing model will be driven by the small and medium business segment because they value cost savings over security or SLAs. And typically with technologies that offer dramatic cost savings, when successful, there will be carnage among the companies that are holding on too tightly to old fashioned business models.

Bluehouse is in public beta

IBM announced cloud computing applications at Lotusphere in January of this year. A service called Bluehouse is a web-delivered social networking and collaboration service targeted to the SMB market. Bluehouse enables people to share documents, projects, and contacts, and offers online conferencing features as well. The Bluehouse service has gone into public beta.

Willy Chiu, VP at IBM of High Performance On-Demand Solutions stated: "We are moving our clients, the industry and even IBM itself to have a mixture of data and applications that live in the data centre and in the cloud." IBM's approach is to expand its cloud computing offerings through a 'four-pronged strategy':

Deliver a home spun set of cloud services

Enable ISVs to design and build cloud services

Help customers integrate cloud services into their business

Sell cloud computing infrastructure to businesses for on-premise deployments

In addition to Bluehouse, IBM is also rolling out a handful of web services. Policy Tester On-Demand will automate the scanning of web content to ensure that it complies with industry legislation, and AppScan On-Demand will scan web applications for security bugs. Sean Poulley, VP of Online Collaboration Services compared the Bluehouse tools to those of Microsoft and Google: "Whereas Microsoft is document centric and Google is email centric, our solution is a mixture of both".

IBM's $400M investment in a new data center to support this new mid-market SaaS/Cloud Computing services portfolio, brings another large player into the mix. These tools have been a long time coming but with every major brand now on-line, the branding wars can begin.

Windows Server on Amazon EC2

As soon as I finished yesterday's blog entry, I became aware of a posting by Amazon's CTO, Werner Vogels, where he announces that Microsoft's Windows Server is available on Amazon EC2. According to Vogels: "we can now run the majority of popular software systems in the cloud". So there you have it, both Amazon and Microsoft are/will be offering Windows based applications in the cloud.

According the Vogels' blog the area that accelerated to adoption of this functionality in Amazon's Elastic Cloud was the entertainment industry due to the wide range of excellent codecs available for Windows. Here is the power of Microsoft's dominance of the client side translating into a huge benefit for cloud adoption. With 20-20 hindsight, the benefit of quality codecs is now obvious, and it will drive very quick adoption of Windows in the Cloud. Content apparently is still king and thus the conduit that delivers it is a critical component. Turns out that Microsoft does have an unfair advantage in the Cloud space.

Red Dog and Windows Cloud: Microsoft is coming!

Microsoft's Professional Developers Conference 2008 makes it clear that the nature of software development is radically changing. Microsoft, as no other vendor, has always recognized that the riches of the platform are directly proportional to the number of good developers that work on your platform. As such, Microsoft has always had absolutely fantastic development tools for all aspects and segments of the IT workload. Typically, they are not leading with technologies, but they sure know how to package and disseminate technology when it is ready. The C/C++ compilers are one example, Active Server Pages and C# are others.

Enter HPC, cluster, and cloud computing: so far this has been driven by Linux mainly because there have been no commercial offerings that solve the problem of pedal-to-the-metal applications that need tight integration with the underlying hardware and operating system services such as memory, communication stacks and I/O.

For a decade now, Google has blazed the way with web-scale hardware and software infrastructures that are showing their true value. And now Amazon Web Services is also offering an IT-for-rent model that is perfect for web based services. Detrimental to Microsoft, Google and Amazon Web Services do not enable any Microsoft application software, operating systems, development tools, or even web services. Clearly, this is moving momentum away from the Microsoft universe and they have to counter to stay relevant.

Red Dog appears to be the first salvo across developers bows that Microsoft is coming. Red Dog is Microsoft's IT-for-rent story, as an answer to Linux centric Amazon Web Services. The second shot is dubbed "Windows Cloud". It is a development environment for Internet-based applications, as an answer to Python centric Google Gears.

Given Microsoft's track record to build very productive development environments that have the hearts of most internal IT shops, I am confident that this will accelerate the Cloud Computing adoption in the mid-market.

Google and corporate espionage

The release of Google's Chrome and the original EULA that was bound to it has opened an interesting debate about how much Google knows about us, and maybe more ominously, how much it knows about your business. I would postulate that Google knows more about your business than you do.

But first, the EULA flap. The old EULA stated: "You retain copyright and any other rights you already hold in Content which you submit, post or display on or through, the Services. By submitting, posting or displaying the content you give Google a perpetual, irrevocable, worldwide, royalty-free, and non-exclusive license to reproduce, adapt, modify, translate, publish, publicly perform, publicly display, and distribute any Content which you submit, post, or display on or through, the Services."

Clearly, Google didn't mess this up: they are a big company with a good legal team, so we have to assume that this EULA was deliberately written the way it was. Since Google is a conduit for content, while using this content for its own profit without wanting to pay for it, the EULA makes a lot of sense from Google's perspective. Equally clear is that asking for a "...perpetual, irrevocable, worldwide, royalty-free, and non-exclusive license to reproduce, adapt, modify... publish" is simply unbelievably aggressive leading to a revolt that forced Google to rewrite the EULA.

For Google's business model to remain viable, it has to extract customer behavior and owning the browser makes that a million times easier. Secondly, searching for information on the internet is essential to today's business, so Google has both customer behavior and customer knowledge searches. This means that it can deduce purpose and effectively learn what you learn. Finally, collective knowledge of your workforce adds a whole new layer of understanding for Google. For example, say you have decided to plan for a new product. The product research your organization is doing will be localized in time and in scope, thus making it easy to filter out of the backdrop of all other searches that your organization is doing. This means that your new product plans will be visible to Google and its clever group of data mining specialists. Their whole job is to mine for data like this so that the Google service can provide you with contextual information that you could use and thus will generate revenue for Google. Google simply needs to know more about your business than you do to continue to generate revenue.

Google of course is not unique in this respect. Any ad-revenue driven Services will need some spying and semantic inference to yield context to generate revenue. In the consumer space, it appears that people are more willing to part with their preferences in exchange for free access. But the cost for business seems a bit steep, particularly big business, and it comes as a surprise to me that only the media companies have been suing Google. Maybe the Google EULA flap will invigorate the debate on how much data a SaaS or Cloud provider can extract and own and how this needs to be regulated.