4. Cloud computing is that
you can have all the
resources you want...as
an infinite amount of
capacity living outside in
the cloud on the
Internet for you to use.
Werner Vogels, CTO of Amazon
http://thenextweb.com/wp-content/uploads/2008/04/thenextweb-0485-2.jpg
5. In 10 years, what compute
tasks will still be running on
machines you own?
17. Is security an accelerator or
a brake?
Reason to avoid clouds
23%
Reason to move to clouds
43%
No opinion
34%
http://www.thewhir.com/web-hosting-news/102309_IT_Firms_Skeptical_About_Cloud_PEER_1_Study
18. Network Operating Management
Software
equipment systems tools
Sold to
Enterprises MSPs
28. OO promised so much
Object oriented (OOD) techniques and ADA (1985-95)
Increased NASA code reuse by 300 percent
Reduced all systems costs by 40 percent
Shortened development cycle time by 25 percent
Slashed error rates by 62 percent
29. But fell so short
Only 15-20% of FDD software written in Ada
Naysayers resisted the language change
Wanted to stay with what they knew (FORTRAN)
Had reusable components maintained by others
Evangelists didn’t help
Promised too much too soon
Avoided root issue: Lack of environment
30. What are the characteristics
of apps that work well in the
cloud?
31. What does a CIO need to do
to encourage a cloud-
compatible developer
mindset?
32. How long before in-house
computing is irresponsibly
expensive?
Unlike enterprises, clouds are focusing on cost
reduction and IT efficiency as their core business
33. Do we really need standards
yet?
Loose consensus and working code trumps
committees every time
FAIL HAIL
OSI HTTP stack
ATM TCP/IP
WS-X REST
36. A bit about Bitcurrent
Analysis and research of emerging technologies
Cloud computing, web performance, human/computer
interaction, emergent communications technology
49. How to think about costs
800,000 Variable
Fixed
Upfront
600,000
Cost
400,000
200,000
0
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
50. How to think about costs
800,000 Variable
Fixed
Upfront
600,000
Cost
400,000
200,000
0
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
51. How to think about costs
800,000 Variable
Fixed
Upfront
600,000
Cost
400,000
200,000
0
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
52. How to think about costs
800,000 Variable
Fixed
Upfront
600,000
Cost
400,000
200,000
0
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
53. IT costs: Upfront
Capital investment (often, “capex”)
Don’t overlook rewriting, retooling, retraining, data
migration
For many enterprises, this is just the cost of periodic
upgrades. They already have equipment.
54. IT costs: Fixed
Happen no matter what; a measure of leanness
May be shared with other activities, and therefore not
eliminated (this is often invoked in defense of jobs)
55. IT costs: Variable
Tied to delivery; a
measure of efficiency 500
Needs to be less
Servers per sysadmin
375
than the resulting
revenue or you’ll be 250
called a cost center
125
Enterprises
underestimate the true 0
costs of service delivery Enterprise Cloud provider
Barry Lynn of 3Tera
56. Clouds might seem pricey today
£30,000,000
£22,500,000
£15,000,000
£7,500,000
£0
Start up cost Year 2 Year 4 Year 6 Year 8 Year 10
Data Centre Cloud
2009 IDC analysis of running 100% of a big enterprise’s IT in-house vs on-demand
Used with permission. Copyright (c) IDC
57. Clouds might seem pricey today
£30,000,000
£22,500,000
£15,000,000
£7,500,000
£0
Start up cost Year 2 Year 4 Year 6 Year 8 Year 10
Data Centre Cloud
2009 IDC analysis of running 100% of a big enterprise’s IT in-house vs on-demand
Used with permission. Copyright (c) IDC
58. Clouds might seem pricey today
£30,000,000
£22,500,000
£15,000,000
£7,500,000
£0
Start up cost Year 2 Year 4 Year 6 Year 8 Year 10
Data Centre Cloud
2009 IDC analysis of running 100% of a big enterprise’s IT in-house vs on-demand
Used with permission. Copyright (c) IDC
59. Clouds might seem pricey today
£30,000,000
£22,500,000 Final score:
DC: £15M
Cloud: £26M
£15,000,000 After year 3,
cloud costs
exceed DC
£7,500,000 Even with 3-year
refresh cycles of 30%
DC remains cheaper
£0
Start up cost Year 2 Year 4 Year 6 Year 8 Year 10
Data Centre Cloud
2009 IDC analysis of running 100% of a big enterprise’s IT in-house vs on-demand
Used with permission. Copyright (c) IDC
64. But we’re deluded
£50,000,000 Year 6 requires build-
out for new facility +
expensive refresh due
DC reaches space to limited space
£37,500,000
capacity in year 3,
50% refresh to high-
end servers needed
£25,000,000
£12,500,000 Cloud costs are dynamic
so even if bad decisions
are made initially, capacity
can be ramped up linearly
£0
Start up cost Year 2 Year 4 Year 6 Year 8 Year 10
Data Centre Cloud
2009 IDC analysis of running 100% of a big enterprise’s IT in-house vs on-demand
Used with permission. Copyright (c) IDC
75. Are you negotiating with
cities & power companies?
“...Microsoft pays an annual utility bill just north of $13
million, which translates to just over 3.8 cents/kwh as
opposed to 5.7 cents/kwh for the ELP rate...”
http://www.virtual-strategy.com/Features/Microsoft-and-Google-Cloud-Computing-Dominance-Through-Renewable-Energy/-5.html
77. Idle
capacity,
lack of
automation,
etc.
IT server
costs
78. Idle
capacity,
lack of
automation,
etc.
IT server
costs
Private
cloud
costs
79. Idle
capacity,
lack of
automation,
etc.
IT server
costs
Ping, power,
pipe,
Private efficiencies
cloud
costs
80. Idle
capacity,
lack of
automation,
etc.
IT server
costs
Ping, power,
pipe,
Private efficiencies
cloud
costs Public
cloud
costs
81. So you won’t be building
your own data centers
70% of the Global 1000 must
“Modify their data center facilities significantly” by 2012
Increase energy from 35 to 70 watts/sq. ft (sometimes up
to 300 watts)
Gartner says to
Monitor energy use
Quantifying all capital and operation changes needed
Deploy virtualization and workload management tools
http://www.virtual-strategy.com/Features/Microsoft-and-Google-Cloud-Computing-Dominance-Through-Renewable-Energy.html
88. • 60 seconds per page
Desktop EC2 • 200 machine
Pages 17,481 17,481 instances
Minutes/page 1 1 • 1,407 hours of virtual
# of machines 1 200 machine time
Total minutes 17,481 • Searchable database
Total hours 291.4 26.0 available 26 hours
Total days 12.1 1.1 later
• $144.62 total cost
99. No straight answer
38% 47%
ITI “Unsure about adopting “Won’t consider the cloud in
cloud services” next 12 months”
0% 25% 50% 75% 100%
100. No straight answer
38% 47%
ITI “Unsure about adopting “Won’t consider the cloud in
cloud services” next 12 months”
F5 Networks 82%
“In trial, implementation, or use of public clouds”
0% 25% 50% 75% 100%
101. No straight answer
38% 47%
ITI “Unsure about adopting “Won’t consider the cloud in
cloud services” next 12 months”
F5 Networks 82%
“In trial, implementation, or use of public clouds”
“Implementing
cloud services”
60% 8%
CIO.com 29% “Actively researching (cloud on
“No interest in the cloud”
radar)”
0% 25% 50% 75% 100%
117. Conclusions
Clouds make good economic sense
They aren’t an either/or
When you consider opportunities, not just costs,
they’re overwhelmingly compelling
But new cost tradeoffs emerge with elastic capacity
Here’s how one guy who should know—Werner Vogels of Amazon.com—describes it.
There’s always specialization along legal borders. Consider, for example, the Patriot Act
As a horde of angry librarians informed us in 2006, they’re specifically prohibited from letting you know when someone has looked at your data or behavior. For this reason, many countries won’t let certain companies use data storage or computation within other nations. So there may be a niche offering within your own country.
Remember Object-Oriented Programming?
Object oriented design (OOD) techniques and ADA (1985-95)
Flight Dynamics Division
Only a certain percentage of NASA’s coders could make that jump. With sharded, shared-nothing, distributed data, that may happen again.
15:10
If you want to post pictures or comments, use #Interop and #ECS
Yossi - I just wanted to let you know where I was staying at Burning Man (and urge all of you to go there!)
First of all: Let’s define the discussion.
If someone wants to have a conversation with me about clouds, they need to pick a tier, and a private or public model. Then we can compare facts.
If someone wants to have a conversation with me about clouds, they need to pick a tier, and a private or public model. Then we can compare facts.
If someone wants to have a conversation with me about clouds, they need to pick a tier, and a private or public model. Then we can compare facts.
If someone wants to have a conversation with me about clouds, they need to pick a tier, and a private or public model. Then we can compare facts.
If someone wants to have a conversation with me about clouds, they need to pick a tier, and a private or public model. Then we can compare facts.
Today, I mean these ones.
Now, let’s talk about cloud costs and ROI
Any cost model consists of three kinds of spending: Upfront money spent to kick things off; fixed spending that doesn’t change whether you sell one or a billion units; and variable spending associated with the amount you sell.
Any cost model consists of three kinds of spending: Upfront money spent to kick things off; fixed spending that doesn’t change whether you sell one or a billion units; and variable spending associated with the amount you sell.
Any cost model consists of three kinds of spending: Upfront money spent to kick things off; fixed spending that doesn’t change whether you sell one or a billion units; and variable spending associated with the amount you sell.
Any cost model consists of three kinds of spending: Upfront money spent to kick things off; fixed spending that doesn’t change whether you sell one or a billion units; and variable spending associated with the amount you sell.
Upfront costs are pretty straightforward. And with many enterprises at 10% utilization, virtualization can extend the lifespan of existing infrastructure substantially.
Then there are the fixed IT costs that you can’t avoid. Clouds can drop these, but if you have IT running internal systems, they won’t magically evaporate when things move to the cloud. What’s more, clouds mean new tasks for IT -- things like provisioning, managing policy, and so on.
The variable costs are where clouds are really strong. This stuff is the costs that increase with service delivery volumes. Cloud operators can handle 500-1000 servers per person (they have to!) and completely automate everything. They also focus on cost measurement and accounting, which is a luxury for many enterprises but a necessity for clouds. Management software is an afterthought for many IT departments; but it’s a competitive advantage for cloud operators
A naive look at clouds (intentionally naive, we should point out) from IDC says that clouds are expensive
A naive look at clouds (intentionally naive, we should point out) from IDC says that clouds are expensive
A naive look at clouds (intentionally naive, we should point out) from IDC says that clouds are expensive
A naive look at clouds (intentionally naive, we should point out) from IDC says that clouds are expensive
A naive look at clouds (intentionally naive, we should point out) from IDC says that clouds are expensive
A naive look at clouds (intentionally naive, we should point out) from IDC says that clouds are expensive
Remember: Google gets 38% server utilization, with insane effort. So this is likely unattainable. What’s more, cloud providers are competing, and may (assuming interoperability of some kind) reduce their costs, too.
Remember: Google gets 38% server utilization, with insane effort. So this is likely unattainable. What’s more, cloud providers are competing, and may (assuming interoperability of some kind) reduce their costs, too.
Remember: Google gets 38% server utilization, with insane effort. So this is likely unattainable. What’s more, cloud providers are competing, and may (assuming interoperability of some kind) reduce their costs, too.
Remember: Google gets 38% server utilization, with insane effort. So this is likely unattainable. What’s more, cloud providers are competing, and may (assuming interoperability of some kind) reduce their costs, too.
Remember: Google gets 38% server utilization, with insane effort. So this is likely unattainable. What’s more, cloud providers are competing, and may (assuming interoperability of some kind) reduce their costs, too.
Remember: Google gets 38% server utilization, with insane effort. So this is likely unattainable. What’s more, cloud providers are competing, and may (assuming interoperability of some kind) reduce their costs, too.
Remember: Google gets 38% server utilization, with insane effort. So this is likely unattainable. What’s more, cloud providers are competing, and may (assuming interoperability of some kind) reduce their costs, too.
Just how big are clouds? Consider that in July 2008, Microsoft revealed that it had 96,000 servers at the Quincy facility, consuming "about 11 megawatts"
More than 80% dedicated to Microsoft's Live Search and the remaining for Hotmail
In August, a really good discovery was posted to a blog called "istartedsomething.com":  a screen shot of a software dashboard that illustrates power consumption and server count at each of Microsoft's fifteen data centers, caught in a Microsoft video posted to their web site.
First, consider silicon. Look at the cost/capacity tradeoff of computing, as described by Moore’s Law.
Then think about another form of sand – glass. Then look at the cost/capacity tradeoff of networking. Netflix pays $0.06 to send a movie over the Internet today, and will pay $0.03 next year.
Finally, think about iron. And consider storage – which is dropping just as quickly.
This trifecta of computing, bandwidth, and storage are driving costs down dramatically. Every time Google builds a data center, it can do more than the last one did.
Cloud computing is on a breakneck ride to zero marginal costs because of sand, iron, and glass. This means the raw materials of clouds will be free -- or too cheap to bill -- for many of us. (if you want to know more about this, see Chris Anderson’s Free)
Consider a San Antonio, Texas facility from Microsoft.
http://ccr.sigcomm.org/online/files/p68-v39n1o-greenberg.pdf
if the data center takes the full load of 44 megawatts at a 90% load factor, Microsoft pays an annual utility bill just north of $13 million, which translates to just over 3.8 cents/kwh as opposed to 5.7 cents/kwh for the ELP rate.  To prove that these assumptions are in the ballpark, public documents from another SLP customer in the San Antonio area reveal that its overall utility rate is 3.7 cents per kwh.
Energy is a huge issue. Even Gartner’s recommendations for saving energy will only temporarily solve the problem at hand, because energy costs will have to be cut by more than 50% in order to keep up
Like electrical utilities, clouds are elastic—one machine for a hundred minutes, or a hundred machines for a minute.
They’re available quickly in convenient billable increments. All you need is a credit card and a phone number.
Clouds let IT focus on things that actually add business value. Very few companies have a competitive advantage because of their hardware infrastructure.
And they eliminate many of the tasks you really didn’t want to do anyway.
In it, he draws an analogy between the rise of electrical utilities and that of cloud computing.
Most of the enterprises I’ve spoken with use clouds as peripherals. In the same way we used to plug peripherals into our computers, enterprises plug clouds into their IT. They might have it for backup, or messaging, or content delivery, or for a specific business process. But to really harness the power of cloud computing, enterprises need to embrace it as more than just a bunch of things to plug into the organization. It needs to become part of their strategy.
One of the most interesting uses of cloud computing is time dilation. Okay, not really, but close: The Washington Post, needed to get all 17,481 pages of Hillary Clinton’s White House schedule scanned and searchable quickly. Using 200 machines, the Post was able to get the data to reporters in only 26 hours. In fact, the experiment is even more compelling: Desktop OCR took about 30 minutes per page to properly scan, read, resize, and format each page – which means that it would have taken nearly a year, and cost $123 in power, to do the work on a single machine.
Moved from their own storage to Amazon's S3 cloud storage system. They now have one petabyte of images and sold their own storage hardware on eBay
Insurance firm Kennedys and Rowanmoor Pensions claims to be saving more than £350,000 a year.
According to Rowanmoor Pensions, a similar cloud computing model is saving the organisation about £200,000 a year.
Main savings from: Being able to decommission
By providing applications, storage and computing power online, cloud computing enables firms to buy IT services as and when required without incurring long-term hardware and software maintenance costs.
Other cost savings come from reduced hardware requirements, no capital expenditure on software, and lower power consumption.
Sydney-based Fresh Produce Group has increased its net profit margin by 100 percent in the first 18 months of its implementation of NetSuite ERP, helping the company save approximately $1 million per year.
NetSuite replaced multiple software systems including a DOS-based financial system, which was actively used by only a handful of accounting staff, and Excel spreadsheets which were used to compile forecasting and inventory.
It has helped identify and eliminate overhead expenses, which is saving approximately $1 million per year."
many of the FPG team work away from an office environment, the organization required an Internet-based, Software as a Service (SaaS) model for 'anytime and anywhere' access.
Seventy of FPG's 100 employees are licensed on the system and can now see the business end-to-end, in real-time and play their part in providing better decision making.
Computer-aided design company AutoDesk wanted to offer some of their desktop software applications as an online service. They didn't know the size of the market and didn't know if it would be a successful business considering the high infrastructure costs. They could test the market at a much lower cost with cloud computing resources.
Vivek Kundra, the first U.S. chief information officer, said the government has been building multiple data centers, so many that about a quarter of its $76 billion IT budget goes to infrastructure. He noted that the Department of Homeland Security has 23 data centers.
As a result, he said, federal energy consumption doubled from 2000 to 2006
He said a revamp of the Web site for the General Services Administration was completed in one day and the site now costs $800,000 a year, compared to six months and $2.5 million a year that would have been expected using the government's traditional approach. And, he said, with cooperation from the IRS, the government's Free Application for Federal Student Aid can now be prefilled with IRS data at the click of a button, eliminating more than 70 questions and 20 screens.
Speaking at a press event at NASA's Ames Research Center Tuesday, Kundra said that the government could save a lot of money by using many of the Web-based and cloud technologies that are already available to consumers. It costs the U.S. Transport Safety Administration (TSA) $600,000 to set up a blog, he said. By contrast, consumers can get a Blogger account free.
"If in our lives, we can go online and provision Webmail within a matter of minutes, why must the government spend billions and billions of dollars on information that may not be sensitive in nature?" he said.
Kundra is hoping that the cloud will provide a way to streamline the government's annual $75 billion IT spending by using cheaper commercial hosting services and by using virtualization technologies to load more applications onto its servers.
Following up on Tuesday's Apps.gov launch, the government will roll out a number of pilot projects in 2010, making lightweight applications available to users. By 2011, federal agencies will start getting guidance on how they are expected to move to the cloud.
Government market research firm Input has revised its forecast for federal cloud-related spending upward; it now expects the government's cloud expenditures to grow from $363 million this year to $1.2 billion by 2014. "I think this is probably a conservative estimate, considering the push from the administration," said Deniece Peterson, an analyst at Reston, Va.-based Input.
The virtual stock market NASDAQ wanted to offer their users a service to replay market data. Their infrastructure were not set up to build that, and they estimated that to build it using traditional methods, it would cost $6m to $8m. Using cloud computing infrastructure, they built it for only $100, Vogels said.
German publisher Bild.de wanted to launch a citizen journalism video service. Their own IT department said it would take 9-12 months, but using cloud computing, they were able to build and launch the service in four weeks.
Although its revenue has dipped to $27 million, Wellington-based IT services company Fronde has squeaked out a full-year profit - thanks to a series of deals based around Salesforce.com and Google’s SaaS products, and Amazon’s cloud computing platform. In the year-ago period, Fronde had higher revenue - $31 million - but made a $2.9 million loss. The company’s debt reduced from a year-ago $3.7 million to $300,000. Chief executive Ian Clarke told NBR earlier this week, “We’ve made a modest profit but a fabulous turnaround.” Part of the move out of the red came from old fashioned cost controls (headcount reduced from 200 to 170 over the year), reduced overheads and productivity gains.
Fronde has been in the business of cloud computing - and integrating cloud, and non-cloud apps - for several years. In 2009, it’s seen the technology move toward the mainstream. Other recent highlights include venture capitalist, NZTE advisor and Power-by-Proxi boss Greg Cross joining Fronde’s board during April, and a major Filipino m-commerce deal struck by its Fronde Anywhere subsidiary. An Amazon Elastic Compute Cloud (EC2) platform implementation has kept Fronde busy at one major account, and Mr Clarke sees a lot more business cloud computing coming up. Some projects expected to start have not. Some have started with reduced budgets.
In it, he draws an analogy between the rise of electrical utilities and that of cloud computing.
Jim Sivers reminded me recently of the paradox of choice. http://sivers.org/jam
Sheena Iyengar has been studying choice. For her research paper, “When Choice is Demotivating”,They set up a free tasting booth in a grocery store, with six different jams. 40% of the customers stopped to taste. 30% of those bought some.
A week later, they set up the same booth in the same store, but this time with twenty-four different jams. 60% of the customers stopped to taste. But only 3% bought some!
Both groups actually tasted an average of 1.5 jams. So the huge difference in buying can’t be blamed on the 24-jam customers being full. Lessons learned:
Having many choices seems appealing (40% vs 60% stopped to taste)
Having many choices makes them 10 times less likely to buy (30% vs 3% actually bought)
Surgeon Atul Gawande found that 65% of people surveyed said if they were to get cancer, they’d want to choose their own treatment. Among people surveyed who really do have cancer, only 12% of patients want to choose their own treatment.
Both groups actually tasted an average of 1.5 jams. So the huge difference in buying can’t be blamed on the 24-jam customers being full. Lessons learned:
Having many choices seems appealing (40% vs 60% stopped to taste)
Having many choices makes them 10 times less likely to buy (30% vs 3% actually bought)
Surgeon Atul Gawande found that 65% of people surveyed said if they were to get cancer, they’d want to choose their own treatment. Among people surveyed who really do have cancer, only 12% of patients want to choose their own treatment.
Both groups actually tasted an average of 1.5 jams. So the huge difference in buying can’t be blamed on the 24-jam customers being full. Lessons learned:
Having many choices seems appealing (40% vs 60% stopped to taste)
Having many choices makes them 10 times less likely to buy (30% vs 3% actually bought)
Surgeon Atul Gawande found that 65% of people surveyed said if they were to get cancer, they’d want to choose their own treatment. Among people surveyed who really do have cancer, only 12% of patients want to choose their own treatment.
Both groups actually tasted an average of 1.5 jams. So the huge difference in buying can’t be blamed on the 24-jam customers being full. Lessons learned:
Having many choices seems appealing (40% vs 60% stopped to taste)
Having many choices makes them 10 times less likely to buy (30% vs 3% actually bought)
Surgeon Atul Gawande found that 65% of people surveyed said if they were to get cancer, they’d want to choose their own treatment. Among people surveyed who really do have cancer, only 12% of patients want to choose their own treatment.
Both groups actually tasted an average of 1.5 jams. So the huge difference in buying can’t be blamed on the 24-jam customers being full. Lessons learned:
Having many choices seems appealing (40% vs 60% stopped to taste)
Having many choices makes them 10 times less likely to buy (30% vs 3% actually bought)
Surgeon Atul Gawande found that 65% of people surveyed said if they were to get cancer, they’d want to choose their own treatment. Among people surveyed who really do have cancer, only 12% of patients want to choose their own treatment.
Surgeon Atul Gawande found that 65% of people surveyed said if they were to get cancer, they’d want to choose their own treatment. Among people surveyed who really do have cancer, only 12% of patients want to choose their own treatment.
In it, he draws an analogy between the rise of electrical utilities and that of cloud computing.
There’s a basic equation in computing. Performance equals traffic divided by capacity. Put another way, more users and something gets slower. More machines and something gets faster.
This is an example of that relationship. As usage grows, performance gets worse.
Normally, IT adds capacity to a system and things get better.
But when if the capacity is infinite?
But when if the capacity is infinite?
But when if the capacity is infinite?
Then you set user experience (“under 1 second”) and the elastic platform adds capacity as needed. The only problem? The bill at the end of the month!
Joe Weinman (cloudonomics.com) should be required reading for some of this math.