Cloud 101


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Slides from the Cloud 101 workshop at Gov 2.0 in Washington, DC on May 25, 2010

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Cloud 101

  1. 1. Clouds 101 Understanding the state of cloud computing Wednesday, May 26, 2010
  2. 2. Wednesday, May 26, 2010 Cloud computing is an approach to computing that’s more flexible and lets organizations focus on their core business by insulating them from much of the underlying IT work.
  3. 3. Wednesday, May 26, 2010 At its most basic, it’s computing as a utility – pay for what you need, when you need it, rather than paying for it all up front.
  4. 4. Wednesday, May 26, 2010 This is what Nicolas Carr talked about in his book The Big Switch.
  5. 5. Wednesday, May 26, 2010 But clouds can be confusing. Part of the reason is that they’re a big deal, which means everyone wants to be a part of them – even companies who have nothing to do with clouds.
  6. 6. Wednesday, May 26, 2010 I’m going to try and clear some of this up for you.
  7. 7. Part one: Disruption and the democratization of IT Wednesday, May 26, 2010
  8. 8. Wednesday, May 26, 2010 First, let’s talk about disruption.
  9. 9. Wednesday, May 26, 2010 Once, IT was a monopoly.
  10. 10. Wednesday, May 26, 2010 Today, it’s a free market. The line of business has tremendous choice in what it owns, runs, and uses.
  11. 11. Wednesday, May 26, 2010 The boardroom loves this: instead of managing machines, they manage services.
  12. 12. Wednesday, May 26, 2010 But enterprise IT doesn’t like it much, because it forces them to compete, and puts them side-by-side with organizations that spend their entire day doing detailed usage and billing.
  13. 13. Wednesday, May 26, 2010 It’s not all bad, though. There’s a lot to be learned from a transition from monopoly to a free market.
  14. 14. Two reasons. Wednesday, May 26, 2010 There were a couple of reasons IT was a monopoly for so long.
  15. 15. (16MB) Wednesday, May 26, 2010 First, the machines were expensive. That meant they were a scarce resource, and someone had to control what we could do with them.
  16. 16. Wednesday, May 26, 2010 Second, they were complicated. It took a very strange sect of experts to understand them. AVIDAC, Argonne's first digital computer, began operation in January 1953. It was built by the Physics Division for $250,000. Pictured is pioneer Argonne computer scientist Jean F. Hall. AVIDAC stands for "Argonne Version of the Institute's Digital Automatic Computer" and was based on the IAS architecture developed by John von Neumann.
  17. 17. Wednesday, May 26, 2010 This was also a result of scarcity. When computers and humans interact, they need to meet each other halfway. But it takes a lot of computing power to make something that’s easy to use;
  18. 18. Wednesday, May 26, 2010 in the early days of computing, humans were cheap and machines weren’t
  19. 19. Wednesday, May 26, 2010 So we used punched cards,
  20. 20. Wednesday, May 26, 2010 and switches,
  21. 21. Wednesday, May 26, 2010 and esoteric programming languages like assembler.
  22. 22. Wednesday, May 26, 2010 Think about what a monopoly means.
  23. 23. Wednesday, May 26, 2010 A monopoly was once awarded for a big project beyond the scope of any one organization, but needed for the public good.
  24. 24. Wednesday, May 26, 2010 Sometimes, nobody wants the monopoly—like building the roads.
  25. 25. Wednesday, May 26, 2010 For the most part, governments have a monopoly on roadwork, because it’s something we need, but the benefits are hard to quantify or charge back for.
  26. 26. Wednesday, May 26, 2010 (IT’s been handed many of these thankless tasks over the years, and the business has never complained.)
  27. 27. Wednesday, May 26, 2010 The only time we can charge back for roads are when the resource is specific and billable: a toll highway, a bridge.
  28. 28. Wednesday, May 26, 2010 Sometimes, we form a company with a monopoly, or allow one to operate, in order to build something or allow an inventor to recoup investment. This is how we got the telephone system, or railways.
  29. 29. For much of its history, AT&T and its Bell System functioned as a legally sanctioned, regulated monopoly. The US accepted this principle, initially in a 1913 agreement known as the Kingsbury Commitment. Anti-trust suit filed in 1949 led in 1956 to a consent decree whereby AT&T agreed to restrict its activities to the regulated business of the national telephone system and government work. Changes in telecommunications led to a U.S. government antitrust suit in 1974. In 1982 when AT&T agreed to divest itself of the wholly owned Bell operating companies that provided local exchange service. In 1984 Bell was dead. In its place was a new AT&T and seven regional Bell operating companies (collectively, the RBOCs.) Wednesday, May 26, 2010 When monopolies are created with a specific purpose, that’s good. But when they start to stagnate and restrict competition, we break them apart.
  30. 30. Wednesday, May 26, 2010 In fact, there’s a lot of antitrust regulation that prevents companies from controlling too much of something because they can stifle innovation and charge whatever they want. That’s one of the things the DOJ does.
  31. 31. First: Monopoly good. Wednesday, May 26, 2010 In other words, early on monopolies are good because they let us undertake hugely beneficial, but largely unbillable, tasks.
  32. 32. Then: Monopoly bad. Wednesday, May 26, 2010 Later, however, they’re bad because they reduce the level of creativity and experimentation.
  33. 33. Wednesday, May 26, 2010 Today, computing is cheap. We can buy many times the compute power of the Apollo missions with a swipe of a credit card.
  34. 34. Wednesday, May 26, 2010 It’s also not complicated. Everyone can use a computer. Because today, the computer is cheap and the human’s expensive we spend so much time on user interfaces, from GUIs to augmented reality to touchscreens to voice control to geopresence.
  35. 35. Wednesday, May 26, 2010 What used to take a long time to procure, configure, and deploy is now a mouseclick.
  36. 36. Wednesday, May 26, 2010 The way data centers are designed must reflect this shift from IT-as-a-monopoly to IT-as-an-enabler
  37. 37. Wednesday, May 26, 2010 That means building a set of platforms that can adapt and adjust:
  38. 38. Wednesday, May 26, 2010 From rack-and-stack servers to click-and-drag deployment
  39. 39. Wednesday, May 26, 2010 From underused bare metal to on-demand virtual machines
  40. 40. Wednesday, May 26, 2010 From procurement and process to self-service and quick decommissioning.
  41. 41. Wednesday, May 26, 2010 The lesson of monopolies is an important one. When a monopoly set out to build a railroad, it didn’t spend a lot of time asking potential travelers what they wanted.
  42. 42. Wednesday, May 26, 2010 When you’re building something huge and expensive, you build what you want, and expect people to be grateful for it.
  43. 43. Wednesday, May 26, 2010 But today’s IT user is driving IT requirements.
  44. 44. Wednesday, May 26, 2010 They can shop around—choosing SaaS, clouds, and internal IT according to their business requirements.
  45. 45. Wednesday, May 26, 2010 They’re increasingly able to build the applications themselves, but expect IT to deliver smooth, fast platforms on which to experiment.
  46. 46. Wednesday, May 26, 2010 As the line of business looks more and more like a consumer in a competitive market—and less and less like a grateful customer of a monopoly—IT has to change its offerings.
  47. 47. USERS APPS PLATFORMS HARDWARE Wednesday, May 26, 2010 It’s an inversion of the traditional IT “pyramid”, where the hardware dictates the platforms, which in turn dictates, the apps, which dictates what users can do.
  48. 48. USERS APPS PLATFORMS HARDWARE Wednesday, May 26, 2010 Today, what users want to do drives the apps they use, which drives the platforms and the hardware.
  49. 49. Wednesday, May 26, 2010 We’ve had big changes since that time. The first was client-server computing: the idea that not everything lived in a mainframe, and some things worked well on the desktop. Software like Visicalc—the first spreadsheet—were useful for businesses, even those who couldn’t afford a mainframe.
  50. 50. Wednesday, May 26, 2010 A second big change was the Web. This browser-based model made computing accessible to the masses. As a result, it became part of society, and everyone knew how to work it. These days, you don’t have to teach a new hire how to use a web browser: they know what links do; what the back button is; and so on.
  51. 51. !"#$%%&&&'()*+,'*-.%#!-/-0%#)1234566)*/%789:;7<=>%? Wednesday, May 26, 2010 A third change is the move to mobility. This has been bigger overseas, where the mobile phone is the dominant way of accessing the Internet, but it’s still a shift to the always- connected, always-on lifestyles we lead today.
  52. 52. Wednesday, May 26, 2010 And now there’s cloud computing. Clouds are as big a shift as client-server, or the web browser, or mobility.
  53. 53. Part two: A history of virtualization. Wednesday, May 26, 2010
  54. 54. Wednesday, May 26, 2010 The  step-­‐func-on  nature  of  dedicated  machines  doesn’t  distribute  workload  very  efficiently.
  55. 55. Wednesday, May 26, 2010 Virtualization lets us put many workloads on a single machine
  56. 56. Wednesday, May 26, 2010 Once  workloads  are  virtualized,  several  things  happen.  First,  they’re  portable
  57. 57. Wednesday, May 26, 2010 Second,  they’re  ephemeral.  That  is,  they’re  short-­‐lived:  Once  people  realize  that  they  don’t  have  to  hoard  machines,  they  spin  them  up  and  down  a  lot   more.
  58. 58. Wednesday, May 26, 2010 Which  inevitably  leads  to  automa3on  and  scrip3ng:  We  need  to  spin  up  and  down  machines,  and  move  them  from  place  to  place.  This  is  hard,  error-­‐prone  work  for  humans,  but   perfect  for  automa3on  now  that  rack-­‐and-­‐stack  has  been  replaced  by  point-­‐and-­‐click
  59. 59. Wednesday, May 26, 2010 Automa-on,  once  in  place,  can  have  a  front  end  put  on  it.  That  leads  to  self  service.
  60. 60. “Cloudy”  tech. Wednesday, May 26, 2010 These  are  the  founda-ons  on  which  new  IT  is  being  built.  Taken  together,  they’re  a  big  part  of  the  movement  towards  cloud  compu-ng,  whether  that’s  in   house  or  on-­‐demand.
  61. 61. Virtualization divorces the app from the machine. One on many (or) Many on one Physical machine Virtual machine Virtual Virtual Virtual Physical Physical Physical machine machine machine machine machine machine Virtual Virtual Virtual Physical Physical Physical machine machine machine machine machine machine Wednesday, May 26, 2010 Okay, so these things mean we have applications that run “virtually” – that is, they’re divorced from the underlying hardware. One machine can do ten things; ten machines can do one thing.
  62. 62. That’s the technical definition Virtualization Automation Self-service Elasticity Usage tracking & billing Service-oriented article Wednesday, May 26, 2010 This is the “technical” definition of cloud computing: virtualized, automated, self-service computing resources. Some people call this a “private cloud”; others think it’s just IT-done- right. Whatever the case, data centers are furiously retooling themselves, much to the enjoyment of companies like VMWare and Citrix.
  63. 63. Part three: Stacks and the separation of concerns. Wednesday, May 26, 2010 Part three: Stacks and the separation of concerns
  64. 64. Wednesday, May 26, 2010 At its most simple, this is all about a “stack” of services. Stacks are a common idea in computing and networking. Basically, they’re a separation of different tasks.
  65. 65. Wednesday, May 26, 2010 We’re familiar with the idea of a stack. There’s a stack in the postal service.
  66. 66. Your virtual platform Layer of separation Their physical infrastructure Wednesday, May 26, 2010 You worry about the address, and the stamp. The postal service handles the rest—it doesn’t care what’s inside your envelope; and you don’t care what route your letter takes to its destination, as long as it gets there.
  67. 67. Part four: Clouds as a business model. Wednesday, May 26, 2010
  68. 68. Wednesday, May 26, 2010 But wait -- there’s more! There’s another way to look at cloud computing.
  69. 69. This has all been DIY. Wednesday, May 26, 2010 Notice that so far, nothing I’ve said about clouds implies you can’t just run your own. Up until now, they’ve been DIY.
  70. 70. Clouds are a business model. Wednesday, May 26, 2010 This is the clouds-as-a-business-model definition. In this, cloud computing is a third-party service.
  71. 71. Wednesday, May 26, 2010 All of the things we’ve seen about cloud technology make it possible to deliver computing as a utility -- computing on tap. The virtualization provides a blood/brain barrier between the application the user is running, and the machines on which it runs.
  72. 72. Wednesday, May 26, 2010 That means you can focus on the thing your business does that makes you special
  73. 73. Wednesday, May 26, 2010 And stop worrying about many of the tasks you really didn’t want to do anyway.
  74. 74. Wednesday, May 26, 2010 Sharing and economies of scale keep costs down. Cloud providers are poised to make the most of these economies of scale. 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 "":  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.
  75. 75. Idle capacity, lack of automation, etc. IT server costs Ping, power, pipe, Private efficiencies cloud costs Public cloud costs Wednesday, May 26, 2010 The move towards the cloud business model has a lot to do with the economies of scale that exist when you can concentrate infrastructure, and put it near dams. (There’s a good—if hotly debated argument—that clouds-as-a-business-model are inevitable, because of the economics.)
  76. 76. Wednesday, May 26, 2010 Cloud providers are thinking at a scale that nearly every enterprise can’t compete with. That’s because operating efficiency, and accounting for everything, are core to their business; whereas making widgets is core to yours.
  77. 77. Wednesday, May 26, 2010 Self-service means customers can deploy and destroy their own machines.
  78. 78. Dedicated On-premise Virtual Third-party hardware private clouds private clouds public clouds Wednesday, May 26, 2010 So while you can build an automated, self-service, on-demand private cloud, there are also many public options (is that a bad word in DC? )
  79. 79. Wednesday, May 26, 2010 Most of the time, when you hear someone say they’re concerned about the security of cloud computing, they’re talking about public clouds, and the issues that come with putting your data somewhere virtually but not knowing where it is physically.
  80. 80. Part five: Kinds of clouds. Wednesday, May 26, 2010
  81. 81. Wednesday, May 26, 2010 So far, while I’ve told you a lot about clouds, I haven’t really told you what they are. That’s partly because there are many kinds of cloud computing. We can separate clouds into three distinct groups.
  82. 82. Infrastructure as a Service Amazon EC2, Rackspace Cloud, Terremark, Gogrid, Joyent (and nearly every private cloud built on Zenserver or VMWare.) Wednesday, May 26, 2010 The first is called Infrastructure as a Service, because you’re renting pieces of (virtual) infrastructure.
  83. 83. Wednesday, May 26, 2010 This is what IT people think of when you say “clouds” – virtual machines I can use for just an hour. Here’s Amazon’s “menu” of machines.
  84. 84. • 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 Wednesday, May 26, 2010 A great example of these clouds in action is what the Washington Post did with Hillarly Clinton’s diaries during her campaign. They 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.
  85. 85. Machine Web Image server Machine instance Wednesday, May 26, 2010 In an IaaS model, you’re getting computers as a utility. The unit of the transaction is a virtual machine. It’s still up to you to install an operating system, and software, or at least to choose it from a list. You don’t really have a machine -- you have an image of one, and when you stop the machine, it vanishes.
  86. 86. DB Machine Storage server Image Machine instance App Machine Server Image Machine instance Web Machine server Image Machine instance Wednesday, May 26, 2010 Most applications consist of several machines -- web, app, and database, for example. Each is created from an image, and some, like databases, may use other services from the cloud to store and retrieve data from a disk
  87. 87. DB Storage server Machine instance Bigger App machine instance Server Machine instance Web server Machine instance Wednesday, May 26, 2010 If you run out of capacity, you can upgrade to a bigger machine (which is called “scaling vertically.”)
  88. 88. DB Storage server Machine instance App Server Machine instance Web server Machine instance Load balancer Machine instance Wednesday, May 26, 2010 Or you can create several machines at each tier, and use a load balancer to share traffic between them. These kinds of scalable, redundant architectures are common -- nay, recommended -- in a cloud computing world where everything is uncertain.
  89. 89. Platform as a Service Google App Engine, Salesforce, Rackspace Cloud Sites, Joyent Smart Platform, (and nearly every enterprise mainframe.) Wednesday, May 26, 2010 The second kind of cloud is called Platform as a Service. In this model, you don’t think about the individual machines—instead, you just copy your code to a cloud, and run it. You never see the machines. In a PaaS cloud, things are very different.
  90. 90. Shared components Data Processing platform Storage API Others’ Others’ code code User Auth database API Your Others’ code code Image Image functions API Others’ Others’ code code ... Big Blob Governor Console Schedule objects API Wednesday, May 26, 2010 - You write your code; often it needs some customization. - That code runs on a share processing platform - Along with other people’s code - The code calls certain functions to do things like authenticate a user, handle a payment, store an object, or move something to a CDN - To keep everything running smoothly (and bill you) the platform has a scheduler (figuring out what to do next) and a governor (ensuring one program doesn’t use up all the resources) as well as a console.
  91. 91. Wednesday, May 26, 2010 Here’s a shot of some code running in Google App Engine. I only know that I’m paying by CPU-hour, or for units like bandwidth, email, or storage. This could be one machine whose CPU was used 8%, or a hundred, or a thousand. I don’t know.
  92. 92. Wednesday, May 26, 2010 I can see the logs for my application. But these aren’t for a single machine -- they’re for the application itself, everywhere.
  93. 93. Wednesday, May 26, 2010 I can even find out what parts of my code are consuming the most CPU, across all machines.
  94. 94. Wednesday, May 26, 2010 And even their latency when served to people.
  95. 95. Wednesday, May 26, 2010 It’s a true, pure utility because you pay for what you use.
  96. 96. Wednesday, May 26, 2010 This is a very different model from IaaS. On the one hand, it’s more liberating, because you don’t have to worry about managing the machines. On the other hand, it’s more restrictive, because you can only do what the PaaS lets you.
  97. 97. IaaS and PaaS differences IaaS PaaS Any operating system you Use only selected want languages and built-in APIs Limited by capacity of Limited by governors to virtual machine avoid overloading Scale by adding more Scaling is automatic machines Use built-in storage Many storage options (file (Bigtable, etc.) system, object, key-value) Wednesday, May 26, 2010 In the case of Google’s App Engine, you have to use their functions and store things in the way they want you to. You get great performance from doing so, but it probably means rewriting your code a bit.
  98. 98. Quota Limit Governor Apps per developer 10 (usage cap) Time per request 30s Blobstore (total file size) 1GB Maximum HTTP response size 10MB Datastore item size 1MB Application code size 150MB Daily cap Emails per day 1,500 (free quota) Bandwidth in per day 1 GB Bandwidth out per day 1GB CPU time per day 6.5h HTTP requests per day 1,300,000 Datastore API calls per day 10,000,000 URLFetch API calls per day 657,084 Wednesday, May 26, 2010 PaaS platforms impose usage caps and billing tiers. Here’s Google App Engine’s set of quotas and free caps.
  99. 99. Wednesday, May 26, 2010 In the case of Salesforce’s, you have to use an entirely new programming language, called Apex.
  100. 100. Wednesday, May 26, 2010 The third kind of cloud is called Software as a Service, or SaaS. Some people argue that this isn’t a cloud at all, just a new way of delivering software. But it’s also what the masses—the non-technologists—think cloud computing means.
  101. 101. My mom’s definition Cloud = Web = Internet = Useless Wednesday, May 26, 2010 (Personally, I think this makes the term “cloud” synonymous with “web” or “Internet”, and therefore a bit useless.)
  102. 102. Wednesday, May 26, 2010 SaaS and PaaS are blurring, too, with the advent of scripting languages. Nobody would argue that Google Apps is a SaaS offering; but now that you can write code for it -- as in this example of a script that sends custom driving directions to everyone in a spreadsheet -- the distinction is less and less clear.
  103. 103. Wednesday, May 26, 2010 But the business model of SaaS is the same as PaaS and IaaS: Sell IT on demand, rather than as software or machines.
  104. 104. Wednesday, May 26, 2010 It’s the form of cloud computing that gets the most lip service in areas like government, particularly with Google Apps.
  105. 105. Part six: It’s all a blend, really. Wednesday, May 26, 2010
  106. 106. Service What it does Elastic Compute Cloud Virtual machines, by the hour Elastic Mapreduce Massively parallel data processing Virtual Private Cloud On demand machines within internal IT Elastic Load Balancing Traffic distribution Cloudfront Content delivery acceleration Flexible Payments Service Funds transfer & payments SimpleDB Realtime structured data queries Simple Storage Service Eleven nines redundant storage Relational Database Service On-demand RDBMS Elastic Block Store Block-level storage (file system) Fulfillment Web Service Merchant delivery system Simple Queue Service On-demand message bus Simple Notification Service System for sending mass notifications Cloudwatch Monitoring of cloud resources Mechanical turk Humans as an API Wednesday, May 26, 2010 This division between PaaS and IaaS is a bit of a fiction. In fact, virtual machines are just one of around twenty “cloud services” Amazon offers – called EC2.
  107. 107. Service What it does App Engine Executing Python or Java code Bigtable datastore Store data for very fast retrieval Calendar Data API Create and modify events Inbox feed API Read a GMail inbox Contact data API Interact with someone’s GMail contacts Documents list API Manage a user’s Google Docs OpenID single signon Use Google authentication to sign in Secure data connector Link Google Apps to enterprise apps Memcache Fast front-end for data Image manipulation Resize, rotate, crop & flip images Task queue Queue and dispatch tasks to code Blobstore Serve large objects to visitors Wednesday, May 26, 2010 The same is true of App Engine - though these are functions called from code, rather than services you pay for separately, they’re still more than just the code.
  108. 108. Clouds aren’t just virtual machines. Wednesday, May 26, 2010 This is a really important concept: Clouds aren’t just virtual machines. Clouds are on-demand computing services.
  109. 109. Wednesday, May 26, 2010 To understand this, we need to talk for a minute about “composed designs.”
  110. 110. Query language Let’s just call this a database, Software ‘mmkay? Operating system Computer hardware Storage media Wednesday, May 26, 2010 When IT architects want to build something, they have a set of proven designs for doing so. A database is an example of this—it’s a combination of storage (disk) and a particular way of arranging things (tables and indexes) and language (structured query language, or SQL). We’ve learned that a database is a good prefab building block, so we use it. The alternative is to build it all, from scratch, writing to the disk itself.
  111. 111. Wednesday, May 26, 2010 There are other examples of “composed designs” in IT, many of them made from several components. For instance, consider the “message bus.” This is a thing you put messages into, and anyone who wants them can grab a copy of the message. Stock exchanges use publish-and-subscribe message busses to move data around.
  112. 112. Wednesday, May 26, 2010 A third example is called a key-value data store. In this case, I put in a key (say, ”username”) and a value (say, “Palin”). Then it’s stored for me. It’s much less fancy than a database, but also much faster and more scalable, and can be backed up more easily so it’s more reliable.
  113. 113. Wednesday, May 26, 2010 When architects want to build an application today, they don’t do so by building everything from scratch. Today’s applications are built on the shoulders of giants—message busses, data stores, authentication systems, payment tools, content delivery networks, and so on.
  114. 114. Wednesday, May 26, 2010 As a result, cloud providers offer a variety of these services. Rackspace has a storage product called Jungledisk; Amazon has S3. The machines that Rackspace or Amazon offer “chew” on data from these storage services.
  115. 115. Wednesday, May 26, 2010 If you equate cloud computing with just virtual machines, you’re missing the real point. Clouds applications are built from composed designs, and one of the components happens to be virtual machines.
  116. 116. Private Public nt t o SaaS a w d s, o u lo u y c If l k PaaS rs t.PaaS t a ne f i i ck o IaaS p IaaS Managed Virtualization hosting Wednesday, May 26, 2010 So let’s put this in perspective: There are public and private cloud models. Private ones are about the technology; public ones are about the business of outsourcing at scale. And there are Infrastructure, Platform, and Software offerings—IaaS, PaaS, and SaaS. 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.
  117. 117. Private Public SaaS Lock-in concerns Long-term PaaS cost Security fears inefficiencies High cost of maintaining & scaling machines IaaS Wednesday, May 26, 2010 Just knowing these two dimensions makes you smarter than nearly everyone in IT right now. And when you’re discussing IT, insist that others are specific about what they mean. Discussions around privacy and security are vital to public clouds, but most people don’t consider security different in private clouds. Similarly, lock-in is a real concern in PaaS but negligible in IaaS.
  118. 118. Part seven: The ecosystem Wednesday, May 26, 2010
  119. 119. Wednesday, May 26, 2010 Lots of people want to move into this space. Some are e-commerce giants (like Amazon) who know how to run many machines well.
  120. 120. Wednesday, May 26, 2010 Some are software companies with legions of developers (like Microsoft) who want to move from software licenses to recurring revenues.
  121. 121. Wednesday, May 26, 2010 Some are managed hosting companies (like Rackspace, Terremark, and Gogrid) who want to sell computing by the hour instead of by the month, and want to have more standardized offerings.
  122. 122. Wednesday, May 26, 2010 Some are giant service companies (like Google) who want people to create millions of applications and keep people using the Web.
  123. 123. Wednesday, May 26, 2010 Some are big systems integrators (like IBM) who want to design and run IT for enterprises.
  124. 124. Wednesday, May 26, 2010 Some are hardware vendors (like Dell) who want to stay in the computing business as it shifts.
  125. 125. Wednesday, May 26, 2010 Some are telecom providers (like AT&T and Verizon) who want to do more than move packets around, and want to make the best use of their existing data centers.
  126. 126. Wednesday, May 26, 2010 Some are even government organizations aiming to build infrastructure for the use of the government itself
  127. 127. Wednesday, May 26, 2010 This isn’t a comfy place to be right now. Cloud computing has what I call a “roofrack” problem.
  128. 128. Wednesday, May 26, 2010
  129. 129. Wednesday, May 26, 2010
  130. 130. Part eight: So what do I do now? Wednesday, May 26, 2010
  131. 131. Wednesday, May 26, 2010 Cloud computing isn’t something you can easily ignore.
  132. 132. Wednesday, May 26, 2010 For some applications, particularly those that are bursty or seasonal, the economics are overwhelmingly in its favor.
  133. 133. '#!/)01#$!"2#34+,#$' <; @< @; !"##"$%&'()$*+'*&'((%&+ ?< ?; >< >; =< =; < ; >@ABA >DABA >CABA ?;ABA =ACA ?ACA <ACA DACA CACA ==ACA =?ACA =<ACA =DACA >;;C >;;C >;;C >;;C >;;C >;;C >;;C >;;C >;;C >;;C >;;C >;;C >;;C Connect times to Amazon Cloudfront from NYC 5%''%,!6%%,($7!0$48#,!9%''%,!,#3'($7: Cloud Encounters, Peter van Eijk, Wednesday, May 26, 2010 ! Cloud providers keep making their stuff better. Amazon introduced roughly 40 new features last year; and in a single month they upgraded their network in New York twice.
  134. 134. Wednesday, May 26, 2010 And clouds make organizations more agile, because they take procurement from weeks to minutes.
  135. 135. Expense  reports  can  no   longer  enforce  IT  policy. Wiley  GAAP  2010:  Interpreta3on  and  Applica3on  of  Generally  Accepted  Accoun3ng  Principles  (By  Barry   J.  Epstein,  Ralph  Nach,  Steven  M.  Bragg) Wednesday, May 26, 2010 They also remove the false sense of security that came from expense limits.
  136. 136. Airfare DNS Cloud Public transit Important research Hotel Wednesday, May 26, 2010 These  days,  supercompu-ng  is  easier  (and  cheaper)  than  booking  a  flight.
  137. 137. We stop worrying about ROI when I is zero. Wednesday, May 26, 2010 Because there’s no investment, the concept of an ROI doesn’t really make sense.
  138. 138. Wednesday, May 26, 2010 Even if you’re only going to run a private cloud, you’re dealing with expectations set by the public Internet. Consider an ATM – once, we didn’t mind taking all of lunch to get money out; today, we worry when the bank machine fails to give us our money back in 10 minutes. That’s a bad thing for organizations that don’t handle IT automatically; humans simply can’t move that fast. Efficiency isn’t about how fast you do things; it’s about how many things you don’t have to do because they’re automated.
  139. 139. Wednesday, May 26, 2010 The Internet has a way of routing around obstacles, so if you try to block people from using them, you’ll likely send your stakeholders underground.
  140. 140. Wednesday, May 26, 2010 The best thing to do is offer people an alternative. Set up self-service computing internally and see what happens.
  141. 141. Single Storage sign on Image processing Mailing service Virtual machine Key/value Virtual store load balancer Parallel framework Wednesday, May 26, 2010 It also means surrounding them with composed services like storage and message queues. Fortunately, there is a wide variety of offerings to help with this. Hadoop, Cassandra, CouchDB, Hypertable and others are all tools that handle storage, scaling, and parallel tasks, and that you can deploy internally for your users.
  142. 142. Wednesday, May 26, 2010 It also means setting up platforms (such as a web server that can handle PHP code, or a Drupal platform for creating social sites, or a instance for microblogging,
  143. 143. Wednesday, May 26, 2010 or a Wordpress instance for blogs.)
  144. 144. Wednesday, May 26, 2010 Finally, it means working with SaaS providers when appropriate, but integrating their applications with your internal data and processes
  145. 145. Wednesday, May 26, 2010 For IT, and governments, cloud computing is a trigger. It means it’s time to rebalance your computing decisions.
  146. 146. Wednesday, May 26, 2010 With clouds, there’s a spectrum of IT options. Different applications live in different places in this new world.
  147. 147. Data centers Contracts Developers <script> Hello, world! </script> Mashup, Bare Virtualization Public/private IaaS PaaS RESTful metal hybrid models services Wednesday, May 26, 2010 Different applications live in different places in this new world.
  148. 148. Wednesday, May 26, 2010 Here’s a five-step plan for embracing clouds.
  149. 149. Wednesday, May 26, 2010 First, you need to assess your existing applications. Make a list of everything you’ve got, or plan to have. You should also baseline usage, performance, and other “before” metrics so you can compare them to the results of your efforts after you’ve moved.
  150. 150. Wednesday, May 26, 2010 Then, you need to rebalance your applications. Evaluate each application along two dimensions: how suitable is the application for migration, and what’s the payoff.
  151. 151. Wednesday, May 26, 2010 Some applications, like legacy ERPs or old mainframe tools, won’t migrate easily. They’re not well suited to a virtualized, on-demand model where users can spin up resources as needed.
  152. 152. Wednesday, May 26, 2010 Others, like web front-ends or parallel data processing tasks like analytics, that can be split up, work really well in clouds.
  153. 153. Some things aren’t worth moving. Wednesday, May 26, 2010 At the same time, some applications won’t benefit much from a cloud model. Something that runs constantly may be more affordable to run in-house.
  154. 154. Wednesday, May 26, 2010 Other applications may have a massive budget savings when they move to the cloud. Something that happens once a year but needs tremendous computing for the three days it runs is a candidate for clouds. So, too, is something that users are constantly requesting, and that your IT team spends a lot of time managing. Automate it!
  155. 155. Compute task (service cloud) Virtual machine (infrastructure cloud) Always on Can be done Always in premise anywhere cloud Load/pricing engine Private Partner access Compliance- Testing enforced Proximity to cloud Training services (storage, Policy engine Need to track and Prototyping CDN, etc.) audit Batch processing Massively grid/ Legislative Seasonal load parallel (genomic, Data near local modelling) computation Wednesday, May 26, 2010 Going forward, we’ll see hybrid on-premise/on demand hybrid clouds that can intelligently move processing tasks between private an public infrastructure according to performance requirements, pricing policies, and security restrictions.
  156. 156. Wednesday, May 26, 2010 Third step: You have to migrate things to the new environments. This means moving stuff around—hopefully the high-payoff, easy-to-move stuff first. There’s no magic here: you’ll need to make your applications portable, which means virtualizing them; and you may need to modify some code.
  157. 157. Wednesday, May 26, 2010 Step four is to optimize things. In their new homes, some applications won’t perform as well. You’ll need to compare how they’re doing now to how they were doing before, and tweak things to ensure equivalent performance, uptime, security, and scalability.
  158. 158. Wednesday, May 26, 2010 Finally, in step five you need to operate things differently. Cloud computing is as much about a cultural shift in IT: you’re operating a self-service business.
  159. 159. Wednesday, May 26, 2010 You’re not doing the IT work any more; you’re managing the scripts and systems that let users do the IT work themselves. You have a very different relationship with your end users.
  160. 160. Wednesday, May 26, 2010 You’re providing the environment for them to innovate, giving them turnkey sets of services with which to work. Where they come from is immaterial.
  161. 161. Wednesday, May 26, 2010 You’re ensuring that the systems you’ve built are functioning properly however end users want to use them, rather than running the applications or data within those systems.
  162. 162. Wednesday, May 26, 2010 Your end users aren’t necessarily technical -- they’re able to build applications easily, and want the tools to experiment.
  163. 163. Wednesday, May 26, 2010 At the same time, you’re seeing what tools and processes are getting adopted -- what’s working? what’s popular? -- and doubling down on those things.
  164. 164. Wednesday, May 26, 2010 You’re giving your users places to experiment.
  165. 165. Wednesday, May 26, 2010 To some extent, you’re “paving the cowpaths.”
  166. 166. Wednesday, May 26, 2010 This is an old civil engineering trick: Watch where people walk, then put paths there.
  167. 167. Part nine: Conclusions. Wednesday, May 26, 2010
  168. 168. Massive disruption on the horizon Clouds are extremely disruptive to the way IT works Wednesday, May 26, 2010
  169. 169. Virtualization let the genie out of the bottle Clouds arose from virtualization, which made application workloads portable Wednesday, May 26, 2010
  170. 170. Clouds start with separation Separation is key Determines economics, lock-in, responsibility, risk Wednesday, May 26, 2010 One of the fundamentals of a cloud is the separation of the provider from the user at some layer in the stack Where that separation happens determines economics, responsibilities, risk, and lock-in
  171. 171. Business vs. technology Know the difference Clouds-as-tech: Virtualized, automated Clouds-as-business: 3rd party, shared Force others to be clear Wednesday, May 26, 2010
  172. 172. Two main divisions IaaS/PaaS/SaaS Public/Private Wednesday, May 26, 2010
  173. 173. One size does not fit all Ultimately, the blend of these different models will vary from organization to organization Wednesday, May 26, 2010
  174. 174. Five steps to cloud migration Assess Balance Migrate Optimize Operate Wednesday, May 26, 2010
  175. 175. Ecosystem is in flux The ecosystem is competitive and confusing right now, with few standards and a lot of noise Wednesday, May 26, 2010
  176. 176. Wednesday, May 26, 2010 It will probably wind up looking like airlines.
  177. 177. StateOfCloudComputingReport-FINALv3_508.pdf Wednesday, May 26, 2010 It will probably wind up looking like airlines.
  178. 178. The big picture Representation is a hack Wednesday, May 26, 2010 It will probably wind up looking like airlines.
  179. 179. Thanks! @acroll Wednesday, May 26, 2010