Introduction to Cloud Computing

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Introduction to Cloud Computing Course Module by David S Platt Harvard University Extension School Lectured by Nilanjan Banerjee 

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In the Beginning was the Mainframe and Terminals Users did individual work by connecting to central computer 

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Next came PCs ا سكسس Users did individual work on their own desktops 

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Then the PCs Got Tied Together Users could talk to each other’s PCs 

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Then came the Web Users did individual work by connecting to web servers 

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Then the Web got big Server had to become cluster of PCs 

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Then the Web got REALLY big, and really important Server PCs had to live in expensive data center Microsoft Data Center in Dublin, 27,000 m?, 22 MW, US$ 500. M 

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Data Centers Need lots of electric power (1.5% of all US electricity, EPA 2007) Long lead time to build Inflexible investment of capital Need specialized skills (security, failover, load balancing, etc.) Takes time away from core competencies Hard for all but largest companies to own/run ۰ ۰ ۰ 

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Solution: Outsource Data Center Can reap economies of scale Because of scale, can afford specialized skills Web developers can concentrate on their core competencies that give them market advantage Shorter lead times Lower capital requirements Computing power becomes a commodity, as did electric power in early 20" century 

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Similar to Electrification in Early 20% Century 0 Te اهام أه 96 Crete ترس Pe a See The Big Switch: Rewiring the World, from Edison to Google , by Nicholas Carr, Norton, 2008, from which this chart is taken 

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Types of Clouds You manage co oo sopuan 6۵ pabeuew = 35 8 a oa 2 a 3 35 < 3 8 a 95 Jopuan Aq pabeuew You manage 

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Current Cloud Platforms 

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Amazon Web Services Launched in 2002 Run by Amazon.com Programmed in many languages, including Java, Python, Ruby, and .NET Evolved from basic computing to add commerce-based services, such as payment and fulfillment 

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Google App Engine inl Po مج سر ۳۰۸ 0 ون ۳ | = 7 مد 3 اک ۲۱5۵۸۸ مه ۱ ۲ خماسه ها Google code seen ‘Google App Engine Home Oucs FAG Aces flog Garmumty Tams Downing Run your web apps on Google's Getting Started infrastructure, + Signup for an App Enso account 4 Easy to BUT, easy to maintain, eaty to sole 2 Dania App Enns SOK ۳ | engl App Engi orale yoo bu anche ws ans on be Sane syst al Watch and Learn ower Goole ppctons. App Engine afer fr segment and captor Deven and dep Ss sista, an ro nebo wary adi Nrowere, Peles Raha: a ow cosas AE Sfforfss scab, Discowrwhy dewlepos are choosing Abe Engi ow <> Google App Engine for Business "" 12022 ‏بز‎ 172 errr 0 consoles you roy ‏وه ۱ اه‎ ۱ 

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Google App Engine * Released in 2008 ۰ Primary languages are Python and Java * Currently provides basic computing and storage; a few more simple things. Can’t imagine that won’t increase and evolve. 

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Microsoft Azure ee ETE oo Windows Azure Platform emer aes Prods Resources ase Stes Purdase Developers Parnas Ssaing out an trastsctne tat Suppers your wed service applatin can be expensive, ‏لعاف ام‎ and time concuning Fercacting the highest possible demand. Bling ot the ‘network fo suport yout peo ites. Getting the ight servers in slace a height ine, ‘naragig and matting 06 Customer Quotes ‘+ you could ack tthe Mics cloud. The Windows Azure platform sa exe dowd ‏وا مه مه مرکا مه عم ورس‎ eens prablens and addressing ۳ on expensive nestrcr, Po oly or what Yu nn ‘se scale up when you neo capac aa ple back when yeu do We hance all he 0 a sca enone with ‏انه‎ 90906 0008 cucu ead wore = sn Scene ‏ی سا‎ whdane ere pao tet cet me nid ‏تست‎ ‎> mean star: youl ie etl Me oe ig ‏یاوه‎ orang ‏ومس‎ ‎er ‘iste 1 ‏و‎ 

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Microsoft Azure Launched in 2009 Program in .NET Provides computation and storage services Allows access to underlying cloud system (“fabric”) for sophisticated tweaking | expect to see additional business services as well, perhaps provided by third parties 

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Workload Patterns Optimal For Cloud 

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On and Off On &off workloads (e.g. batch job) Example: scientists running modeling software for new drug Installed capacity is wasted when not being used, but: Users twiddle thumbs expensively while waiting for jobs to finish 

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Growing Fast ب ب ب ب ب ع سسسسسكح Successful services need to grow and scale Example: new Internet game that catches on Deployment and scaling lags can stunt growth at key critical moment. See “Pogue effect” on Line2 iPhone app Need capital for software development or marketing instead of building data center 

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Predictable Bursting Many services have seasonality trends, either macro (FTD Florists and Valentine’s Day) or micro (Domino’s Pizza on Super Bowl Sunday), or any restaurant at peak meal hours. Installed capacity is wasted when not being used, but lack of sufficient capacity at key moment could kill 

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Unpredictable Bursting Unexpected/unplanned peak in demand Extreme example: CNN.com on 9/11/01 Less extreme example: Weather.com as a big storm moves in Can’t afford to provision for extreme case, but failure to handle it well can kill a brand Take care: if you depend on handling bursts for your company’s life, be very careful about service level agreement 

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Potential Snags or Platt’s Second Law: The Amount of Crap in the Universe is Conserved 

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What If Cloud Dies ? The cloud probably has better availability than you could do on your own. However: Consider retaining as much in-house capacity as you need to stay alive and muddle through Example: hospital or police department, which get electricity from grid for normal operations but keep backup generator for vital functions in case of outage. 

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Ultra-Sensitive Data * Some core, vital data you just can’t trust to anyone else. Example: Fidelity account contents, US Department of Defense submarine locations. Can't use external cloud, but might consider internal cloud appliances, with safeguards. + These companies often have much larger stores of data with lower security requirements for which cloud could be highly appropriate. Example: Fidelity fund prospecti and reports, US DoD purchases of coffee and underwear. 

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Legal * Sometimes law requires that certain data be stored in specific countries or locations (EU). ٠ Sometimes you want data stored in specific locations to avoid any possible uncertainties in jurisdiction (MS HealthVault in Canada). * Technology changing faster than law can keep up. More than a little bit tricky. Cloud could hurt (hosting not available in required jurisdiction) or help (quick switch of hosting into newly required jurisdiction). 

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Availability of Cloud Resources How sure are you that your cloud provider will have enough cloud resources available when you want to scale up, particularly in burst situations? How badly would it hurt your business if you wanted to scale up but couldn’t? What remedies are available from cloud provider if you cannot scale at the time you want, to the degree that you want? (See service level agreement with provider.) Amazon has interesting spot market for computational resources. 

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Demo Hello, Cloud Application