[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"cheat-sheet---en":3,"domain-info---en":3,"topic-info----en":3,"prev-cloud-computing-fundamentals-cloud-concepts-and-economics-cloud-computing-basics-why-cloud-computing-exists-en":3,"next-cloud-computing-fundamentals-cloud-concepts-and-economics-cloud-computing-basics-why-cloud-computing-exists-en":4,"lesson-cloud-computing-fundamentals-cloud-concepts-and-economics-cloud-computing-basics-why-cloud-computing-exists-en":171},null,{"locked":5,"reason":3,"meta":6,"item":16},false,{"title":7,"description":8,"isFree":5,"estimatedMinutes":9,"difficulty":10,"learningObjectives":11},"What Is Cloud Computing?","The official NIST definition of cloud computing, unpacked phrase by phrase, and the test it gives you for telling a real cloud service apart from a data center someone just calls one.",14,"beginner",[12,13,14,15],"State the NIST definition of cloud computing","Explain what each phrase in the definition actually requires of a real cloud service","List the 5 essential characteristics, 3 service models, and 4 deployment models the definition names","Identify when a hosted server does not qualify as cloud computing",{"id":17,"title":7,"body":18,"description":8,"difficulty":10,"estimatedMinutes":9,"extension":118,"infographics":119,"isFree":5,"learningObjectives":120,"meta":121,"navigation":122,"path":123,"quiz":124,"seo":168,"stem":169,"__hash__":170},"courses/courses/cloud-computing-fundamentals/en/domains/01-cloud-concepts-and-economics/01-cloud-computing-basics/02-what-is-cloud-computing.md",{"type":19,"value":20,"toc":108},"minimark",[21,26,30,33,37,40,43,46,49,52,55,58,62,65,88,91,95,98,101,105],[22,23,25],"h2",{"id":24},"a-definition-that-has-to-do-real-work","A definition that has to do real work",[27,28,29],"p",{},"\"The cloud\" gets used so loosely that it can mean almost anything: a file synced to a phone, a website hosted somewhere else, an email account you did not have to install software for. That looseness is a problem the moment you need to tell whether a specific service actually is cloud computing, or just something running on someone else's server. You need a definition precise enough to test a service against, not just a feeling.",[27,31,32],{},"The definition the industry actually uses comes from the U.S. National Institute of Standards and Technology (NIST), published in Special Publication 800-145. It is vendor-neutral: NIST does not sell cloud services, so its definition describes the model itself rather than any one provider's marketing.",[22,34,36],{"id":35},"the-nist-definition-phrase-by-phrase","The NIST definition, phrase by phrase",[27,38,39],{},"Here is the full definition:",[27,41,42],{},"\"Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.\"",[27,44,45],{},"That is a dense sentence, so unpack it piece by piece.",[27,47,48],{},"\"Ubiquitous, convenient, on-demand network access\" means you reach the service over a network, almost always the internet, from ordinary devices, whenever you want, without arranging access in advance.",[27,50,51],{},"\"A shared pool of configurable computing resources\" means many customers draw from the same underlying hardware, servers, storage, networking, rather than each customer owning a dedicated machine. \"Configurable\" matters here: you are not just handed a fixed slice, you can shape what you get to fit your needs.",[27,53,54],{},"\"Rapidly provisioned and released\" means capacity appears when you ask for it and disappears when you are done with it, on the order of minutes, not the weeks you saw in the previous lesson.",[27,56,57],{},"\"With minimal management effort or service provider interaction\" means you do not file a request and wait for a human at the provider to act on it. You configure it yourself, through a console, an API, or a command line.",[22,59,61],{"id":60},"the-shape-of-the-full-model","The shape of the full model",[27,63,64],{},"NIST's definition is really the headline for a larger model with 3 parts, each covered in its own place in this course:",[66,67,68,76,82],"ul",{},[69,70,71,75],"li",{},[72,73,74],"strong",{},"5 essential characteristics",", the specific, testable traits every real cloud service has to exhibit. The next lesson walks through all 5 in depth.",[69,77,78,81],{},[72,79,80],{},"3 service models",", IaaS, PaaS, and SaaS, which describe how much of the technology stack the provider manages for you versus how much you manage yourself. You will cover these in the Cloud Service Models topic later in this course.",[69,83,84,87],{},[72,85,86],{},"4 deployment models",", public, private, community, and hybrid, which describe who the infrastructure is shared with. You will cover these in the next topic, Cloud Deployment Models.",[27,89,90],{},"You do not need to memorize those lists yet. What matters here is the shape: a cloud service is defined by characteristics it must have, not by a single technology or a single company.",[22,92,94],{"id":93},"the-boundary-that-trips-people-up","The boundary that trips people up",[27,96,97],{},"Here is the misconception worth naming directly: a server you did not buy is not automatically \"cloud.\" A traditional web host that racks a physical server for you, gives you SSH access, and requires you to email support and wait a day whenever you want more RAM is not cloud computing, even though it is remote and even though someone else owns the hardware. It fails the definition on \"on-demand\" and \"minimal service provider interaction,\" because a human has to act before you get more capacity.",[27,99,100],{},"Contrast that with a service where you open a console, request more capacity, and have it within minutes, with no email, no ticket, no wait. That gap, self-service versus request-and-wait, is the practical test you can apply to almost any service someone calls \"cloud\" to check whether it actually earns the label.",[22,102,104],{"id":103},"carrying-this-forward","Carrying this forward",[27,106,107],{},"You now have the test: a real cloud service is on-demand, self-service, network-accessible, drawn from a shared and elastic resource pool, and billed for what you actually use. The next lesson slows down on each of those 5 traits individually, because they are exactly what a genuine architecture decision, or an exam question, will ask you to recognize.",{"title":109,"searchDepth":110,"depth":110,"links":111},"",3,[112,114,115,116,117],{"id":24,"depth":113,"text":25},2,{"id":35,"depth":113,"text":36},{"id":60,"depth":113,"text":61},{"id":93,"depth":113,"text":94},{"id":103,"depth":113,"text":104},"md",[],[12,13,14,15],{},true,"/courses/cloud-computing-fundamentals/en/domains/01-cloud-concepts-and-economics/01-cloud-computing-basics/02-what-is-cloud-computing",{"passingScore":125,"questions":126},70,[127,136,142,150,160],{"question":128,"type":129,"options":130,"correctAnswer":133,"explanation":135},"Which organization publishes the vendor-neutral definition of cloud computing used throughout this course?","single",[131,132,133,134],"Amazon Web Services","The International Organization for Standardization","The U.S. National Institute of Standards and Technology (NIST)","Microsoft","NIST is a U.S. government standards body with no cloud services to sell, so its SP 800-145 definition describes the model itself rather than any one vendor's product. AWS and Microsoft are cloud providers, not standards bodies, and while ISO publishes its own technology standards, this specific definition originates with NIST.",{"question":137,"type":129,"options":138,"correctAnswer":140,"explanation":141},"According to the NIST definition, a real cloud service requires a person at the provider to manually approve most capacity requests.",[139,140],"True","False","The definition specifically calls for capabilities that are provisioned with minimal management effort or service provider interaction, meaning you provision resources yourself rather than waiting on a human at the provider. A service that requires a support ticket for every change fails this part of the definition.",{"question":143,"type":129,"options":144,"correctAnswer":146,"explanation":149},"A hosting company racks a physical server for a customer, provides SSH access, and requires an email to support (with a 1-day wait) whenever the customer wants more RAM. Why does this NOT qualify as cloud computing under the NIST definition?",[145,146,147,148],"It uses physical hardware instead of software","It fails the requirement for rapid provisioning with minimal service provider interaction","It does not use the internet","It only serves one customer","The definition requires resources to be provisioned quickly with minimal interaction with the provider's staff. Waiting a day for a human to manually add RAM violates that requirement, even though the server is remote and someone else owns the hardware.",{"question":151,"type":152,"options":153,"correctAnswers":158,"explanation":159},"According to the NIST model, which 3 categories break down the full cloud computing model beyond the core definition? (Select all that apply.)","multiple",[154,155,156,157],"Essential characteristics","Service models","Programming languages","Deployment models",[154,155,157],"NIST's model breaks down into 5 essential characteristics, 3 service models (IaaS, PaaS, SaaS), and 4 deployment models (public, private, community, hybrid). Programming languages are not part of the definitional model, since cloud computing is defined by delivery characteristics, not by what code runs on it.",{"question":161,"type":129,"options":162,"correctAnswer":166,"explanation":167},"In the phrase 'a shared pool of configurable computing resources,' what does 'configurable' add to the meaning?",[163,164,165,166],"Only the provider can adjust your resources","You get a fixed, unchangeable slice of the pool","Configuration only applies to networking","You can shape how much of each resource, like storage or compute, you draw from the pool, rather than receiving a one-size-fits-all allocation","Configurable means the resource pool is not a single fixed package. You choose how much compute, storage, or other capacity you need, and that shape can change over time as your needs change.",{"title":7,"description":8},"courses/cloud-computing-fundamentals/en/domains/01-cloud-concepts-and-economics/01-cloud-computing-basics/02-what-is-cloud-computing","U7y35nu3VXw3x3qCDrUI0FpvIBvE4tpNqiU40phdsNU",{"locked":5,"reason":3,"meta":172,"item":181},{"title":173,"description":174,"isFree":122,"estimatedMinutes":175,"difficulty":10,"learningObjectives":176},"Why Cloud Computing Exists","The procurement delays, idle hardware, and upfront costs that made traditional IT painful, and the 3 technologies that had to converge before the cloud could replace it.",13,[177,178,179,180],"Explain the cost and speed problems traditional on-premises IT created for growing teams","Trace the 3 technologies that had to converge before cloud computing became possible","Identify the launch dates of AWS, Google App Engine, and Microsoft Azure","Distinguish the decades-old idea behind the cloud from the recent technology that made it practical",{"id":182,"title":173,"body":183,"description":174,"difficulty":10,"estimatedMinutes":175,"extension":118,"infographics":253,"isFree":122,"learningObjectives":265,"meta":266,"navigation":122,"path":267,"quiz":268,"seo":306,"stem":307,"__hash__":308},"courses/courses/cloud-computing-fundamentals/en/domains/01-cloud-concepts-and-economics/01-cloud-computing-basics/01-why-cloud-computing-exists.md",{"type":19,"value":184,"toc":246},[185,189,192,195,198,202,205,208,212,215,218,221,224,229,233,236,239,243],[22,186,188],{"id":187},"a-launch-date-you-cannot-un-guess","A launch date you cannot un-guess",[27,190,191],{},"Picture a team preparing to launch a new product in 6 months. Before they write a line of code, someone has to answer a question nobody can answer accurately: how many servers will they need on launch day? Guess low, and the site buckles the moment real traffic shows up. Guess high, and the company just spent tens of thousands of dollars on machines that will spend most of their life idle, humming in a rack, drawing power, waiting for a traffic spike that may never come.",[27,193,194],{},"That guess used to be unavoidable. Buying a server was not a same-day decision. A purchase order, an approval chain, a vendor shipment, a rack installation, and a network configuration could easily add up to weeks before the hardware did anything useful. Once it arrived, someone on staff had to keep it running: apply security patches, replace failed drives, keep the room cool, and eventually retire and replace it every few years whether the business had grown into it or not.",[27,196,197],{},"This is the world cloud computing was built to escape: a large upfront purchase (capital expense, or CapEx) made months before you actually need the capacity, based on a guess you will often get wrong in one direction or the other. You will see this cost model contrasted with the cloud's pay-as-you-go alternative in detail later in this domain.",[22,199,201],{"id":200},"an-idea-older-than-the-personal-computer","An idea older than the personal computer",[27,203,204],{},"It is tempting to think of the cloud as a brand-new invention from the 2000s. It is not. The core idea, letting many users share one large, expensive computer instead of each owning a small one, dates back to the 1960s. Mainframe computers of that era cost more than most companies could justify owning outright, so vendors and universities built time-sharing systems: dozens of people connected to the same physical mainframe through remote terminals, each believing they had the machine to themselves. By the mid-1960s, hundreds of companies were selling access to shared computing time this way.",[27,206,207],{},"Time-sharing did not survive the 1970s and 1980s. Minicomputers, and later personal computers, became cheap enough that businesses could simply own their computing instead of renting a slice of someone else's. The shared-mainframe market collapsed, but the underlying idea, that many users could share one large pool of computing power, never went away. It just needed better technology to come back.",[22,209,211],{"id":210},"the-3-pieces-that-had-to-fall-into-place","The 3 pieces that had to fall into place",[27,213,214],{},"Modern cloud computing needed 3 separate advances to converge before it could work at the scale you see today.",[27,216,217],{},"The first was virtualization: software that lets one physical machine safely run several independent, isolated systems at once. IBM had proven this was possible on mainframes back in the 1970s, but it stayed a mainframe-only trick for decades. That changed in 1999, when VMware brought practical virtualization to the ordinary x86 servers that most businesses actually used, turning a mainframe specialty into something any data center could run. The next lesson walks through exactly how this works.",[27,219,220],{},"The second was reliable, affordable internet access. Time-sharing in the 1960s meant dialing into a specific machine over a dedicated line. A cloud has to be reachable from anywhere, on ordinary internet connections, which only became realistic as broadband spread through the 1990s and 2000s.",[27,222,223],{},"The third was a business willing to rent out spare capacity at scale. Amazon had already built massive data centers to handle its own retail traffic spikes, like the holiday shopping season, and realized that capacity sat underused most of the rest of the year. In 2006, it opened that infrastructure to the public as Amazon Web Services, launching with Amazon EC2 for compute and Amazon S3 for storage. Google followed in 2008 with Google App Engine, and Microsoft launched Microsoft Azure in 2010. Within 4 years, the 3 providers that still dominate the market today were all live.",[225,226],"infographic",{"alt":227,"slug":228},"Timeline showing how mainframe time-sharing, x86 virtualization, and the 2006 to 2010 launches of AWS, Google App Engine, and Microsoft Azure combined to make modern cloud computing possible.","why-cloud-computing-exists-timeline",[22,230,232],{"id":231},"what-the-cloud-actually-removes","What the cloud actually removes",[27,234,235],{},"Put the pieces together and you can see exactly what changed. The guessing game around capacity mostly disappears, because you can add or remove servers in minutes instead of weeks. The multi-week wait for hardware to ship and get installed disappears, because there is no hardware to ship to you. The large upfront purchase disappears, because you pay for what you use as you use it instead of buying equipment before you need it. And the ongoing maintenance work, patching, cooling, replacing failed drives, shifts to the provider, whose entire business is doing that at a scale no single company could match.",[27,237,238],{},"None of this makes the 1960s idea new again. It makes it, for the first time, practical: safe to run at scale, reachable from anywhere, and offered as a business you can simply sign up for instead of building yourself.",[22,240,242],{"id":241},"where-this-leaves-you","Where this leaves you",[27,244,245],{},"The problems in this lesson, expensive guessing, slow procurement, and constant maintenance, are the \"why.\" The next lesson gives you the formal \"what\": the definition cloud computing actually has to meet to earn the name, so you can tell a real cloud service apart from a data center someone just calls one.",{"title":109,"searchDepth":110,"depth":110,"links":247},[248,249,250,251,252],{"id":187,"depth":113,"text":188},{"id":200,"depth":113,"text":201},{"id":210,"depth":113,"text":211},{"id":231,"depth":113,"text":232},{"id":241,"depth":113,"text":242},[254],{"slug":228,"concept":255,"style":256,"aspectRatio":257,"labels":258},"A left-to-right timeline with 5 milestone markers spaced across the decades: 1960s mainframe time-sharing, 1999 VMware x86 virtualization, and the 2006, 2008, and 2010 launches of AWS, Google App Engine, and Microsoft Azure clustered near the right end to show how close together the 3 modern platforms arrived once the underlying technology was ready. Each marker gets a short caption naming the event and its significance. A footer strip carries the takeaway line about 3 breakthroughs converging.","timeline","16:9",[259,260,261,262,263,264],"1960s: Mainframe time-sharing lets many users share one expensive computer","1999: VMware brings virtualization to ordinary x86 servers","2006: Amazon Web Services launches EC2 and S3","2008: Google App Engine launches","2010: Microsoft Azure launches","Three separate breakthroughs, sharing, virtualizing, and connecting, had to combine before the cloud became possible",[177,178,179,180],{},"/courses/cloud-computing-fundamentals/en/domains/01-cloud-concepts-and-economics/01-cloud-computing-basics/01-why-cloud-computing-exists",{"passingScore":125,"questions":269},[270,278,282,290,299],{"question":271,"type":129,"options":272,"correctAnswer":274,"explanation":277},"A team guesses wrong about how much server capacity it will need on launch day. What is the risk of guessing too high?",[273,274,275,276],"The site crashes under real traffic","Expensive hardware sits mostly idle","The team pays nothing until launch day","The provider automatically adjusts the order","Guessing too high means paying for capacity that goes unused during quiet periods, the classic overprovisioning problem traditional IT could not avoid. Guessing too low creates the opposite failure, a crash under real traffic, which is why capacity planning was such an expensive risk before the cloud.",{"question":279,"type":129,"options":280,"correctAnswer":140,"explanation":281},"The idea of sharing one large computer among many users originated with cloud providers in the 2000s.",[139,140],"The idea is much older: 1960s mainframe time-sharing let many users share one expensive computer over remote terminals. What the 2000s added was the technology, virtualization, broadband internet, and providers willing to rent out spare capacity, to make that old idea practical at a global scale.",{"question":283,"type":129,"options":284,"correctAnswer":287,"explanation":289},"Which 1999 development made it practical to bring virtualization from mainframes to the ordinary x86 servers most businesses used?",[285,286,287,288],"The launch of Amazon Web Services","Broadband internet access","VMware's virtualization software for x86 servers","Time-sharing terminals","VMware reinvented virtual machines for x86 systems in 1999, turning a mainframe-only trick into something any ordinary data center could run. AWS launched years later in 2006, building on this and other advances rather than causing them.",{"question":291,"type":152,"options":292,"correctAnswers":297,"explanation":298},"Which of these were genuine drawbacks of traditional on-premises IT, according to this lesson? (Select all that apply.)",[293,294,295,296],"Weeks of lead time to buy, ship, and install new hardware","A large capital expense paid before you know how much you will use","Automatic scaling that matches real-time demand","In-house staff time spent on patching and maintaining hardware",[293,294,296],"Procurement delays, large upfront capital expense, and ongoing in-house maintenance were all real costs of on-premises IT. Automatic scaling to match real-time demand is a cloud characteristic that on-premises hardware, fixed in size once purchased, cannot do.",{"question":300,"type":129,"options":301,"correctAnswer":131,"explanation":305},"A company built large data centers to handle its own holiday shopping traffic spikes, then noticed that capacity sat underused the rest of the year. Renting that spare capacity out to the public became the founding idea behind which service, launched in 2006?",[131,302,303,304],"Microsoft Azure","Google App Engine","VMware","Amazon built its own data centers to handle retail traffic spikes like the holiday season, then opened that spare capacity to the public in 2006 as Amazon Web Services, launching with EC2 for compute and S3 for storage. Google App Engine (2008) and Microsoft Azure (2010) followed a few years later.",{"title":173,"description":174},"courses/cloud-computing-fundamentals/en/domains/01-cloud-concepts-and-economics/01-cloud-computing-basics/01-why-cloud-computing-exists","kNrYLAoGbSmgkrX59C3Hzxh_XaEgi-BRJ_yaY1nsmLc"]