Cloud computing is the use of computing resources (hardware and software) that are delivered as a service over a network (typically the Internet). The name comes from the use of a cloud-shaped symbol as an abstraction for the complex infrastructure it contains in system diagrams. Cloud computing entrusts remote services with a user's data, software and computation.
There are many types of public cloud computing:
There are many types of public cloud computing:
Infrastructure as a service (IaaS)
Platform as a service (PaaS)
Software as a service (SaaS)
Storage as a service (STaaS)
Security as a service (SECaaS)
Data as a service (DaaS)
Database as a service (DBaaS)
Test environment as a service (TEaaS)
Desktop virtualization
API as a service (APIaaS)
Backend as a service (BaaS)
In the business model using software as a service, users are provided access to application software and databases. The cloud providers manage the infrastructure and platforms on which the applications run. SaaS is sometimes referred to as “on-demand software” and is usually priced on a pay-per-use basis. Saas providers generally price applications using a subscription fee.
Proponents claim that the SaaS allows a business the potential to reduce IT operational costs by outsourcing hardware and software maintenance and support to the cloud provider. This will enable a business to reallocate IT operations to focus on other IT goals. In addition, the application is hosted centrally, so updates can be released without users having to reinstall new software. The drawback of SaaS is that the user stores their data on the cloud provider’s server. As a result, there could be unauthorized access to the data.
End users access cloud-based applications through a web browser or a light-weight desktop or mobile app while the business software and user's data are stored on servers at a remote location. Proponents claim that cloud computing allows enterprises to get their applications up and running faster, with improved manageability and less maintenance, and enables IT to more rapidly adjust resources to meet fluctuating and unpredictable business demand.
Cloud computing relies on sharing of resources to achieve coherence and economies of scale similar to a utility (like the electricity grid) over a network. At the foundation of cloud computing is the broader concept of converged infrastructure and shared services.
History
The origin of the term cloud computing is obscure, but it appears to derive from the practice of using drawings of stylized clouds to denote networks in diagrams of computing and communications systems. The word cloud is used as a metaphor for the Internet, based on the standardized use of a cloud-like shape to denote a network on telephony schematics and later to depict the Internet in computer network diagrams as an abstraction of the underlying infrastructure it represents. The cloud symbol was used to represent the Internet as early as 1994.
In the 1990s, telecommunications companies who previously offered primarily dedicated point-to-point data circuits, began offering virtual private network (VPN) services with comparable quality of service but at a much lower cost. By switching traffic to balance utilization as they saw fit, they were able to utilize their overall network bandwidth more effectively. The cloud symbol was used to denote the demarcation point between that which was the responsibility of the provider and that which was the responsibility of the users. Cloud computing extends this boundary to cover servers as well as the network infrastructure.
The underlying concept of cloud computing dates back to the 1950s; when large-scale mainframe became available in academia and corporations, accessible via thin clients / terminal computers. Because it was costly to buy a mainframe, it became important to find ways to get the greatest return on the investment in them, allowing multiple users to share both the physical access to the computer from multiple terminals as well as to share the CPU time, eliminating periods of inactivity, which became known in the industry as time-sharing.
As computers became more prevalent, scientists and technologists explored ways to make large-scale computing power available to more users through time sharing, experimenting with algorithms to provide the optimal use of the infrastructure, platform and applications with prioritized access to the CPU and efficiency for the end users.
John McCarthy opined in the 1960s that "computation may someday be organized as a public utility." Almost all the modern-day characteristics of cloud computing (elastic provision, provided as a utility, online, illusion of infinite supply), the comparison to the electricity industry and the use of public, private, government, and community forms, were thoroughly explored in Douglas Parkhill's 1966 book, The Challenge of the Computer Utility. Other scholars have shown that cloud computing's roots go all the way back to the 1950s when scientist Herb Grosch (the author of Grosch's law) postulated that the entire world would operate on dumb terminals powered by about 15 large data centers. Due to the expense of these powerful computers, many corporations and other entities could avail themselves of computing capability through time sharing and several organizations, such as GE's GEISCO, IBM subsidiary The Service Bureau Corporation (SBC, founded in 1957), Tymshare (founded in 1966), National CSS (founded in 1967 and bought by Dun & Bradstreet in 1979), Dial Data (bought by Tymshare in 1968), and Bolt, Beranek and Newman (BBN) marketed time sharing as a commercial venture.
The development of the Internet from being document centric via semantic data towards more and more services was described as "Dynamic Web". This contribution focused in particular in the need for better meta-data able to describe not only implementation details but also conceptual details of model-based applications.
The ubiquitous availability of high-capacity networks, low-cost computers and storage devices as well as the widespread adoption of hardware virtualization, service-oriented architecture, autonomic, and utility computing have led to a tremendous growth in cloud computing.
After the dot-com bubble, Amazon played a key role in the development of cloud computing by modernizing their data centers, which, like most computer networks, were using as little as 10% of their capacity at any one time, just to leave room for occasional spikes. Having found that the new cloud architecture resulted in significant internal efficiency improvements whereby small, fast-moving "two-pizza teams" (teams small enough to be fed with two pizzas) could add new features faster and more easily, Amazon initiated a new product development effort to provide cloud computing to external customers, and launched Amazon Web Service (AWS) on a utility computing basis in 2006.
In early 2008, Eucalyptus became the first open-source, AWS API-compatible platform for deploying private clouds. In early 2008, OpenNebula, enhanced in the RESERVOIR European Commission-funded project, became the first open-source software for deploying private and hybrid clouds, and for the federation of clouds. In the same year, efforts were focused on providing quality of service guarantees (as required by real-time interactive applications) to cloud-based infrastructures, in the framework of the IRMOS European Commission-funded project, resulting to a real-time cloud environment. By mid-2008, Gartner saw an opportunity for cloud computing "to shape the relationship among consumers of IT services, those who use IT services and those who sell them" and observed that "organizations are switching from company-owned hardware and software assets to per-use service-based models" so that the "projected shift to computing... will result in dramatic growth in IT products in some areas and significant reductions in other areas."
On March 1, 2011, IBM announced the Smarter Computing framework to support Smarter Planet.
Among the various components of the Smarter Computing foundation, cloud computing is a critical piece.
Similar systems and concepts
Cloud computing shares characteristics :
Autonomic computing — Computer systems capable of self-management.
Client–server model — Client–server computing refers broadly to any distributed application that distinguishes between service providers (servers) and service requesters (clients).
Grid computing — "A form of distributed and parallel computing, whereby a 'super and virtual computer' is composed of a cluster of networked, loosely coupled computers acting in concert to perform very large tasks."
Mainframe computer — Powerful computers used mainly by large organizations for critical applications, typically bulk data processing such as census, industry and consumer statistics, police and secret intelligence services, enterprise resource planning, and financial transaction processing.
Utility computing — The "packaging of computing resources, such as computation and storage, as a metered service similar to a traditional public utility, such as electricity."
Peer-to-peer — Distributed architecture without the need for central coordination, with participants being at the same time both suppliers and consumers of resources (in contrast to the traditional client–server model).
Cloud gaming - Also known as on-demand gaming, this is a way of delivering games to computers. The gaming data will be stored in the provider's server, so that gaming will be independent of client computers used to play the game.
On-demand self-service
On-demand self-service allows users to obtain, configure and deploy cloud services themselves using cloud service catalogues, without requiring the assistance of IT. This feature is listed by the The National Institute of Standards and Technology (NIST) as a characteristic of cloud computing.
The self-service requirement of cloud computing prompts infrastructure vendors to create cloud computing templates, which are obtained from cloud service catalogues. Manufacturers of such templates or blueprints include Hewlett-Packard (HP), which names its templates as HP Cloud Maps RightScale and Red Hat, which names its templates CloudForms.
The templates contain predefined configurations used to by consumers to set up cloud services. The templates or blueprints provide the technical information necessary to build ready-to-use clouds. Each template includes specific configuration details for different cloud infrastructures, with information about servers for specific tasks such as hosting applications, databases, websites and so on. The templates also include predefined Web service, the operating system, the database, security configurations and load balancing.
Cloud consumers use cloud templates to move applications between clouds through a self-service portal. The predefined blueprints define all that an application requires to run in different environments. For example, a template could define how the same application could be deployed in cloud platforms based on Amazon Web Service, VMware or Red Hat. The user organization benefits from cloud templates because the technical aspects of cloud configurations reside in the templates, letting users to deploy cloud services with a push of a button. Cloud templates can also be used by developers to create a catalog of cloud services.
Similar systems and concepts
Cloud computing shares characteristics :
Autonomic computing — Computer systems capable of self-management.
Client–server model — Client–server computing refers broadly to any distributed application that distinguishes between service providers (servers) and service requesters (clients).
Grid computing — "A form of distributed and parallel computing, whereby a 'super and virtual computer' is composed of a cluster of networked, loosely coupled computers acting in concert to perform very large tasks."
Mainframe computer — Powerful computers used mainly by large organizations for critical applications, typically bulk data processing such as census, industry and consumer statistics, police and secret intelligence services, enterprise resource planning, and financial transaction processing.
Utility computing — The "packaging of computing resources, such as computation and storage, as a metered service similar to a traditional public utility, such as electricity."
Peer-to-peer — Distributed architecture without the need for central coordination, with participants being at the same time both suppliers and consumers of resources (in contrast to the traditional client–server model).
Cloud gaming - Also known as on-demand gaming, this is a way of delivering games to computers. The gaming data will be stored in the provider's server, so that gaming will be independent of client computers used to play the game.
On-demand self-service
On-demand self-service allows users to obtain, configure and deploy cloud services themselves using cloud service catalogues, without requiring the assistance of IT. This feature is listed by the The National Institute of Standards and Technology (NIST) as a characteristic of cloud computing.
The self-service requirement of cloud computing prompts infrastructure vendors to create cloud computing templates, which are obtained from cloud service catalogues. Manufacturers of such templates or blueprints include Hewlett-Packard (HP), which names its templates as HP Cloud Maps RightScale and Red Hat, which names its templates CloudForms.
The templates contain predefined configurations used to by consumers to set up cloud services. The templates or blueprints provide the technical information necessary to build ready-to-use clouds. Each template includes specific configuration details for different cloud infrastructures, with information about servers for specific tasks such as hosting applications, databases, websites and so on. The templates also include predefined Web service, the operating system, the database, security configurations and load balancing.
Cloud consumers use cloud templates to move applications between clouds through a self-service portal. The predefined blueprints define all that an application requires to run in different environments. For example, a template could define how the same application could be deployed in cloud platforms based on Amazon Web Service, VMware or Red Hat. The user organization benefits from cloud templates because the technical aspects of cloud configurations reside in the templates, letting users to deploy cloud services with a push of a button. Cloud templates can also be used by developers to create a catalog of cloud services.
Service models
Cloud computing providers offer their services according to three fundamental models:
Infrastructure as a service (IaaS), platform as a service (PaaS), and
software as a service (SaaS) where IaaS is the most basic and each
higher model abstracts from the details of the lower models.
Infrastructure as a service (IaaS)
In this most basic cloud service model, providers offer computers, as physical or more often as virtual machines, and other resources. The virtual machines are run as guests by a hypervisor, such as Xen or KVM. Management of pools of hypervisors by the cloud operational support system leads to the ability to scale to support a large number of virtual machines. Other resources in IaaS clouds include images in a virtual machine image library, raw (block) and file-based storage, firewalls, load balancers, IP addresses, virtual local area networks (VLANs), and software bundles.[48] Amies, Alex; Sluiman, Harm; Tong IaaS cloud providers supply these resources on demand from their large pools installed in data centers. For wide area connectivity, the Internet can be used or—in carrier clouds -- dedicated virtual private networks can be configured., Qiang Guo (July 2012). "Infrastructure as a Service Cloud Concepts". Developing and Hosting Applications on the Cloud. IBM Press. ISBN 978-0-13-306684-5.
To deploy their applications, cloud users then install operating system images on the machines as well as their application software. In this model, it is the cloud user who is responsible for patching and maintaining the operating systems and application software. Cloud providers typically bill IaaS services on a utility computing basis, that is, cost will reflect the amount of resources allocated and consumed. STaaS - STorage As A Service. This service comes under IaaS, which manages all the storage services in cloud computing. There are many security issues in this service. They are 1. Data Integrity 2. Confidentiality 3. Reliability, etc.
IaaS refers not to a machine that does all the work, but simply to a facility given to businesses that offers users the leverage of extra storage space in servers and data centers.
Examples of IaaS include: Amazon CloudFormation (and underlying services such as Amazon EC2), Rackspace Cloud, Terremark, Windows Azure Virtual Machines, Google Compute Engine. and Joyent.
Platform as a service (PaaS)
In the PaaS model, cloud providers deliver a computing platform typically including operating system, programming language execution environment, database, and web server. Application developers can develop and run their software solutions on a cloud platform without the cost and complexity of buying and managing the underlying hardware and software layers. With some PaaS offers, the underlying computer and storage resources scale automatically to match application demand such that cloud user does not have to allocate resources manually.
Examples of PaaS include: Amazon Elastic Beanstalk, Cloud Foundry, Heroku, Force.com, EngineYard, Mendix, Google App Engine, Windows Azure Compute and OrangeScape.
To deploy their applications, cloud users then install operating system images on the machines as well as their application software. In this model, it is the cloud user who is responsible for patching and maintaining the operating systems and application software. Cloud providers typically bill IaaS services on a utility computing basis, that is, cost will reflect the amount of resources allocated and consumed. STaaS - STorage As A Service. This service comes under IaaS, which manages all the storage services in cloud computing. There are many security issues in this service. They are 1. Data Integrity 2. Confidentiality 3. Reliability, etc.
IaaS refers not to a machine that does all the work, but simply to a facility given to businesses that offers users the leverage of extra storage space in servers and data centers.
Examples of IaaS include: Amazon CloudFormation (and underlying services such as Amazon EC2), Rackspace Cloud, Terremark, Windows Azure Virtual Machines, Google Compute Engine. and Joyent.
Platform as a service (PaaS)
In the PaaS model, cloud providers deliver a computing platform typically including operating system, programming language execution environment, database, and web server. Application developers can develop and run their software solutions on a cloud platform without the cost and complexity of buying and managing the underlying hardware and software layers. With some PaaS offers, the underlying computer and storage resources scale automatically to match application demand such that cloud user does not have to allocate resources manually.
Examples of PaaS include: Amazon Elastic Beanstalk, Cloud Foundry, Heroku, Force.com, EngineYard, Mendix, Google App Engine, Windows Azure Compute and OrangeScape.
Software as a service (SaaS)
In this model, cloud providers install and operate application software in the cloud and cloud users access the software from cloud clients. The cloud users do not manage the cloud infrastructure and platform on which the application is running. This eliminates the need to install and run the application on the cloud user's own computers simplifying maintenance and support. What makes a cloud application different from other applications is its scalability. This can be achieved by cloning tasks onto multiple virtual machines at run-time to meet the changing work demand. Load balancers distribute the work over the set of virtual machines. This process is transparent to the cloud user who sees only a single access point. To accommodate a large number of cloud users, cloud applications can be multitenant, that is, any machine serves more than one cloud user organization. It is common to refer to special types of cloud based application software with a similar naming convention: desktop as a service, business process as a service, test environment as a service, communication as a service.
The pricing model for SaaS applications is typically a monthly or yearly flat fee per user, so price is scalable and adjustable if users are added or removed at any point.
Examples of SaaS include: Google Apps, Microsoft Office 365, and Onlive.
In this model, cloud providers install and operate application software in the cloud and cloud users access the software from cloud clients. The cloud users do not manage the cloud infrastructure and platform on which the application is running. This eliminates the need to install and run the application on the cloud user's own computers simplifying maintenance and support. What makes a cloud application different from other applications is its scalability. This can be achieved by cloning tasks onto multiple virtual machines at run-time to meet the changing work demand. Load balancers distribute the work over the set of virtual machines. This process is transparent to the cloud user who sees only a single access point. To accommodate a large number of cloud users, cloud applications can be multitenant, that is, any machine serves more than one cloud user organization. It is common to refer to special types of cloud based application software with a similar naming convention: desktop as a service, business process as a service, test environment as a service, communication as a service.
The pricing model for SaaS applications is typically a monthly or yearly flat fee per user, so price is scalable and adjustable if users are added or removed at any point.
Examples of SaaS include: Google Apps, Microsoft Office 365, and Onlive.
Cloud clients
Users access cloud computing using networked client devices, such as desktop computers, laptops, tablets and smartphones. Some of these devices - cloud clients - rely on cloud computing for all or a majority of their applications so as to be essentially useless without it. Examples are thin clients and the browser-based Chromebook. Many cloud applications do not require specific software on the client and instead use a web browser to interact with the cloud application. With Ajax and HTML5 these Web user interfaces can achieve a similar or even better look and feel as native applications. Some cloud applications, however, support specific client software dedicated to these applications (e.g., virtual desktop clients and most email clients). Some legacy applications (line of business applications that until now have been prevalent in thin client Windows computing) are delivered via a screen-sharing technology.
Deployment models
Cloud computing types
Public cloud
Public cloud applications, storage, and other resources are made
available to the general public by a service provider. These services
are free or offered on a pay-per-use model. Generally, public cloud
service providers like Amazon AWS, Microsoft and Google own and operate
the infrastructure and offer access only via Internet (direct
connectivity is not offered).
Community cloud
Community cloud
shares infrastructure between several organizations from a specific
community with common concerns (security, compliance, jurisdiction,
etc.), whether managed internally or by a third-party and hosted
internally or externally. The costs are spread over fewer users than a
public cloud (but more than a private cloud), so only some of the cost
savings potential of cloud computing are realized.
Hybrid cloud
Hybrid cloud is a composition of two or more clouds (private,
community or public) that remain unique entities but are bound together,
offering the benefits of multiple deployment models.
By utilizing "hybrid cloud" architecture, companies and individuals
are able to obtain degrees of fault tolerance combined with locally
immediate usability without dependency on internet connectivity. Hybrid
cloud architecture requires both on-premises resources and off-site
(remote) server-based cloud infrastructure.
Hybrid clouds lack the flexibility, security and certainty of in-house applications.
Hybrid cloud provides the flexibility of in house applications with the
fault tolerance and scalability of cloud based services.
Private cloud
Private cloud is cloud infrastructure operated solely for a single
organization, whether managed internally or by a third-party and hosted
internally or externally.
Undertaking a private cloud project requires a significant level and
degree of engagement to virtualize the business environment, and it will
require the organization to reevaluate decisions about existing
resources. When it is done right, it can have a positive impact on a
business, but every one of the steps in the project raises security
issues that must be addressed in order to avoid serious vulnerabilities.
They have attracted criticism because users "still have to buy,
build, and manage them" and thus do not benefit from less hands-on
management, essentially "[lacking] the economic model that makes cloud computing such an intriguing concept".
Architecture
Cloud computing sample architecture
Cloud architecture, the systems architecture of the software systems involved in the delivery of cloud computing, typically involves multiple cloud components
communicating with each other over a loose coupling mechanism such as a
messaging queue. Elastic provision implies intelligence in the use of
tight or loose coupling as applied to mechanisms such as these and
others.
The Intercloud
Main article: Intercloud
The Intercloud is an interconnected global "cloud of clouds" and an extension of the Internet "network of networks" on which it is based.
Cloud engineering
Cloud engineering is the application of engineering
disciplines to cloud computing. It brings a systematic approach to the
high-level concerns of commercialisation, standardisation, and
governance in conceiving, developing, operating and maintaining cloud
computing systems. It is a multidisciplinary method encompassing
contributions from diverse areas such as systems, software, web, performance, information, security, platform, risk, and quality engineering.
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