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Cloud computing

Cloud computing[1] is the on-demand availability of computer system resources, especially data storage (cloud storage) and computing power, without direct active management by the user.[2] Large clouds often have functions distributed over multiple locations, each of which is a data center. Cloud computing relies on sharing of resources to achieve coherence and typically uses a pay-as-you-go model, which can help in reducing capital expenses but may also lead to unexpected operating expenses for users.[3]

"Cloud Computing" redirects here. For the horse, see Cloud Computing (horse).

On-demand self-service. A consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed automatically without requiring human interaction with each service provider.

Broad network access. Capabilities are available over the network and accessed through standard mechanisms that promote use by heterogeneous thin or thick client platforms (e.g., mobile phones, tablets, , and workstations).

laptops

. The provider's computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to consumer demand. 

Resource pooling

Rapid elasticity. Capabilities can be elastically provisioned and released, in some cases automatically, to scale rapidly outward and inward commensurate with demand. To the consumer, the capabilities available for provisioning often appear unlimited and can be appropriated in any quantity at any time.

Measured service. Cloud systems automatically control and optimize resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and active user accounts). Resource usage can be monitored, controlled, and reported, providing transparency for both the provider and consumer of the utilized service.

[5]

A European Commission communication issued in 2012 argued that the breadth of scope offered by cloud computing made a general definition "elusive",[4] but the United States National Institute of Standards and Technology's 2011 definition of cloud computing identified "five essential characteristics":

Public-resource computing – This type of distributed cloud results from an expansive definition of cloud computing, because they are more akin to distributed computing than cloud computing. Nonetheless, it is considered a sub-class of cloud computing.

Volunteer cloud – Volunteer cloud computing is characterized as the intersection of public-resource computing and cloud computing, where a cloud computing infrastructure is built using volunteered resources. Many challenges arise from this type of infrastructure, because of the volatility of the resources used to build it and the dynamic environment it operates in. It can also be called peer-to-peer clouds, or ad-hoc clouds. An interesting effort in such direction is Cloud@Home, it aims to implement a cloud computing infrastructure using volunteered resources providing a business-model to incentivize contributions through financial restitution.

[84]

Market

According to International Data Corporation (IDC), global spending on cloud computing services has reached $706 billion and expected to reach $1.3 trillion by 2025.[97] While Gartner estimated that global public cloud services end-user spending would reach $600 billion by 2023.[98] As per a McKinsey & Company report, cloud cost-optimization levers and value-oriented business use cases foresee more than $1 trillion in run-rate EBITDA across Fortune 500 companies as up for grabs in 2030.[99] In 2022, more than $1.3 trillion in enterprise IT spending was at stake from the shift to the cloud, growing to almost $1.8 trillion in 2025, according to Gartner.[100]

Adobe Creative Cloud

Amazon Web Services

Google Cloud

IBM Cloud

Microsoft Azure

OpenStack

Oracle Cloud

Panorama9

– Client–server computing refers broadly to any distributed application that distinguishes between service providers (servers) and service requestors (clients).[102]

Client–server model

– A service bureau providing computer services, particularly from the 1960s to 1980s.

Computer bureau

– 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.

Grid computing

– Distributed computing paradigm that provides data, compute, storage and application services closer to the client or near-user edge devices, such as network routers. Furthermore, fog computing handles data at the network level, on smart devices and on the end-user client-side (e.g. mobile devices), instead of sending data to a remote location for processing.

Fog computing

– The "packaging of computing resources, such as computation and storage, as a metered service similar to a traditional public utility, such as electricity."[103][104]

Utility computing

– A distributed architecture without the need for central coordination. Participants are both suppliers and consumers of resources (in contrast to the traditional client-server model).

Peer-to-peer

– A live, isolated computer environment in which a program, code or file can run without affecting the application in which it runs.

Cloud sandbox

The goal of cloud computing is to allow users to take benefit from all of these technologies, without the need for deep knowledge about or expertise with each one of them. The cloud aims to cut costs and helps the users focus on their core business instead of being impeded by IT obstacles.[101] The main enabling technology for cloud computing is virtualization. Virtualization software separates a physical computing device into one or more "virtual" devices, each of which can be easily used and managed to perform computing tasks. With operating system–level virtualization essentially creating a scalable system of multiple independent computing devices, idle computing resources can be allocated and used more efficiently. Virtualization provides the agility required to speed up IT operations and reduces cost by increasing infrastructure utilization. Autonomic computing automates the process through which the user can provision resources on-demand. By minimizing user involvement, automation speeds up the process, reduces labor costs and reduces the possibility of human errors.[101]


Cloud computing uses concepts from utility computing to provide metrics for the services used. Cloud computing attempts to address QoS (quality of service) and reliability problems of other grid computing models.[101]


Cloud computing shares characteristics with:

Millard, Christopher (2013). . Oxford University Press. ISBN 978-0-19-967168-7.

Cloud Computing Law

Weisser, Alexander (2020). . Editions Juridiques Libres, ISBN 978-2-88954-030-3.

International Taxation of Cloud Computing

Singh, Jatinder; Powles, Julia; Pasquier, Thomas; Bacon, Jean (July 2015). . IEEE Cloud Computing. 2 (4): 24–32. doi:10.1109/MCC.2015.69. S2CID 9812531.

"Data Flow Management and Compliance in Cloud Computing"

Armbrust, Michael; Stoica, Ion; Zaharia, Matei; Fox, Armando; Griffith, Rean; Joseph, Anthony D.; Katz, Randy; Konwinski, Andy; Lee, Gunho; Patterson, David; Rabkin, Ariel (1 April 2010). . Communications of the ACM. 53 (4): 50. doi:10.1145/1721654.1721672. S2CID 1673644.

"A view of cloud computing"

Hu, Tung-Hui (2015). A Prehistory of the Cloud. MIT Press.  978-0-262-02951-3.

ISBN

Mell, P. (2011, September). . Retrieved November 1, 2015, from National Institute of Standards and Technology website

The NIST Definition of Cloud Computing


Media related to Cloud computing at Wikimedia Commons