According to the NIST (Mell & Grance 2009), there are six fundamental characteristics that make cloud computing different from other more conventional ICT outsourcing facilities. Many academics and industry analysts including (Armbrust et al. 2009), (Vaquero et al. 2008) (McKinsey&Company 2009) and (Daryl C. Plummer et al. 2009), have refined these characteristics and argue that to be considered a cloud service, a solution should adhere to some combination of these attributes.
On-demand self-service: a customer can unilaterally provision computing resources as needed, such as server time and network storage, without requiring any human intervention in the process and by using just a credit card. It is not even necessary to be registered as a legal commercial entity. Plummer et al. in “Five Refining Attributes of Public and private cloud Computing” further contend the importance of the service-based characteristics of cloud computing through the claim that consumer concerns should be abstracted from provider concerns in that the interfaces should hide the implementation details and enable a completely automated and ready-to-use response to the consumer of the service. The articulation of the service feature is based on service levels and ICT concerns such as availability, response time, performance versus price, and clear and predefined operational processes, rather than technology and its capabilities. In other words, “what the service needs to do is more important than how the technologies are used to implement the solution”
Pay-per-use: customers pay services on a pay-per-use (or pay-as-you-go) basis. This characteristic addresses the utility dimension of cloud computing, but utility computing must not be confused with cloud computing as a whole because it relates rather to the pay-per-use business model of the cloud rather than being a substitutive term. Furthermore, the pay-peruse transferability does not make the difference between buying compute power out of one virtual machine for 1000 hours and buying compute power out of 1000 virtual machines for one hour. The cost is the same. Altogether, the pay-per-use characteristic implies that enterprises incur no infrastructure capital costs, just operational thanks to the pay-per-use business model with no contractual obligations.
Scalable and elastic: elasticity is a key characteristic of cloud computing, which resides in the ability to quickly increase or decrease ICT resources (i.e. compute power, storage and network capacity on demand). Elasticity15 is a trait of shared pools of resources. It allows provisioning any number of server instances and disk storage programmatically in an economical way, that is, on a fine-grained basis with a lead time of minutes rather than weeks. To a customer, capabilities available for provisioning ICT resources often appear to be unlimited and can be purchased in any quantity at any time which allows matching resource allocation with the current workload. Scalability is a feature of the underlying infrastructure and software platforms. For example, a scalable service called Auto Scaling in AWS removes the need for customers to plan far ahead of time for more capacity. For example, AWS Auto Scaling allows to automatically scale Amazon EC2 capacity up or down according to the conditions set by the customer. Amazon claims that with Auto Scaling, customers can ensure that the number of Amazon EC2 instances they are using scales up seamlessly during demand spikes to maintain performance, and scales down automatically during demand lulls to minimize costs. Complementary to the concept of elasticity are the concepts of over-drafting or cloud-bursting. Cloud-bursting pushes elasticity even further by allowing to automatically get more capacity from external clouds when the primary cloud infrastructure is overloaded. The concept of over-drafting also supports the idea of a cloud Market Exchange whereby providers could trade compute capacity at a spot price when supply and demand fluctuate over time. Cloud-bursting, in turn, allows to migrate application workloads out of the in-house datacenter to the cloud when the local infrastructure is overloaded.
Shared resource pooling: ICT resources are pooled to serve multiple consumers in a multitenant (shared) fashion to leverage economies of scale and achieve maximum efficiency. Amrbrust et al. (2009) coined the term statistical multiplexing to describe how providers bet on the likelihood that, at any point in time, the demand never exceed the capacity of the infrastructure by shuffling virtual resources across datacenters. This scheme works on the principle that the more applications and the more users using the cloud, the more dispersed are the load profiles, whereby applications running at peak load can “borrow” resources from idle applications or applications running in a quiet state. To be efficient, resource pooling requires a high degree of virtualization, automated operations and state-of-the-art resource provisioning capabilities. There is a sense of location independence and transparency in that the customer generally has no control or knowledge over the exact location of the provided resources but may be able to specify location at a higher level of abstraction (for example, country, state or datacenter).
Uses Internet technologies: cloud services are delivered using Internet technologies including Universal Resource Identifiers (URI), data formats and protocols, such as XML, HTTP, and representational state transfer (Restful) Web services. In other words, cloud computing is Internet-centric, allowing ubiquitous access over the network through standard mechanisms that promote use by heterogeneous thin or thick client platforms (e.g., mobile phones, laptops and PDAs). In that, it offers a computing software model that is multi- platform, multi-network and global.
On-demand self-service: a customer can unilaterally provision computing resources as needed, such as server time and network storage, without requiring any human intervention in the process and by using just a credit card. It is not even necessary to be registered as a legal commercial entity. Plummer et al. in “Five Refining Attributes of Public and private cloud Computing” further contend the importance of the service-based characteristics of cloud computing through the claim that consumer concerns should be abstracted from provider concerns in that the interfaces should hide the implementation details and enable a completely automated and ready-to-use response to the consumer of the service. The articulation of the service feature is based on service levels and ICT concerns such as availability, response time, performance versus price, and clear and predefined operational processes, rather than technology and its capabilities. In other words, “what the service needs to do is more important than how the technologies are used to implement the solution”
Pay-per-use: customers pay services on a pay-per-use (or pay-as-you-go) basis. This characteristic addresses the utility dimension of cloud computing, but utility computing must not be confused with cloud computing as a whole because it relates rather to the pay-per-use business model of the cloud rather than being a substitutive term. Furthermore, the pay-peruse transferability does not make the difference between buying compute power out of one virtual machine for 1000 hours and buying compute power out of 1000 virtual machines for one hour. The cost is the same. Altogether, the pay-per-use characteristic implies that enterprises incur no infrastructure capital costs, just operational thanks to the pay-per-use business model with no contractual obligations.
Scalable and elastic: elasticity is a key characteristic of cloud computing, which resides in the ability to quickly increase or decrease ICT resources (i.e. compute power, storage and network capacity on demand). Elasticity15 is a trait of shared pools of resources. It allows provisioning any number of server instances and disk storage programmatically in an economical way, that is, on a fine-grained basis with a lead time of minutes rather than weeks. To a customer, capabilities available for provisioning ICT resources often appear to be unlimited and can be purchased in any quantity at any time which allows matching resource allocation with the current workload. Scalability is a feature of the underlying infrastructure and software platforms. For example, a scalable service called Auto Scaling in AWS removes the need for customers to plan far ahead of time for more capacity. For example, AWS Auto Scaling allows to automatically scale Amazon EC2 capacity up or down according to the conditions set by the customer. Amazon claims that with Auto Scaling, customers can ensure that the number of Amazon EC2 instances they are using scales up seamlessly during demand spikes to maintain performance, and scales down automatically during demand lulls to minimize costs. Complementary to the concept of elasticity are the concepts of over-drafting or cloud-bursting. Cloud-bursting pushes elasticity even further by allowing to automatically get more capacity from external clouds when the primary cloud infrastructure is overloaded. The concept of over-drafting also supports the idea of a cloud Market Exchange whereby providers could trade compute capacity at a spot price when supply and demand fluctuate over time. Cloud-bursting, in turn, allows to migrate application workloads out of the in-house datacenter to the cloud when the local infrastructure is overloaded.
Shared resource pooling: ICT resources are pooled to serve multiple consumers in a multitenant (shared) fashion to leverage economies of scale and achieve maximum efficiency. Amrbrust et al. (2009) coined the term statistical multiplexing to describe how providers bet on the likelihood that, at any point in time, the demand never exceed the capacity of the infrastructure by shuffling virtual resources across datacenters. This scheme works on the principle that the more applications and the more users using the cloud, the more dispersed are the load profiles, whereby applications running at peak load can “borrow” resources from idle applications or applications running in a quiet state. To be efficient, resource pooling requires a high degree of virtualization, automated operations and state-of-the-art resource provisioning capabilities. There is a sense of location independence and transparency in that the customer generally has no control or knowledge over the exact location of the provided resources but may be able to specify location at a higher level of abstraction (for example, country, state or datacenter).
Uses Internet technologies: cloud services are delivered using Internet technologies including Universal Resource Identifiers (URI), data formats and protocols, such as XML, HTTP, and representational state transfer (Restful) Web services. In other words, cloud computing is Internet-centric, allowing ubiquitous access over the network through standard mechanisms that promote use by heterogeneous thin or thick client platforms (e.g., mobile phones, laptops and PDAs). In that, it offers a computing software model that is multi- platform, multi-network and global.
Metered by use: cloud services are tracked with usage metrics to enable multiple payment models. The service provider has a usage accounting model for measuring the use of the services, which could then be used to create different pricing plans and models. These may include pay-as-you go plans, subscriptions, fixed plans and even free plans. The implied payment plans will be based on usage, not on the cost of the equipment. These plans are based on the amount of service used by the consumers, which may be in terms of hours, data transfers or other use-based attributes delivered providing transparency for both the provider and the consumer.
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