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Cloud computing architecture refers to the components and subcomponents required for cloud computing.These components typically consist of a front end platform (fat client, thin client, mobile), back end platforms (servers, storage), a cloud based delivery, and a network (Internet, Intranet, Intercloud).
Hybrid SaaS refers to a deployment model where a software application is delivered as a service and combines elements of both on-premises and cloud-based infrastructure. In this model, some components or data reside on the customer's local infrastructure (on-premises) while others are hosted in the cloud.
Cloud bursting is an application deployment model in which an application runs in a private cloud or data center and "bursts" to a public cloud when the demand for computing capacity increases. A primary advantage of cloud bursting and a hybrid cloud model is that an organization pays for extra compute resources only when they are needed. [90]
Software as a service (SaaS / s æ s / [1]) is a cloud computing service model where the provider offers use of application software to a client and manages all needed physical and software resources. [2] Unlike other software delivery models, it separates "the possession and ownership of software from its use". [3]
Frequently, cloud-native applications are built as a set of microservices that run in Open Container Initiative compliant containers, such as Containerd, and may be orchestrated in Kubernetes and managed and deployed using DevOps and Git CI workflows [8] (although there is a large amount of competing open source that supports cloud-native ...
Platform as a service (PaaS) or application platform as a service (aPaaS) or platform-based service is a cloud computing service model where users provision, instantiate, run and manage a modular bundle of a computing platform and applications, without the complexity of building and maintaining the infrastructure associated with developing and launching application(s), and to allow developers ...
Engineers use containerization tools to package the model and create consistent environments for deployment, ensuring seamless integration across cloud-based or on-premise systems. Whether starting from scratch or using pre-trained models, the integration phase requires ensuring that the model is ready to scale and perform efficiently within ...
Continuous delivery is enabled through the deployment pipeline. The purpose of the deployment pipeline has three components: visibility, feedback, and continually deploy. [7] Visibility – All aspects of the delivery system including building, deploying, testing, and releasing are visible to every member of the team to promote collaboration.
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