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Cost estimation in software engineering is typically concerned with the financial spend on the effort to develop and test the software, this can also include requirements review, maintenance, training, managing and buying extra equipment, servers and software. Many methods have been developed for estimating software costs for a given project.
Kubernetes (/ ˌ k (j) uː b ər ˈ n ɛ t ɪ s,-ˈ n eɪ t ɪ s,-ˈ n eɪ t iː z,-ˈ n ɛ t iː z /, K8s) [3] is an open-source container orchestration system for automating software deployment, scaling, and management.
Microsoft Azure, or just Azure (/ˈæʒər, ˈeɪʒər/ AZH-ər, AY-zhər, UK also /ˈæzjʊər, ˈeɪzjʊər/ AZ-ure, AY-zure), [5] [6] [7] is the cloud computing platform developed by Microsoft. It has management, access and development of applications and services to individuals, companies, and governments through its global infrastructure.
In software engineering, containerization is operating-system–level virtualization or application-level virtualization over multiple network resources so that software applications can run in isolated user spaces called containers in any cloud or non-cloud environment, regardless of type or vendor. [1]
In 2017, CNCF also helped the Linux Foundation launch a free Kubernetes course on the EdX platform [104] — which has more than 88,000 enrollments. [105] The self-paced course covers the system architecture, the problems Kubernetes solves, and the model it uses to handle containerized deployments and scaling.
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Cost engineering is "the engineering practice devoted to the management of project cost, involving such activities as estimating, cost control, cost forecasting, investment appraisal and risk analysis". [1] "Cost Engineers budget, plan and monitor investment projects. They seek the optimum balance between cost, quality and time requirements." [2]
Following strong initial uptake, ABC lost ground in the 1990s compared to alternative metrics, such as Kaplan's balanced scorecard and economic value added.An independent 2008 report concluded that manually driven ABC was an inefficient use of resources: it was expensive and difficult to implement for small gains, and a poor value, and that alternative methods should be used. [4]