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Google Cloud Platform is a part [8] of Google Cloud, which includes the Google Cloud Platform public cloud infrastructure, as well as Google Workspace (G Suite), enterprise versions of Android and ChromeOS, and application programming interfaces (APIs) for machine learning and enterprise mapping services.
Google Cloud Dataflow was announced in June, 2014 [3] and released to the general public as an open beta in April, 2015. [4] In January, 2016 Google donated the underlying SDK, the implementation of a local runner, and a set of IOs (data connectors) to access Google Cloud Platform data services to the Apache Software Foundation. [5]
Google Compute Engine Unit (GCEU), which is pronounced as GQ, is an abstraction of computing resources. According to Google, 2.75 GCEUs represent the minimum power of one logical core (a hardware hyper-thread) based on the Sandy Bridge platform. The GCEU was created by Anthony F. Voellm out of a need to compare the performance of virtual ...
Google Cloud offers blue–green deployment capabilities through Deployment Manager. By defining resources in a declarative format, Deployment Manager allows users to create, update, and delete resources as part of a blue–green deployment process.
The following practices can enhance productivity of CI/CD pipelines, especially in systems hosted in the cloud: [5] [6] [7] Number of Pipelines: Small teams can be more productive by having one repository and one pipeline. In contrast, larger organizations may have separate repositories and pipelines for each team or even separate repositories ...
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.
While deployment flowcharts can be drawn by hand using pen and paper, various software tools include functionality to construct the flowcharts on computer. These include products such as Microsoft Visio. [5] As with other process mapping techniques, deployment flowcharts require a certain degree of detail (and accuracy) to provide useful benefit.
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. [ 68 ]
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