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Google Cloud Platform is a part [7] 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.
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).
Kubernetes architecture diagram. Kubernetes defines a set of building blocks ("primitives") that collectively provide mechanisms that deploy, maintain, and scale applications based on CPU, memory [29] or custom metrics. [30] Kubernetes is loosely coupled and extensible to meet the needs of different workloads.
Google App Engine (also referred to as GAE or App Engine) is a cloud computing platform used as a service for developing and hosting web applications.Applications are sandboxed and run across multiple Google-managed servers. [2]
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 File System (GFS or GoogleFS, not to be confused with the GFS Linux file system) is a proprietary distributed file system developed by Google to provide efficient, reliable access to data using large clusters of commodity hardware. Google file system was replaced by Colossus in 2010.
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.
Cloud computing abstractions aim to simplify resource management, but leaky abstractions can expose underlying complexities. These variations in abstraction quality depend on the cloud vendor, service and architecture. Mitigating leaky abstractions requires users to understand the implementation details and limitations of the cloud services ...