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A Google Compute Engine instance is a virtual machine running on a Linux or Microsoft Windows configuration. Users can choose to modify the instances including customizing the hardware, OS, disk, and other configuration options.
Compute Engine – Infrastructure as a Service to run Microsoft Windows and Linux virtual machines. Google Kubernetes Engine (GKE) or GKE on-prem offered as part of Anthos platform [10] [11] – Containers as a Service based on Kubernetes. Cloud Functions – Functions as a Service to run event-driven code written in Node.js, Java, Python, or Go.
Apache Ignite is a distributed database management system for high-performance computing.. Apache Ignite's database uses RAM as the default storage and processing tier, thus, belonging to the class of in-memory computing platforms. [2]
In order to compete with the kingpin of that space, Amazon Web Services (AWS) and its Elastic Compute Cloud, Google has bolstered its platform with new features, including shared-core instances ...
Google Cloud Connect was a free cloud computing plug-in for Windows Microsoft Office 2003, 2007 and 2010 that can automatically store and synchronize any Microsoft Word document, PowerPoint presentation, or Excel spreadsheet to Google Docs in Google Docs or Microsoft Office formats. The Google Doc copy is automatically updated each time the ...
Google Slides is a presentation program and part of the free, web-based Google Docs suite offered by Google. Google Slides is available as a web application, mobile app for: Android, iOS, and as a desktop application on Google's ChromeOS. The app is compatible with Microsoft PowerPoint file formats. [5]
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]
Cycle Computing was founded in 2005. [1] Its original offerings were based around the HTCondor scheduler and focused on maximizing the effectiveness of internal resources. . Cycle Computing offered support for HTCondor as well as CycleServer, which provided metascheduling, reporting, and management tools for HTCondor resour
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