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Résumé
Serverless computing is a cloud computing execution model in which the cloud provider allocates machine resources on demand, taking care of the servers on behalf of their customers. "Serverless" is a misnomer in the sense that servers are still used by cloud service providers to execute code for developers. However, developers of serverless applications are not concerned with capacity planning, configuration, management, maintenance, fault tolerance, or scaling of containers, VMs, or physical servers. Serverless computing does not hold resources in volatile memory; computing is rather done in short bursts with the results persisted to storage. When an app is not in use, there are no computing resources allocated to the app. Pricing is based on the actual amount of resources consumed by an application. It can be a form of utility computing.
Serverless computing can simplify the process of deploying code into production. Serverless code can be used in conjunction with code deployed in traditional styles, such as microservices or monoliths. Alternatively, applications can be written to be purely serverless and use no provisioned servers at all. This should not be confused with computing or networking models that do not require an actual server to function, such as peer-to-peer (P2P).
Serverless vendors offer compute runtimes, also known as Function as a Service (FaaS) platforms, which execute application logic but do not store data. Common languages supported by serverless runtimes are Java, Python and PHP. Generally, the functions run under isolation boundaries, such as, Linux containers.
The first "pay as you go" code execution platform was Zimki, released in 2006, but it was not commercially successful. In 2008, Google released Google App Engine, which featured metered billing for applications that used a custom Python framework, but could not execute arbitrary code. PiCloud, released in 2010, offered FaaS support for Python.
Knative and Fission are two Open Source FaaS platforms which run with Kubernetes.
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