Serverless Computing Platform

Context:
- It can simplify System Operations.
- It can be used to create a Serverless Application (that runs in stateless compute containers that are event-triggered, ephemeral - may last for one invocation, and fully managed by the cloud provider).
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Example(s):
- a Function as a Service (FaaS), such as: AWS Lambda, Azure Functions, and Google Cloud Functions.
- a Containers as a Service (CaaS), such as: GCP Cloud Run and AWS Fargate.
- AWS DynamoDB.
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Counter-Example(s):
- a Microservices-based Application.
See: Microservice, Execution Model, Utility Computing, Peer-to-Peer, Cloud-Computing, Utility Computing, Microservices, Server (Computing), Horoku.

References

(Wikipedia, 2019) ⇒ https://en.wikipedia.org/wiki/Serverless_computing Retrieved:2019-11-15.
- Serverless computing is a cloud-computing execution model in which the cloud provider runs the server, and dynamically manages the allocation of machine resources. Pricing is based on the actual amount of resources consumed by an application, rather than on pre-purchased units of capacity. It can be a form of utility computing.
  Serverless computing can simplify the process of deploying code into production. Scaling, capacity planning and maintenance operations may be hidden from the developer or operator. Serverless code can be used in conjunction with code deployed in traditional styles, such as microservices. 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, like peer-to-peer (P2P).

https://hackernoon.com/what-is-serverless-architecture-what-are-its-pros-and-cons-cc4b804022e9
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