Browsing by Author "Tilles, Jan"

Serverless Computing aka Function as a Service is a cloud service model in which cloud provider manages computing resources and tenants deploy their code without knowing the details behind the underlying infrastructure. The promise of serverless is to drive the costs down so that a tenant pays only for the computing resources that it actually utilizes instead of paying for idle containers or virtual machines. In this thesis, we discuss that Serverless Computing does not always fulfill these requirements. For instance, some serverless frameworks keep certain resources, such as containers or functions, idle in order to reduce latency during function invocation. This may be particularly problematic in edge domains where computing power and resources are limited. In Function as a Service, the smallest unit of deployment is a function. These functions can be used, for example, to deploy traditional microservice-based applications. Serverless computing allows a tenant to run and scale functions with high availability. Serverless Computing also includes some tradeoffs: developers does not have so much of control over the underlying environment, testing of serverless functions is cumbersome, and commercial cloud service providers have a high degree of lock-in in their serverless technologies. A serverless application is stateless by its nature, and it runs in a stateless container that is event-triggered and managed by the cloud provider. A serverless application can access databases but, in general, state related to the function itself is not stored in files or databases. A number of commercial offerings and a wide range of open-source serverless frameworks are available. In this thesis, we present an overview of the different alternatives and show a qualitative comparison. We also show our benchmarking results with OpenFaaS running on an Kubernetes edge cloud (Raspberry Pi) based on algorithms typically utilized in machine learning.