In recent times, cloud computing is attracting a lot of attention because of its' services such as servers, databases or software on premise. During the development
of an application of any type, scalability, flexibility and cost estimates must be considered in advance.
In this diploma thesis, we experimented with different methods for establishing an API service for using a pre-trained machine learning model, whereby we used use containers and technologies for container orchestration, test different cloud providers, and compare them to each other. We tried to estimate the costs of the establishment of a scalable sistem depending of infrastructure needed for achieving a satisfactory response time.
Despite Kubernetes being the most often used solution for container orchestration, we have shown that AWS ECS is a good alternative. On Heroku cloud platform, we don't have as much flexibility, however the establishment is very simple.
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