A Decision Model for Selecting Serverless Platforms

Serverless computing has revolutionized cloud computing by abstracting the management of underlying infrastructure. This paradigm shift allows developers to concentrate on developing and optimizing application logic rather than managing the complexities of servers. Platforms such as AWS Lambda and OpenWhisk are gaining widespread adoption by enabling organizations to execute code in response to events. However, selecting the right serverless platform becomes challenging for organizations with the increasing number of serverless platforms and their diverse features. Moreover, decision-makers often lack specialized expertise in each platform, compelling them to continuously adapt to the rapidly evolving information and frequent updates. Therefore, this study presents a decision model for the serverless platforms selection problem that systematically captures knowledge and key features required for selecting serverless platforms. The model was evaluated through five real-world case studies at different software development companies. It suggests and prioritizes more than one serverless platform based on the participants' requirements. Participants reported that the model offered valuable insights, significantly simplifying the selection process while reducing the time and costs associated with decision-making. Additionally, the model enables organizations to efficiently evaluate and select serverless platforms that align with their technical requirements and strategic objectives. It also provides a foundation of reusable insights for researchers addressing future challenges in serverless computing.