A comparison between traditional and Serverless technologies in a microservices setting

• URL: http://arxiv.org/abs/2305.13933v1
• Date: Tue, 23 May 2023 10:56:28 GMT
• Title: A comparison between traditional and Serverless technologies in a microservices setting
• Authors: Juan Mera Men\'endez, Jose Emilio Labra Gayo, Enrique Riesgo Canal, Aitor Echevarr\'ia Fern\'andez
• Abstract summary: This study implements 9 prototypes of the same microservice application using different technologies. We use Amazon Web Services and start with an application that uses a more traditional deployment environment (Kubernetes) Migration to a serverless architecture is performed by combining and analysing the impact (both cost and performance) of the use of different technologies such as AWS ECS Fargate, AWS, DynamoDBDB.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Serverless technologies, also known as FaaS (Function as a Service), are promoted as solutions that provide dynamic scalability, speed of development, cost-per-consumption model, and the ability to focus on the code while taking attention away from the infrastructure that is managed by the vendor. A microservices architecture is defined by the interaction and management of the application state by several independent services, each with a well-defined domain. When implementing software architectures based on microservices, there are several decisions to take about the technologies and the possibility of adopting Serverless. In this study, we implement 9 prototypes of the same microservice application using different technologies. Some architectural decisions and their impact on the performance and cost of the result obtained are analysed. We use Amazon Web Services and start with an application that uses a more traditional deployment environment (Kubernetes) and migration to a serverless architecture is performed by combining and analysing the impact (both cost and performance) of the use of different technologies such as AWS ECS Fargate, AWS Lambda, DynamoDB or DocumentDB.

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