Microservices for a carrying hailing service system: management of cargo transports in real-time

Abstract

The work of this master thesis is encompassed in the project of a platform that serves to put in contact through mobiles apps customers who need a cargo transport service with drivers available to provide that service. In this sense, this system should be capable of finding hauliers or drivers who fit to the customers’ needs for the freight that they want to transport and close to their location. And for the drivers, this system should be able to show them the customer freight details so that they can decide whether they want to accept to perform the ride or not. Meanwhile, the company should be able to track the rides in all different stages until the freights are delivered, showing up-to-date information in real time and elaborating reports that add value to the business. The server application will use a Microservice Architecture to break the system functionalities into independent units providing services that comply with the system requirements. This allows us to decouple the business logic into components that can be maintained independently, giving huge flexibility and portability. In the case of availability, microservice resilience is a key issue, because if the failover, replication and monitoring are managed correctly, the microservice will have a high availability. So, the deployment environment is essential to support these features along with scalability. To get a high scalability, resource allocation is very important, being the load balancer the component in charge of this task, splitting microservice workload among system resources, and being responsible for managing infrastructure resources. Performance is very dependent on scalability, supposing that the microservices are well implemented, since a good allocation of resources is essential for not degrading the service when traffic pikes are received. The server application consists of two back-ends, the Realtime and Administration back-ends. This master thesis focuses on the development of the Realtime back-end. In the development and deployment of the Realtime back-end, we have used different technologies such as Azure Kubernetes, Docker, NodeJS, MongoDB, etc. The final result is promising, because we built an elastic solution that can be easily configured based on the system requirements without extra coding effort. The proposed architecture and deployment can easily be used for a low or high workload after user demand, making scalability one of the greatest benefits for a company that is starting with the platform and in the future may grow without too much effort for adapting the current software solution.