## 6 Conclusions and Future Work  
In the current study, computational metrics such as CPU, disk reading speed, disk writing speed, memory, network reception, and transmission are evaluated for comparing a web application in a monolithic architecture versus the same application using microservices. The mathematical model based on the Non-Parametric Regression Method was applied to validate these studies' findings. Also, we could accurately validate the results and provide a quantitative technical interpretation. The architecture of microservices with containers proved to be more efficient. This gives rise to discussion topics and is part of the planning that leads to DevOps' use when time is a priority factor. Our findings indicate that using microservices with containers generally applied in demanding computer systems, at massive scale, and within high traffic allows jobs to be conducted independently hence faster than serialized processed. Containers were the methods used to encapsulate microservices, which simplified configuration. Since it is necessary to deploy the applications to be uploaded to the cloud, it is preferable to use containers and upload them instead of using virtual machines. Its purpose is feasible if the goal is to process a large number of requests in the shortest time possible, regardless of resource limitations and where scalability is a priority. We could also determine that both platforms (monolithic and micro-services) could be used for different purposes and different technological conditions. However, our study demonstrates more efficiency concerning hardware resources, cost reduction, and high productivity when using microservices. As future work, we plan to optimize a collaborative native monolithic tool by migrating it to microservices. With this, we intend to continue showing the strengths and weaknesses of each of these architectures. Also, we plan the extension of the design and implementation of a users and services management system that optimizes the creation and deployment of containers, using MongoDB as a back end deployed in a Docker container, developed in Node.js, managed in cluster mode for high availability, and works through HTTPS. To solve the overload problem, we will design and implement a load balancer, whose primary purpose will be to respond to requests that come from the management system. The balancer will reply to the management system, with the address URL of the container with the least amount of users connected to it. It will also communicate with each container, every time a user connects to one of them. A high transactional rate must characterize this load balancer. Also, it must be under the principle of microservices and operate independently. Besides, it must collect each node's status and the number of users per node. Finally, given the increase in cyber-attacks on microservices applications, we will design software solutions to increase these systems' information security. [PERSON] is the initiator of the project. _Conceptualization:_ [PERSON], [PERSON] and [PERSON] identified the theoretical constructs and the different elements. _Validation:_ [PERSON] and [PERSON] conducted the verification and validation that the system complies with the requirements and specifications. _Formal analysis:_ [PERSON], [PERSON] and [PERSON] developed such analysis. _Resources and funding:_ [PERSON] and [PERSON] obtained financial, and economic resources. _Writing--initial draft preparation:_ [PERSON] and [PERSON] edited the first deliverable draft of the manuscript. _Writing--review and editing:_ [PERSON] re-edited the paper and performed proofreading. _Supervision:_ [PERSON] and [PERSON] supervised the technical and scientific quality assurance of the study. All authors have read and agreed to the proposed version of the manuscript.