###### Abstract  
Cloud computing is a rapidly growing paradigm which has evolved from having a monolithic to microservices architecture. The importance of cloud data centers has expanded dramatically in the previous decade, and they are now regarded as the backbone of the modern economy. Cloud-based microservices architecture is incorporated by firms such as Netflix, Twitter, eBay, Amazon, Hailo, Groupon, and Zalando. Such cloud computing arrangements deal with the parallel deployment of data-intensive workloads in real time. Moreover, commonly utilized cloud services such as the web and email require continuous operation without interruption. For that purpose, cloud service providers must optimize resource management, efficient energy usage, and carbon footprint reduction. This study presents a conceptual framework to manage the high amount of microservice execution while reducing response time, energy consumption, and execution costs. The proposed framework suggests four key agent services: (1) intelligent partitioning: responsible for microservice classification; (2) dynamic allocation: used for pre-execution distribution of microservices among containers and then makes decisions for dynamic allocation of microservices at runtime; (3) resource optimization: in charge of shifting workloads and ensuring optimal resource use; (4) mutation actions: these are based on procedures that will mutate the microservices based on cloud data center workloads. The suggested framework was partially evaluated using a custom-built simulation environment, which demonstrated its efficiency and potential for implementation in a cloud computing context. The findings show that the engrosment of suggested services can lead to a reduced number of network calls, lower energy consumption, and relatively reduced carbon dioxide emissions. cloud computing; virtual machine; containers; microservices; multicloud +
Footnote †: journal: Applied Sciences
Platform (GCP), IBM Cloud, and Kamatera. Elasticity, the pay-as-you-go model, and on-demand provisioning of resources are a few of the major cloud computing advantages [2]. Three major categories of the cloud service models are known as [1; 3; 4] Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS); refer to Figure 1.  
1. Software as a Service (SaaS): SaaS provides access to cloud-based software. Through web or API, the users access the software residing on the remote cloud network. In SaaS, the vendor manages most of the technical issues including data handling, storage, servers, etc. Therefore, the users do not have to spend more time installing, maintaining, and upgrading software. Some of the SaaS examples are Dropbox, Salesforce, GoToMeeting, Google Apps, etc. 2. Infrastructure as a Service (IaaS): In IaaS, the cloud computing vendors provide access to resources such as storage, computing resources, and networking. IaaS lets businesses purchase resources according to their needs/demands. Therefore, IaaS provides a flexible cloud computing model where clients have complete control over the infrastructure. As the whole infrastructure is based on the cloud, there will be no single point of failure. Some of the IaaS examples are Amazon Web Services (AWS), Microsoft Azure, Google Compute Engine (GCE), etc. 3. Platform as a Service (PaaS): PaaS provides a framework for the users (specifically developers) on which they can develop, manage, and deploy the applications. The users not only have access to computing and storage resources, but they also have access to a set of tools for application development, testing, security, backups, etc. PaaS has several advantages including scalability, high availability, and a cost-effective development and deployment platform. Some of the PaaS examples are Apache Stratos, AWS Elastic Beanstalk, Google App Engine, etc. In the last decade, large-scale, as well as small- to medium-sized, enterprises mostly shifted to cloud computing.