With the proliferation of IoT devices, there has been exponential growth in data generation, placing substantial demands on both cloud computing (CC) and internet infrastructure. CC, renowned for its scalability and virtual resource provisioning, is of paramount importance in e-commerce applications. However, the dynamic nature of IoT and cloud services introduces unique challenges, notably in the establishment of service-level agreements (SLAs) and the continuous monitoring of compliance. This paper presents a versatile framework for the adaptation of e-commerce applications to IoT and CC environments. It introduces a comprehensive set of metrics designed to support SLAs by enabling periodic resource assessments, ensuring alignment with service-level objectives (SLOs). This policy-driven approach seeks to automate resource management in the era of CC, thereby reducing the dependency on extensive human intervention in e-commerce applications. This paper culminates with a case study that demonstrates the practical utilization of metrics and policies in the management of cloud resources. Furthermore, it provides valuable insights into the resource requisites for deploying e-commerce applications within the realms of the IoT and CC. This holistic approach holds the potential to streamline the monitoring and administration of CC services, ultimately enhancing their efficiency and reliability.

The forecasting model used random forest algorithm. From the outcomes, it has been found that the regression models utilize basic linkage works and are exceptionally solid for forecast of COVID-19 cases in different countries as well as India. Current shared of worldwide COVID-19 confirmed case has been predicted by taking the world population and a comparatives study has been done on COVID-19 total cases growth for top 10 worst affected countries including US and excluding US. The ratio between confirmed cases vs. fatalities of COVID-19 is predicted and in the end a special study has been done on India where we have forecasted all the age groups affected by COVID-19 then we have extended our study to forecast the active, death and recovered cases especially in India and compared the situation with other countries.