Virtualization is utilized by cloud computing to effectively supply resources. Virtual Machines (VMs) are requiring more and more bandwidth, but prior study has not adequately addressed the issue of both VM and bandwidth allocation. A combined strategy combining bandwidth distribution and virtual machines (VMs) is needed to effectively supply resources. Demand in real life is also unpredictable. Resource reservations are permitted by service suppliers. However, we employ stochastic programming to account for this risk into consideration due to risks associated with over- and under-provisioning. We use a scenario tree reduction method to condense the problem space in order to increase the tractability of the stochastic optimization while maintaining its effectiveness as a heuristic. We also conduct a sensitivity analysis to determine how sensitive our answer is to parameter variations. We are using a deterministic equivalent formulation to analyses past demand data and discover that our answer is both optimum and responsive to alterations in parameter values. Additionally, this research demonstrates how consumers and suppliers can both benefit from price sensitivity analysis to maximise cost effectiveness

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