AUTOMATING OPERATIONAL EXCELLENCE IN MULTI-CLOUD ENVIRONMENTS: A SCALABLE FRAMEWORK FOR REAL-TIME COST OPTIMIZATION
Abstract
As multi cloud environment matures and is adopted to be flexible and reduce the vendor lock in, the operational cost optimization becomes a real challenge. In this paper, we propose a scalable framework for automated execution of cost saving strategies, bandwidth optimization and scalability in multi cloud environments. We evaluated the framework over three main cloud platforms (AWS, Azure, Google Cloud) and measure up to a 30% average decrease in cost. Under the high workloads, we improved the rates of resource utilization by 25% when compared to the baseline latency is still kept under 150ms. The system achieved a success rate of 98% demonstrating that it can capitalize on bringing operational cost down while performance is kept very high. Results show the possible promise for automating frameworks in helping operational efficiency in dynamic cloud environments, and the very path to sustainable and cost effective multi cloud management. The system performed very well with a success rate of 98%, demonstrating the capability to decrease operational cost while maintaining high performance. The results finally show the promise of such automated frameworks to benefit dynamic cloud environments in improving operational efficiency, thus resulting in sustainable and cost effective multi cloud management.
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