Automated Scalability in Cloud Computing Using AI Based Framework

Cloud computing has become exceedingly popular in the past few years, and everyone needs an automated solution. The traditional ways of resource management in the cloud world will not work and need to be more efficient. To use the AI techniques, researchers have proposed using ML algorithms to automate it dynamically with the cloud resources. Through extensive experimentation, we develop a full-fledged framework for applying AI to automate cloud scalability. Implementing this framework uses hybridized data collection, processing, and prediction algorithms to manage the dynamic resource demands of cloud-based applications optimally manage cloud-based applications dynamic resource demands. Using this historical data, the framework can train and update the prediction models, which are then used for real-time predictions of resource requirements. It also has self-healing properties to deal with faults when they occur and benefit from this. It also facilitates multi-cloud providers to provide changing assets as floating and versatile assets. It provides efficient utilization of resources, lower expenses and better application throughput. Though it helps avoid human handlers, it gives more efficient solutions for managing scalable resources in the cloud. In summary, the AI-based framework for on-the-fly scalability with cloud computing is a promising and cutting-edge method that allows applications in the cloud to optimize their resource usage while maintaining optimal performance at all times.