Cloud computing's auto-scaling feature allows it to adapt to clients’ changing needs in real time. Auto-scaling techniques regularly address two interconnected optimization challenges scheduling. The issue is deciding when and how to scale the resource in order to fulfill the service agreement (SLA). However, the unpredictability in Cloud performance constitutes a key cause of uncertainty in the execution of applications. In order to automatically scale resources to match client demands, we provide an auto scaling controller. With auto scaling, even when system knowledge is limited or nonexistent, resource adjustments may be made more efficiently through a mix of reinforcement learning and fuzzy logic control. The suggested auto scaling works, according to the experimental findings.