<p>Cloud computing offers various services to its users, ranging from infrastructure, and system development environments, to software as a service over the Internet. A cloud service provider should deliver its services swiftly to real-time applications, which demand fluctuating computational processing. Real-time stream computations are perennial, receiving processing requests unpredictably and requiring a fair amount of resources for their processing in a constrained timeframe. Such a dynamic nature of applications leads to resource elasticity at runtime. In a cloud resource hierarchy, multiple resources with different processing capabilities and costs exist. To optimally utilize them and ensure the uninterrupted availability of resources to the real-time processing requirements, it is required to scale the resources at each processing layer efficiently. This work proposed the multilevel elasticity framework in a cloud environment for processing real-time streaming applications and collectively optimizing the elasticity concern of multilevel resources while attaining service level agreements and quality of service parameters.</p>