This research paper sets forward an autoscaler, called EPMA, (Elastic Platform for Microservice-based Applications). Its main objective corresponds to resource optimization. The basic contributions of EPMA are twofold. First, an analysis module that correctly detects and identifies the root cause of performance degradation while considering a cross-layer approach. The detected problems may be related to request issues such as a workload increase or a specific request consuming a lot of resources. Other problems related to container and VM (Virtual Machine) layers are also considered. Second, a planning module that considers the above detected problems and offers an optimized elasticity plan avoiding useless resource provisioning and thus permitting resource optimization. Thus, our planning module selects the appropriate microservices to which resources should be added as well as the optimized amount of resources that should be incorporated to correct the situation. Experimental results conducted on two concrete use cases revealed that EPMA autoscaler detects and identifies different problems generating the overload state and launching an optimized resource provisioning that reduces computing resources.
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