Considering the dynamic nature of new generation scientific problems, load balancing is a necessity to manage the load in an efficient manner. Load balancing systems are used to optimize the resource consumption, maximize the throughput, minimize response time, and to prevent overload in resources. In current research, we consider operational distributed systems with dynamic variables caused by different nature of the applications and heterogeneity of the various levels in the system. The conducted studies indicate that many different factors should be considered to select the load balancing algorithm, including the processing power, load transfer and communication delay of nodes. In this work, We aim to design a dashboard that is capable of merging the load balancing algorithms in different environments. We design an adaptive system infrastructure with the ability to adjust various factors in the run time of a load balancing algorithm. We propose a task and a resource allocation mechanism and further introduce a mathematical model of load balancing process in the system. We calculate a normalized hardware score that determines the maturity of the system according to the environmental conditions of the load balancing process. The evaluation results confirm that the proposed method performs well and reduces the probability of system failure.