The model and algorithms of decision-making on scaling cloud applications (ClAp) of the cloud-oriented educational environment of the university (CEE) are presented. The model allows you to find the execution time of a network request in the CEE. The model was implemented in the computing core – a decision support system for the need to scale the CEE of the CEE or the digital cloud environment (DCE) of the university. The computational core of the Adaptive Decision Support System (DSS) uses an evaluation function to analyze the scaling options of the DSS of the University's DCE. This makes it possible to obtain an economic assessment of the effectiveness of the ClAp, which is based on the cost of maintaining the infrastructure of the ClAp. Based on the information about the state of the DCE and the algorithms proposed in the article for the DSS, sets of rules for reactive scaling and evaluating the effectiveness of the university's DCE are formed. The proposed algorithms for adaptive DSS allow flexible decision-making on the scaling of the university's DCE cloud application. Adaptive DSS has been tested in a number of universities in Kazakhstan and Ukraine. Based on the test results, a conclusion was made about the operability of the proposed solutions.