Operational analytics is the direction of research related to the analysis of the current state of computing processes and the prediction of the future in order to anticipate imbalances and take timely measures to stabilize a complex system. There are two relevant areas in ATLAS Distributed Computing that are currently in the focus of studies: end-user physics analysis including the forecast of samples of data popularity among users, and ranking of WLCG centers for user analysis tasks. Studies in these areas are non-trivial and require detailed knowledge of all boundary conditions, which may be numerous in large-scale distributed computing infrastructures. Forecasts of data popularity are impossible without the categorization of user tasks by their types (data transformation or physics analysis), which do not always appear on the surface but may induce noise, which introduces significant distortions for predictive analysis. Ranking the WLCG resources is also a challenging task as it is necessary to find a balance between the workload of the resource, its performance, the waiting time for jobs on it, as well as the volume of jobs that it processes. This is especially difficult in a heterogeneous computing environment, where legacy resources are used along with modern high-performance machines. We will look at these areas of research in detail and discuss what tools and methods we use in our work, demonstrating the results that we already have. The difficulties we face and how we solve them will also be described.
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