The Support System for Anomaly Detection with Application in Mainframe Management Process Dominik STRZALKA a , Alicja GERKA a, 1 , Bartosz KOWAL a , Pawel KURAŚ a , Grzegorz LEOPOLD b , Michal LEWICZ b and Dawid JAWORSKI c a Department of Complex Systems, Rzeszów University of Technology, Al. Powstańców Warszawy 12, 35-959 Rzeszów, POLAND b Z-RAYS, Plac Andersa 7, 61-894 Poznań, POLAND c Department of Mathematical Modelling, Rzeszów University of Technology, Al. Powstańców Warszawy 12, 35-959 Rzeszów, POLAND Abstract. The process of mainframe machines managing and administration requires not only specialized expert knowledge based on many years of experience but also on appropriate tools provided by a machine performance management system, e.g. the Resource Measurement Facility (RMF). The aim of this paper is to show some preliminary results of Z-RAYS system construction that is built basing on machine learning (ML) techniques. It allows automatic detection of anomalies and generation of early warnings about some errors that can appear in the mainframe to support mainframe management process. Presented results are based on extensive simulations that were done basing on the IBM emulator. We focus on determining the degree of the metrics variability, the degree of the data repeatability in metrics, some approaches in metrics anomaly detection and solutions for event correlation detection in metrics. Keywords. Mainframe, anomaly detection, support system, machine learning, Z- RAYS 1. Introduction Mainframe (mainframe machines, big iron computers) are a class of computers used mainly by large organizations for critical applications like financial, statistical. Today, this term (name) is usually related to computers compatible with the IBM System/360 line introduced in 1965 [1]. There is no formal definition of a mainframe. Such machines run uninterrupted for very long periods of time and are used everywhere when the high availability is required because any downtime would be costly or even catastrophic. They can run in parallel different instances of operating systems thanks to the technique of virtual machines. They are not a supercomputer [1]. In this paper we focus on a series of preliminary studies and analyses to prepare: 1 Corresponding Author, Alicja Gerka, Department of Complex System, Rzeszów University of Technology, Al. Powstańców Warszawy 12, 35-959 Rzeszów, Poland; E-mail: a.gerka@prz.edu.pl. Modern Management based on Big Data II and Machine Learning and Intelligent Systems III A.J. Tallón-Ballesteros (Ed.) © 2021 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). doi:10.3233/FAIA210236 96