AIOps 플랫폼 창업 사례 연구: 제이슨을 중심으로

AIOps (AI for IT Operations), which automates IT operations by utilizing big data analytics, machine learning and AI technologies, is gaining worldwide attention. The purpose of this study is to explore AIOps and discuss the future of AIOps platform through introducing the Jason company’s JMachine. This case study examines the future prospects of AIOps market, including the start-up and growth of Jason, the leader in AIOps platform, and JMachine's function. In first, we introduce Jason company and JMachine. Secondly, we analyze the core function of JMachine with comparing with other AIOps platform. Then, we compare with the traditional IT monitoring based on moogsoft’s AIOps event management procedure. Using the big data analysis and artificial intelligence technology, JMachine detects system anomalies or information leaks, analyze the problem symptoms, and then automatically provide actions without operator, focusing on the stages of detection, analysis, and response. This study provided customer customization, control flexibility, and product portfolio diversification for JMachine's success in the AIOps market. This study suggests that the AIOps platform can greatly contribute to maximizing and stabilizing the efficiency of IT operations. And it also describes the various scalability of AIOps, such as the protection of information leak, the detection of external intrusion. In addition, this case study introduces implications for IT operations practitioners and market challengers preparing to start their own businesses, who are constantly struggling to improve the efficiency of IT operations in the future.