Cookies Policy
The website need some cookies and similar means to function. If you permit us, we will use those means to collect data on your visits for aggregated statistics to improve our service. Find out More
Accept Reject
  • Menu
Interest
Topics
Details

Details

  • Name

    Tiago Costa Mendes
  • Role

    External Student
  • Since

    08th December 2021
001
Publications

2023

Unsupervised Online Event Ranking for IT Operations

Authors
Mendes, TC; Barata, AA; Pereira, M; Moreira, JM; Camacho, R; Sousa, RT;

Publication
Intelligent Data Engineering and Automated Learning - IDEAL 2023 - 24th International Conference, Évora, Portugal, November 22-24, 2023, Proceedings

Abstract
Keeping high service levels of a fast-growing number of servers is crucial and challenging for IT operations teams. Online monitoring systems trigger many occurrences that experts find hard to keep up with. In addition, most of the triggered warnings do not correspond to real, critical problems, making it difficult for technicians to know which to focus on and address in a timely manner. Outlier and concept drift detection techniques can be applied to multiple streams of readings related to server monitoring metrics, but they also generate many False Positives. Ranking algorithms can already prioritize relevant results in information retrieval and recommender systems. However, these approaches are supervised, making them inapplicable in event detection on data streams. We propose a framework that combines event aggregations and uses a customized clustering algorithm to score and rank alarms in the context of IT operations. To the best of our knowledge, this is the first unsupervised, online, high-dimensional approach to rank IT ops events and contributes to advancing knowledge about associated key concepts and challenges of this problem. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.