Unlocking Insights From Multimodal Data for IT Automation

As IT systems become increasingly mission-critical, businesses must ensure continuous access to their systems to maintain seamless IT operations. Automating problem detection, resolution, and prevention is essential for smooth operations. IT Automation helps engineers automate and streamline operational workflows with little to no human intervention. IT automation monitoring generates a multivariate time-series, capturing spatial and topological relationships within an application's services. Effectively leveraging this multi-modal time-series data requires creating a holistic representation that integrates temporal and spatial aspects, along with their correlations and dependencies. This unified approach enables various IT applications, including anomaly detection, early incident prediction, and root cause analysis. This tutorial will provide a comprehensive understanding of multimodal data, focusing on its integration and representation to enhance IT automation tasks and drive proactive operations. Participants will gain insights into the latest advancements in the field, including their strengths and limitations.

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Publication Details

Published
2025-06-23
DOI
https://doi.org/10.1145/3696630.3728620
Primary Topic
Software System Performance and Reliability
Type
article
Field-Weighted Citation Impact
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article

Unlocking Insights From Multimodal Data for IT Automation

Prateeti Mohapatra, Seema Nagar, Atri Mandal
Software System Performance and Reliability
article

Unlocking Insights From Multimodal Data for IT Automation

Prateeti Mohapatra, Seema Nagar, Atri Mandal
article en

Abstract

As IT systems become increasingly mission-critical, businesses must ensure continuous access to their systems to maintain seamless IT operations. Automating problem detection, resolution, and prevention is essential for smooth operations. IT Automation helps engineers automate and streamline operational workflows with little to no human intervention. IT automation monitoring generates a multivariate time-series, capturing spatial and topological relationships within an application's services. Effectively leveraging this multi-modal time-series data requires creating a holistic representation that integrates temporal and spatial aspects, along with their correlations and dependencies. This unified approach enables various IT applications, including anomaly detection, early incident prediction, and root cause analysis. This tutorial will provide a comprehensive understanding of multimodal data, focusing on its integration and representation to enhance IT automation tasks and drive proactive operations. Participants will gain insights into the latest advancements in the field, including their strengths and limitations.

Centre for Air Borne System (IN), IBM Research - India (IN)
Industry, innovation and infrastructure
Openalex Percentile: Top 80%
Software System Performance and Reliability
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