Literature Study on Operational Data Analytics Frameworks in Large-scale Computing Infrastructures
A new study maps frameworks for analyzing operational data in massive computing infrastructures handling zettabytes annually.
A team of researchers led by Shekhar Suman, Xiaoyu Chu, and Alexandru Iosup has published a comprehensive literature study on Operational Data Analytics (ODA) frameworks, crucial for managing the immense complexity of modern large-scale computing infrastructures. Published on arXiv, the paper addresses the challenge of managing systems that generate zettabytes of data annually, such as High-Performance Computing (HPC) clusters. The authors first identify the fundamental architectural pillars that enable ODA capabilities within these environments, which are essential for optimizing efficiency and addressing sustainability concerns through fine-grained monitoring.
The core contribution of the study is the proposal of a new, more holistic ODA framework. This framework is designed to match the various layers of a large-scale graph-processing distributed ecosystem, as proposed by Sherif Sak et al., and extends the functionalities of an existing novel framework by Netti et al. The researchers then compare their proposed holistic framework against other state-of-the-art ODA solutions analyzed in the literature to highlight its novelty and potential advantages.
To demonstrate the tangible value of advanced ODA, the study also highlights the significant operational efficiencies observed from implementing cutting-edge frameworks. By cataloging trending research and creating awareness of these efficiencies, the authors aim to spur more extensive investigation into this critical field. The work serves as a foundational map for developers and operators of massive computing systems who need to harness operational data to improve performance, reliability, and manageability.
- Proposes a new holistic ODA framework extending Netti et al.'s work to match layers of graph-processing ecosystems.
- Analyzes fundamental pillars of large-scale computing infrastructures that enable Operational Data Analytics (ODA) capabilities.
- Highlights significant operational efficiencies gained from implementing state-of-the-art ODA frameworks in HPC environments.
Why It Matters
As computing systems grow to handle zettabytes, efficient ODA frameworks are critical for managing complexity, optimizing performance, and ensuring sustainability.