# From Facility to Application Sensor Data: Modular, Continuous and Holistic Monitoring with DCDB

arXiv: https://arxiv.org/abs/1906.07509 · HTML: https://mlsanity.com/paper/1906.07509/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Jun 2019.

## Built on by (most cited first, 1 of 1)

- [EPIC: Generative AI Platform for Accelerating HPC Operational Data Analytics](https://mlsanity.com/paper/2509.16212/) (2025)

## Abstract (arXiv)

Today's HPC installations are highly-complex systems, and their complexity will only increase as we move to exascale and beyond. At each layer, from facilities to systems, from runtimes to applications, a wide range of tuning decisions must be made in order to achieve efficient operation. This, however, requires systematic and continuous monitoring of system and user data. While many insular solutions exist, a system for holistic and facility-wide monitoring is still lacking in the current HPC ecosystem. In this paper we introduce DCDB, a comprehensive monitoring system capable of integrating data from all system levels. It is designed as a modular and highly-scalable framework based on a plugin infrastructure. All monitored data is aggregated at a distributed noSQL data store for analysis and cross-system correlation. We demonstrate the performance and scalability of DCDB, and describe two use cases in the area of energy management and characterization.