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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2603.05241 |
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| _version_ | 1866914371940122624 |
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| author | Ranković, Tamara Rilak, Mateja Rakonjac, Janko Simić, Miloš |
| author_facet | Ranković, Tamara Rilak, Mateja Rakonjac, Janko Simić, Miloš |
| contents | Applications requiring real-time processing of large volumes of data have been the main driver for rethinking the traditional cloud, giving rise to novel cloud models. Distributed cloud (DC) is a model that allows users to dynamically create and dispose of strategically located ad-hoc clouds that contain resources best tailored to their needs. It is essential for this model to provide a high degree of observability for it to be viable in real-world scenarios. In this paper, we present the design and implementation of a monitoring system that collects metrics from DCs and makes them accessible to diverse clients. Agents running on nodes are responsible for collecting machine-, container-, and application-level metrics. During the health-check protocol, that data is transferred from the node to the DC's control plane running inside the cloud. There, it is persisted and served via multiple APIs, including a streaming API. Moreover, node metrics are aggregated for every DC in order to provide a more comprehensive view of the system's state. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_05241 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A monitoring system for collecting and aggregating metrics from distributed clouds Ranković, Tamara Rilak, Mateja Rakonjac, Janko Simić, Miloš Distributed, Parallel, and Cluster Computing Applications requiring real-time processing of large volumes of data have been the main driver for rethinking the traditional cloud, giving rise to novel cloud models. Distributed cloud (DC) is a model that allows users to dynamically create and dispose of strategically located ad-hoc clouds that contain resources best tailored to their needs. It is essential for this model to provide a high degree of observability for it to be viable in real-world scenarios. In this paper, we present the design and implementation of a monitoring system that collects metrics from DCs and makes them accessible to diverse clients. Agents running on nodes are responsible for collecting machine-, container-, and application-level metrics. During the health-check protocol, that data is transferred from the node to the DC's control plane running inside the cloud. There, it is persisted and served via multiple APIs, including a streaming API. Moreover, node metrics are aggregated for every DC in order to provide a more comprehensive view of the system's state. |
| title | A monitoring system for collecting and aggregating metrics from distributed clouds |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2603.05241 |