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| Main Authors: | , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.07621 |
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| _version_ | 1866914378669883392 |
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| author | Koukis, Georgios Dermentzis, Ioannis Tsaoussidis, Vassilis Lenke, Jan Wolk, Fabian Uceda, Daniel Sanchez, Guillermo Puentes, Miguel A. Serrano, Javier Karamolegkos, Panagiotis Sofia, Rute C. |
| author_facet | Koukis, Georgios Dermentzis, Ioannis Tsaoussidis, Vassilis Lenke, Jan Wolk, Fabian Uceda, Daniel Sanchez, Guillermo Puentes, Miguel A. Serrano, Javier Karamolegkos, Panagiotis Sofia, Rute C. |
| contents | Containerized microservices are widely adopted for latency-sensitive and compute-intensive applications, with Kubernetes (K8s) as the dominant orchestration platform. However, automating the deployment and management of multi-service applications remains challenging, particularly in heterogeneous Edge-Cloud environments. This paper evaluates the CODECO toolkit, an open-source framework designed to enhance container orchestration across distributed infrastructures. We compare CODECO with baseline K8s workflows using three key performance indicators: deployment time, level of manual intervention, and runtime performance with resource utilization. Experiments across diverse hardware platforms (ARM, AMD, RPi) and K8s distributions, including lightweight variants such as k3s, demonstrate that CODECO substantially reduces manual effort while maintaining competitive performance and acceptable overhead. These results validate CODECO as an effective solution for Edge-Cloud orchestration and highlight its potential to improve the flexibility and intelligence of K8s-based deployments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_07621 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Performance Evaluation of Automated Multi-Service Deployment in Edge-Cloud Environments with the CODECO Toolkit Koukis, Georgios Dermentzis, Ioannis Tsaoussidis, Vassilis Lenke, Jan Wolk, Fabian Uceda, Daniel Sanchez, Guillermo Puentes, Miguel A. Serrano, Javier Karamolegkos, Panagiotis Sofia, Rute C. Distributed, Parallel, and Cluster Computing Containerized microservices are widely adopted for latency-sensitive and compute-intensive applications, with Kubernetes (K8s) as the dominant orchestration platform. However, automating the deployment and management of multi-service applications remains challenging, particularly in heterogeneous Edge-Cloud environments. This paper evaluates the CODECO toolkit, an open-source framework designed to enhance container orchestration across distributed infrastructures. We compare CODECO with baseline K8s workflows using three key performance indicators: deployment time, level of manual intervention, and runtime performance with resource utilization. Experiments across diverse hardware platforms (ARM, AMD, RPi) and K8s distributions, including lightweight variants such as k3s, demonstrate that CODECO substantially reduces manual effort while maintaining competitive performance and acceptable overhead. These results validate CODECO as an effective solution for Edge-Cloud orchestration and highlight its potential to improve the flexibility and intelligence of K8s-based deployments. |
| title | Performance Evaluation of Automated Multi-Service Deployment in Edge-Cloud Environments with the CODECO Toolkit |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2603.07621 |