Performance Evaluation of Automated Multi-Service Deployment in Edge-Cloud Environments with the CODECO Toolkit
Georgios Koukis, Ioannis Dermentzis, Vassilis Tsaoussidis, Jan Lenke, Fabian Wolk, Daniel Uceda, Guillermo Sanchez, Miguel A. Puentes, Javier Serrano, Panagiotis Karamolegkos, Rute C. Sofia

TL;DR
This paper evaluates the CODECO toolkit, an open-source framework that improves multi-service container deployment automation in heterogeneous Edge-Cloud environments, demonstrating reduced manual effort and maintained performance.
Contribution
It introduces and empirically assesses CODECO, a novel framework that enhances Kubernetes-based multi-service deployment automation across diverse hardware platforms.
Findings
CODECO reduces manual deployment effort significantly.
It maintains competitive runtime performance.
The framework is effective across various hardware and Kubernetes distributions.
Abstract
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…
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Taxonomy
TopicsSoftware System Performance and Reliability · Cloud Computing and Resource Management · IoT and Edge/Fog Computing
