Performance Evaluation of Automated Multi-Service Deployment in Edge-Cloud Environments with the CODECO Toolkit

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 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.