Sidi Mohammed Kaddour

Team STACK

Inria

Research engineer at Inria STACK

I design feedback-driven systems for the edge-to-cloud continuum, with a focus on observability, orchestration, and adaptive deployment.

Distributed Systems Observability Edge-to-Cloud Ansible Kubernetes Grid'5000

Explore projects Selected publications Open CV

Current work

At Inria, I am developing CoAnsible, an extension that brings coordination logic from Concerto into complex distributed deployments.

Technical focus

My work combines OpenTelemetry, Prometheus, Kubernetes, and Ansible to build measurable and adaptive systems.

Research scope

I work across runtime monitoring, feedback loops, resource-aware placement, and reproducible experiments on heterogeneous infrastructures.

Motto

“Fail, learn, adapt, repeat.”

You can start with my projects, publications, or CV below, then reach out through the contact links if you’d like to discuss research, engineering, or collaboration.

news

Sep 17, 2025	📰 Exciting News! I am honored to serve as Co-Web Chair for the 18th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2025) and the 12th IEEE/ACM International Conference on Big Data Computing, Applications, and Technologies (BDCAT 2025), which will be held in Nantes, France. Looking forward to contributing to the success of these conferences!

latest posts

Dec 01, 2024	Started a New Position at Inria
Dec 01, 2023	Feedback Mechanisms for Edge-to-Cloud Applications at IMT Atlantique

selected publications

Application level observability for adaptive Edge to Cloud continuum systems

Sidi Mohammed Kaddour, Baptiste Jonglez, and Daniel Balouek

In Proceedings of the 18th IEEE/ACM International Conference on Utility and Cloud Computing, 2026

Abs DOI

This paper introduces an application-level observability framework for adaptive Edge-to-Cloud systems. The approach integrates SLO-aware feedback loops and fine-grained monitoring using OpenTelemetry, Prometheus, and Kubernetes-based infrastructures. Experimental results show improved adaptability, scalability, and resilience under dynamic workloads and fault conditions.
Multi-provider capabilities in EnOSlib: driving distributed system experiments on the edge-to-cloud continuum

Baptiste Jonglez, Matthieu Simonin, Jolan Philippe, and 1 more author

In IFIP International Conference on Distributed Applications and Interoperable Systems, 2025

Abs

This paper extends EnOSlib with multi-provider capabilities to support experimental research across the edge-to-cloud continuum. The proposed enhancements enable seamless orchestration, reproducibility, and performance evaluation of distributed systems spanning heterogeneous infrastructures.
Proteus: Towards Intent-driven Automated Resource Management Framework for Edge Sensor Nodes

Shashikant Ilager, Daniel Balouek, Sidi Mohammed Kaddour, and 1 more author

In Proceedings of the 14th Workshop on AI and Scientific Computing at Scale using Flexible Computing Infrastructures, 2024

Abs

Proteus presents an intent-driven framework for automated resource management in edge sensor nodes. The framework translates high-level intents into low-level resource configurations, enabling adaptive, efficient, and scalable management of edge infrastructures.
Electricity consumption data analysis using various outlier detection methods

Sidi Mohammed Kaddour and Mohamed Lehsaini

International Journal of Software Science and Computational Intelligence (IJSSCI), 2021

Abs DOI

This paper investigates abnormal electricity consumption detection using several unsupervised outlier detection techniques. Isolation Forest, One-Class SVM, and K-means clustering are evaluated on real consumption data to identify unusual patterns. The results demonstrate the effectiveness of these methods in detecting energy anomalies and supporting better energy management.