Xavier Duthil
Software Engineer at OVHcloud
Nantes, Pays de la Loire, France
Summary
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Rockstar🎓
Top SchoolXavier Duthil is a Software Engineer based in Nantes with 8 years’ experience building backend and operations tooling, primarily in Golang and Python. At OVHcloud he maintains and evolves their Managed Kubernetes service and has contributed notable fixes and OVH-specific enhancements to the widely used Kubernetes autoscaler, improving node-pool templating, concurrency safety, and API retry behavior. Previously he developed Go-based data acquisition backends and automated deployment tooling, bringing a strong automation and clean-code mindset to production systems. Trained as an engineer with a solid math background, he combines hands-on backend development with DevOps practices to deliver reliable, efficient infrastructure software.
9 years of coding experience
3 years of employment as a software developer
Analyste Programmeur, Ingénierie logicielle, Diplôme obtenu, Analyste Programmeur, Ingénierie logicielle, Diplôme obtenu at exia.CESI : Ecole d'Ingénieurs InformatiqueLicense 1, Mathématiques et informatique, Année validée, License 1, Mathématiques et informatique, Année validée at Université du HavreBac Scientifique, Spécialité Mathématiques, Mention Très Bien, Bac Scientifique, Spécialité Mathématiques, Mention Très Bien at Lycée Saint Joseph - Le Havre
French, English
Stackoverflow
1reputation
0reached
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Github Skills (12)
autoscaling10
kubernetes10
go10
api10
apidoc10
kubernetes-pods10
concurrency9
concurrent9
concurrent-programming9
docker8
error-handling8
dockers8
Programming languages (6)
Github contributions (5)
kubernetes/autoscaler
May 2022 - May 2022
Autoscaling components for Kubernetes
Role in this project:
Backend & DevOps Engineer
Backend & DevOps EngineerContributions:6 reviews, 1 commit, 5 PRs in 1 day
Contributions summary:Xavier primarily focused on addressing bugs and enhancing the OVHcloud integration within the Kubernetes autoscaler. Their work involved fixing issues related to node group scaling, handling of non-autoscaled node pools, and correcting resource allocation. They also introduced improvements to prevent concurrency issues in node deletion and added support for node pool templating to improve autoscaler functionality. Additionally, they implemented a retry mechanism for API calls to address potential issues with Canadian tenant deployments.
autoscalingkubernetes
ricoleabricot/harbor-operator
Jul 2020 - Aug 2020
Kubernetes operator for Harbor service components
Contributions:1 PR, 21 pushes, 4 branches in 13 days
kubernetes-operatorkubernetesoperatorharbor
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