Francesco Cheinasso
Software Engineer at Liqo
Turin, Piedmont, Italy
Summary
🤩
Rockstar🎓
Top SchoolFrancesco Cheinasso is a software engineer with 8 years of experience specializing in cloud-native and multi-cluster Kubernetes solutions, currently working at Cast AI and maintaining the open-source project Liqo. He has hands-on experience improving observability and CLI tooling—contributing status reporting, pod presentation refinements, and metrics exposure to liqoctl—helping dynamic interconnection across clusters. Previously a cloud engineer at ArubaKube, he now also teaches cloud programming at Politecnico di Torino, blending practical engineering with academic instruction. Graduating with top honors (110 cum laude) in computer engineering from Politecnico di Torino, he brings a strong academic foundation to production-grade distributed systems work.
8 years of coding experience
3 years of employment as a software developer
Laurea Magistrale LM in ingegneria informatica, 110 cum laude, Laurea Magistrale LM in ingegneria informatica, 110 cum laude at Politecnico di Torino
Stackoverflow
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2kreached
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Github Skills (17)
kubernetes10
command-line-interface10
kubernetes-pods10
command-line10
cli10
develop9
cluster-computing9
go9
clustering9
go-testing8
testing8
cloud-computing8
nftables6
netfilter6
networking6
Programming languages (5)
Github contributions (5)
liqotech/liqo
Mar 2022 - Nov 2022
Enable dynamic and seamless Kubernetes multi-cluster topologies
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 release, 446 reviews, 18 commits in 8 months
Contributions summary:Francesco primarily contributed to the `liqoctl` command-line tool, enhancing its functionality and information display. Their work involved adding status information to the `liqoctl status` command and modifying code related to the presentation of pod statuses, specifically focusing on deployment and daemonset information. The commits also included refactoring code for better maintainability and exposing wireguard metrics for monitoring. This suggests the user worked on improving observability and extending the tool's capabilities.
cloud-computingmulti-clusterclustersresource-sharingkubernetes-clusters
liqotech/liqo-resource-plugins
Nov 2022 - Jul 2024
Plugins to fine-tune the amount of resources shared by liqo
Contributions:3 reviews, 3 PRs, 2 pushes in 1 year 8 months
tunepythonfine-tunefine
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