Michaël Bertoni

• Renewal of CI/CD tools and processes for Skyweaver and Sequence platforms with Buildkit, Github Actions, Docker, Kubernetes and Pulumi.

• Implementation of platform monitoring with Grafana, Prometheus and Google Cloud Monitoring.

• First full time member of the Core Infra Squad (formerly known as Cloud team), leading Invafresh in its transition to become a SaaS provider.

• With empathy and patience, the role requires creating bridges between teams and educating them to Cloud concepts.

• Recommendations to implement non functional requirements (observability, performance, scalability, availability, security) for the components and business features within the products. Influencing product and development teams to improve the whole SDLC and product compliance with modern software and cloud engineering best practices.

• Using Azure services, Terraform, Packer, Ansible, Azure DevOps, Gitlab, Datadog, PowerShell, Bash; Design, deployment and supervision of application environments for Invafresh's FIM solution in a single‑tenant infrastructure.

• Management of a small team of 2 DevOps Engineers/SRE and mentor a Junior SRE which started as an intern. Management of contractors' work as well.

• Migration of existing on premise products to a SaaS model.

• Management of infrastructure change requests coming from internal teams to enable their work.

• Completed a TFS to Gitlab migration targeting Development and QA teams.

• Completed an Azure DevOps to Gitlab migration targeting Cloud team.

• Enabled deployment of infrastructure changes to 15+ environments from dev to prod in 20 minutes using Terraform and Gitlab CI.

• Through standardization and optimization of infrastructure, reduced monthly costs by 30%.

• Pushed new Agile practices and asynchronous framework to help the team adapt to a remote work culture.

• Unconventional Data Services team and Kinetix Team.

• CI/CD pipelines optimization with Azure DevOps, reduced execution time and cost, leveraging Docker caching feature and YAML pipelines.

• Full deployment of application environment on GCP with Azure DevOps: GCE, GAE, GKE, IAM, BigQuery, Storage, Secret Manager.

• Monitoring tools deployment: Stackdriver for GCP, Alerts and Insights for Azure, with Slack Alert ‑ Deployment of these tools with Terraform.

• Typescript development to make the backend executes CPU intensive tasks on GKE/AKS with Kubernetes Jobs through its API.

• IHS data pipeline (third party domain data ETL) optimization, debugging and monitoring with Apache Airflow / GCP Cloud Composer.

• Security: audit of vulnerable NPM packages, vulnerabilities in the code, pentesting with Veracode, hardening Docker/Kubernetes, dynamic retrieval of secrets from the API of a third party service (Azure Keyvault, Google Secret Manager).

• Better liveness / readiness check for services to increase accuracy of software availability.