Philippe Gressent

Objective: Implementation of GCP/Azure/Oracle Cloud in a move-to-cloud project. Technical Environment: Terraform, Ansible, Python, Gitlab, GCP (GKS, network), Azure (Subscription, Hub and Spoke), Palo Alto, F5, Infoblox, Oracle Cloud, Okta, API Management.

• - Use of Terraform for deployment and infrastructure as code implementation of clouds.

• - Development of Terraform modules for Azure and GCP with Fast Fabric.

• - Multicloud migration (Azure Office+History, GCP API+Data, Oracle Cloud).

• - Deployment of Terraform scripts in Oracle Cloud for network interconnection.

• - Azure Gitlab / Jenkins CI/CD deployment.

• - Deployment, configuration, and network supervision (Palo Alto, F5, Infoblox), MFA security with Okta.

◦ o Automated deployment of network configurations with Nautobot.

◦ o Ansible playbooks for network configurations, and Python scripts for deployment.

◦ o AI templates for generic deployment.

• - Project management for migration projects.

• - Hybrid network deployment to manage resilience and redundancy (GCP + On Premise).

• • Transformation

◦ o Refactoring of Azure cloud to implement a hub and spoke (Best Practice).

◦ o Securing access and management of the Azure cloud (RBAC, IAM).

◦ o Providing application and system technical support to developers and other business teams.

◦ o Writing resolution procedures and runbooks for knowledge capitalization.

◦ o Integration of AI services in Azure for use by innovation teams.

◦ o Redesign of the landing zone and governance (IAM, tagging, policies).

◦ o Implementation of "architecture round table" ceremonies.

• • Automation & CI/CD

◦ o Automation of deployment management and implementation of automatic referencing for CMDB.

◦ o Setting up and maintaining CI/CD pipelines (Jenkins, Maven) to deploy application and system components.

◦ o AI/CD deployment through the use of templates.

◦ o Developing orchestration and observability monitoring for effective tracking.

• • Industrialization of Data & ML use cases

◦ o Industrializing Data and ML use cases on data warehouses and data lakes.

◦ o Using pilot use cases to validate the target architecture before production.

◦ o Optimizing performance and automating monitoring for Data & ML pipelines in production.

◦ o Creation of building blocks and pipelines (Terraform) under GitLab. Cloud Security

◦ o Assistance in setting up and deploying CSPM and CPWD.

◦ o Securing access with RBAC deployment.

◦ o Review of user access by group (Read, User, Admin).

◦ o Use of groups for RBAC. POC/POV & Innovation

Objective: Plan for "Move to Cloud" to public clouds to close global datacenters.

- Application Referencing.

- Selection of migration plans (AWS 7R rule).

- Organization of the Site Plan.

- Writing of infrastructure/application migration specifications.

- Migration and integration monitoring.

- Multicloud migration (AWS, GCP, Azure)