ALB signifie Application Load Balancer.
Deployment from scratch of the solution Open E-Mobility Charging Station Management solutions created earlier with my
friends developed in NodeJS :
● Implementation of a Microservices Architecture for the E-Mobility Solution application ( Before Monolithe ) :
⠀⠀⠀ → Create Dockerfile to containerize the Microservices to deploy on Kubernetes
● Complete automation of infrastructure and application deployment :
⠀⠀⠀ → Code/Develop Terraform Infrastructure as code ( IaC ) with Terragrunt to automate deployment infrastructure in HA
and applications with providers hashicorps AWS / Modules
● Implement Operator Kubernetes in Ansible to have a better resilience
● 50% Reduction in application deployment Time using Helm Charts :
⠀⠀⠀ → Create and Code the Helm Chart to deploy app in HA on Kubernetes
● Improved code quality with the integration of quality tests and static code analysis in the CI/CD Pipeline:
⠀⠀⠀ → Put in place pipeline CI/CD with Argo Workflow & ArgoCD & Github Action
⠀⠀⠀ → Create yaml template for the build and the test of new features in Argo Workflow
⠀⠀⠀ → Create application file for ArgoCD to synchronize the deployment on the clusters
⠀⠀⠀ → Github Action to test the quality of the " code static code analysis " and Integration test
● Switch from ECR to Github Registry to centralize in github
● Proactive application performance monitoring using Prometheus and Grafana
⠀⠀⠀ → Deployment of Prometheus & Grafana,
⠀⠀⠀ → Create Dashboard and code queries for Metrics
● Optimizing resources and improving application Scalability by using Auto Scaling with HPA / Optimization code for web
socket / Replicas / put algorithm on load balancer
● Work closely with development teams to solve performance and scalability problems :
⠀⠀⠀ → CDN Cloud Front / Global Accelerator / Simulator to simulate + 10 000 charging station / ALB or NLB (depends ip
static or not, etc...) for each services / K6 to simule in each region the performance and retrieve all metrics in grafana
⠀⠀⠀ → Setup a Profiler for nodejs " Clinic JS " to optimize the code to have a better performance, Optimize the size of
Docker image
● Implemented a Resilience Architecture to have a good SLA
● Implementing a data backup and recovery strategy with AWS S3
⠀⠀⠀ → Automated backup and restore of application data
⠀⠀⠀ → Snapshot / PVC & PV MongoDB in HA
● Reduce infrastructure costs by 30% by optimizing resource utilization in Kubernetes
⠀⠀⠀ → Finops with spot and optimization cost with manages service of AWS (switch from tools consume a lot resource to
manages services)
● Secure the solution
⠀⠀⠀ → Attack DDOS with annotation ingress (rps) and manage services AWS
⠀⠀⠀ → Secret with Gihtub secret / Sops and Sealed Secrets
⠀⠀⠀ → Optimize the Security of docker image to deploy on kubernetes with more security (No Root, Distroless)
I'm proud to have contributed to the creation of Open E-Mobility Open Source Charging station management solutions
Deployment from scratch Supervison Platform E-Mobility Solution developed in NodeJS so :
● Successfully migrate the applications from ECS Fargate to Kubernetes EKS, resulting in improved scalability and
performance
● Reduced the size of Docker images by 30% and implemented security measures such as running containers as non-root
users and using distroless images, enhancing the overall security of the deployment
● Implemented Infrastructure as Code (IaC) using Terraform and Terragrunt, automating the deployment of infrastructure and
applications in a highly available environment
⠀⠀⠀ → Code/Develop Terraform for Infrastructure as code ( IaC ) with Terragrunt with Providers Hashicorps AWS / Modules
● Developed Helm Charts to deploy Microservices in a highly available configuration on Kubernetes, ensuring seamless
scalability and fault tolerance
● Implemented CI/CD pipeline using Argo Workflow, ArgoCD, and Github Actions, enabling automated testing, build, and
deployment of new features with improved efficiency and reliability
⠀⠀⠀ → Create yaml template for the build and the test of new features in Argo Workflow
⠀⠀⠀ → Create application file for ArgoCD to synchronize the deployment on the clusters
⠀⠀⠀ → Github Action to test the quality of the code " Static Code Analysis " and Integration Test
⠀⠀⠀ → Managed and maintained the CI/CD pipeline, ensuring smooth integration and deployment of code changes across
multiple environments
● Implemented Monitoring and logging solutions using Prometheus and Grafana, providing real-time visibility into the
performance and health of the infrastructure
⠀⠀⠀ → Deploy Prometheus & Grafana, create dashboard and code queries for metrics
● Optimized the deployment process by implementing Blue-Green deployments and canary releases, reducing downtime and
minimizing the impact of new releases on the production environment "Canary"
⠀⠀⠀ → Progressive deployment (weight)
● Scalability with HPA / Optimization code for web socket / Replicas / put algorithm on load balancer
● Resilience pod on node-group in different region (az) / Replicas / Snapshot / PVC & PV for MongoDB / Back up / Job / ALB
for each services
● Performance with CDN Cloud Front / Global Accelerator / Simulator to simulate + 10 000 charging station / ALB or NLB
(depends ip static or not, etc...) for each services / K6 to simule in each region the performance and retrieve all Metrics in
Grafana
⠀⠀⠀ → Setup a Profiler for NodeJS " Clinic JS " to optimize the code to have a better Performance
⠀⠀⠀ → Collaborated with the development team to optimize application performance, reducing response time by 40%
● Implement security best practices, including vulnerability scanning
⠀⠀⠀ → Put in place Sonarqube
⠀⠀⠀ → Scanning vulnerability of containers with Snyke
● Implemented automated scaling of infrastructure based on traffic patterns, resulting in cost savings of 20% on cloud
resources "Self Service" Finops
⠀⠀⠀ → Spot and Reserved by years
⠀⠀⠀ → Manages service of AWS (switch from tools consume a lot resource to manages services)
● Secure the solution
⠀⠀⠀ → Attack DDOS with annotation ingress (rps) and manage services AWS
⠀⠀⠀ → Secret with Gihtub Secret / Sealed Secrets / Sops and Secret Manager on AWS
● Developed and maintained documentation for infrastructure and deployment processes, facilitating knowledge sharing and
onboarding of new team members
● Led the implementation of a disaster recovery plan, ensuring business continuity in case of infrastructure failures
Successfully Migrated multiple applications and data to the Azure Cloud, resulting in improved scalability and cost
efficiency.
Automated deployment of applications on AKS, reducing deployment time by 50%.
Implementation of a monitoring and log management infrastructure, enabling proactive detection of problems and faster
resolution
Working with development teams to optimise application performance and reduce infrastructure costs by 30%.
Implementation of a data backup and recovery strategy, ensuring continuous availability of services
Training internal teams in DevOps best practice and cloud technologies, improving their expertise and productivity
Collaborated PAAS Data-Mesh on the cloud, enhancing data accessibility and security.
Implemented highly available infrastructure using AKS, Terraform, and Ansible, ensuring continuous availability of
applications.
Collaborated with cross-functional teams to integrate BI platforms on the cloud, enabling automatic deployment on both
internal PAAS and public clouds.
Collaborated with the team to implement and maintain OpenStack and OpenShift Platforms, enabling seamless deployment
and management of applications. :
Contributed to the continuous integration and continuous deployment (CI/CD) pipeline, streamlining the software
development and release process :
● Create a Tool in Python / Robot Framework and Flask to Automated the testing process for the QA team by developing a
Python tool using Robot Framework and Flask, resulting in a significant reduction in manual effort and improved efficiency.
● for QA Team to Automate the tests with
● Provisioned and managed development, staging, and pre-production environments for the developers, ensuring they had all
the necessary packages, languages, and libraries to deploy new features
● Optimized resource utilization in the data center by conducting a comprehensive inventory of server topology and updating
packages, languages, and libraries using Ansible Playbook.
HOBBIES
COMMUNICATION WITH CHARGING...