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Mohamed K. - Fullstack Developer, Kubeflow, Machine Translation

My journey at Softaims has been defined by curiosity, growth, and collaboration. I’ve always believed that good software is not just built—it’s carefully shaped through understanding, exploration, and iteration. Every project I’ve worked on has taught me something new about how to balance simplicity with depth, and efficiency with creativity. At its core, my work revolves around helping businesses and people achieve more through thoughtful technology. I’ve learned that the most successful projects come from teams that communicate openly and stay adaptable. At Softaims, I’ve had the opportunity to work alongside professionals who challenge assumptions, share knowledge generously, and inspire continuous improvement. I take pride in focusing on the fundamentals—clarity in logic, consistency in design, and empathy in execution. Software is more than a set of features; it’s a reflection of how we think about problems and how we choose to solve them. By maintaining this perspective, I aim to build solutions that are not only effective today but also flexible enough to support the challenges of tomorrow. The culture at Softaims promotes learning as an ongoing process. Every new project feels like a step forward, both personally and professionally. I see each challenge as a chance to refine my skills and contribute to the shared vision of building technology that genuinely improves lives.

Main technologies

  • Fullstack Developer

    3 years

  • Kubernetes

    2 Years

  • Amazon Web Services

    2 Years

  • Terraform

    1 Year

Additional skills

  • Kubernetes
  • Amazon Web Services
  • Terraform
  • CI/CD
  • Docker
  • Jenkins
  • Ansible
  • Bash
  • CircleCI
  • Prometheus
  • Python
  • Automatic Speech Recognition
  • MLOps
  • Kubeflow
  • Machine Translation

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Potentially possible

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Experience Highlights

Build and deploy Laravel project on AWS EKS

requirements: • Implement docker to this repository • Implement GitLab CI/CD to this repository • Run sample tests on CI stage when MR is created. Make sure that failed test won’t allow MR to complete • GitLab CI/CD will deploy this repository to AWS EC2 using EKS and ECR when there is a merge to master branch • Add IAM user to AWS that has access to only EC2, EKS, and ECR. This user will be used by us to evaluate your work with AWS • Create documentation about how the CI/CD pipeline works and step by step how you finish the task and put it in the repository submission: Tools used: ⊠ Docker for building the image ⊠ Terraform IAAC ⊠ Kubernetes for hosting the application on ec2 instances ⊠ AWS cloud provider ⊠ EKS for managing kubernetes cluster ⊠ ECR for hosting the images (container registry) ⊠ GITLAB for CI/CD BonusFeatures: Docker image: • Secure with alpine based images for it being light (faster building) and have a smaller attack surface • Caching is used for even faster build (CI build took less than 2 minutes) Diagram • Run as nonroot Terraform • Use Terraform as IAAC to easily provision/destroy infra and benifit from IAAC. Kubernetes Role and Rolebinding • Instead of creating the cluster using the same user to access (which is not going to happen in real scenarios), created the cluster using another role and created the user with ability to do some actions including applying the deployment

CI-CD-using-CIrcleCI-AWS-CLOUDFORMATION-ANSIBLE-PROMETHEUS

Build CI/CD pipeline using circle ci and deploy using IAAC tool cloudformation on ec2 instances on AWS use Ansible as configuration management tool Monitor app using prometheus and alert manager Tools: Circle CI - Cloud-based CI/CD service Amazon AWS - Cloud services AWS CLI - Command-line tool for AWS CloudFormation - Infrastrcuture as code Ansible - Configuration management tool Prometheus - Monitoring tool

Terraform-Anbile-AWS-Jenkins

Using terraform to deploy 2 instances on AWS configuring them using ansible one to be used as jenkins and the other as webserver connecting jenkins to the webserver using ssh and deploying to it a docker container exposing a python application

blue-green deployment-Cloudformation-Kubernetes-Docker-EKS-Jenkins

1. create AWS EC2 instance and install Jenkins, docker on it 2. make IAM user with admin privilege and use it for the jenkins-aws connection 3. install dockerhub and AWS pipeline plugins on Jenkins and add their credentials 4. create aws cluster by running create-aws-eks-cluster.sh 5. run jenkinsfile which will build docker image and upload it to dockerhub and then create 2 stages blue and green deployment and run the blue deployment using blue-service which is a kubernetes loadbalancer pointing to the blue deployment using code selector=blue then check if the green environment is ready for being used if yes jenkins will run green-service which will point loadbalancer to the green deployment using code `selector=green'

Python_automation_scripts_online_store

You work for an online fruit store, and you need to develop a system that will update the catalog information with data provided by your suppliers. When each supplier has new products for your store, they give you an image and a description of each product. Given a bunch of images and descriptions of each of the new products: Upload the new products to your online store. Images and descriptions should be uploaded separately, using two different web endpoints. Since this process is key to your business's success, you need to make sure that it keeps running! So: Run a script on your web server to monitor system health. Send an email with an alert if the server is ever unhealthy.

Education

  • Ain Shams University

    Bachelor of Science in Information Technology in Faculty of Engineering Electronics and Communications department

    2014-01-01-2019-01-01

Languages

  • Arabic
  • English

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