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Schedule Interview NowMy name is Ibrahim M. and I have over 1 years of experience in the tech industry. I specialize in the following technologies: Architecture, DevOps, Computing & Networking, Docker, Kubernetes. I hold a degree in Master of Science (MS). Some of the notable projects I’ve worked on include: Strengthening AWS Security to Prevent Breaches, Automated Deployment of Financial App, AWS Deployment & Security, Cloud Infrastructure Architecture, Migration from Elastic Beanstalk to AWS ECS, etc.. I am based in Fremont, United States. I've successfully completed 6 projects while developing at Softaims.
My expertise lies in deeply understanding and optimizing solution performance. I have a proven ability to profile systems, analyze data access methods, and implement caching strategies that dramatically reduce latency and improve responsiveness under load. I turn slow systems into high-speed performers.
I focus on writing highly efficient, clean, and well-documented code that minimizes resource consumption without sacrificing functionality. This dedication to efficiency is how I contribute measurable value to Softaims’ clients by reducing infrastructure costs and improving user satisfaction.
I approach every project with a critical eye for potential bottlenecks, proactively designing systems that are efficient from the ground up. I am committed to delivering software that sets the standard for speed and reliability.
Main technologies
1 year
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IBM
This project focuses on addressing a significant data breach within an AWS cloud infrastructure and implementing a comprehensive security strategy to prevent future incidents. The approach centers on reinforcing network security, improving access management, ensuring data encryption, and integrating automated vulnerability scanning into CI/CD pipelines. Key solutions implemented include the creation of a private VPC for resource isolation, secure IAM policies enforcing least privilege, data encryption both in transit and at rest.
This project demonstrates the automated deployment of a Python-based financial application using GitLab CI/CD, Docker, and AWS. The process ensures streamlined, secure, and scalable deployment with minimal downtime. AWS services like ECS and ECR were utilized to enhance performance, high availability, and cost efficiency. The solution automates the build, testing, and deployment phases, providing a reliable and efficient application delivery process.
The project involved deploying and managing scalable, secure cloud-based applications on AWS ECS using Docker and CloudFormation. AWS services were integrated for content moderation, media conversion, and security, with CI/CD pipelines automated for continuous development. MongoDB was hosted on MongoAtlas, and monitoring was handled through Grafana and CloudWatch. Security was ensured via AWS WAF, and environment variables were managed securely with AWS Secret Manager.
This architecture integrates AWS services and open-source tools for secure, scalable CI/CD, container orchestration, and monitoring. Developers commit code to a private repo, triggering Jenkins to build, test, and push Docker images. ArgoCD automates deployments to Kubernetes. Prometheus and Grafana monitor system health, while alerts notify issues. Key components include VPC, private subnets, RDS, ALB, WAF, CloudFront, and S3. VPN access and private subnets ensure security, providing a robust, automated environment for development and deployment.
The client needed to migrate their application from Elastic Beanstalk, which was causing instability and performance issues, to a more reliable and scalable solution. They required a seamless transition to AWS ECS, minimizing downtime during deployment. My task was to design and implement an automated deployment pipeline, ensure the application was containerized effectively, and utilize a blue-green deployment strategy to enable smooth rollouts and the ability to quickly revert changes if necessary. The goal was to enhance the application’s stability and prepare it for future scalability.
Master of Science (MS) in Computer science
2012-01-01-2016-01-01