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Schedule Interview NowMy name is Asad U. and I have over 3 years of experience in the tech industry. I specialize in the following technologies: DevOps, Amazon Web Services, Microsoft Azure, Google Cloud Platform, Docker, etc.. I hold a degree in Bachelor of Science (BS). Some of the notable projects I’ve worked on include: Edge Kubernetes Cluster on Raspberry Pi, Azure DevOps CI/CD for AI API with Docker, Automated Functional Testing Pipeline with PyTest & Azure, On-Premises Proxmox Cloud for Docker Compose VMs, Interactive BASH Script for SQL Backups, etc.. I am based in Lahore, Pakistan. I've successfully completed 6 projects while developing at Softaims.
I approach every technical challenge with a mindset geared toward engineering excellence and robust solution architecture. I thrive on translating complex business requirements into elegant, efficient, and maintainable outputs. My expertise lies in diagnosing and optimizing system performance, ensuring that the deliverables are fast, reliable, and future-proof.
The core of my work involves adopting best practices and a disciplined methodology, focusing on meticulous planning and thorough verification. I believe that sustainable solution development requires discipline and a deep commitment to quality from inception to deployment. At Softaims, I leverage these skills daily to build resilient systems that stand the test of time.
I am dedicated to making a tangible difference in client success. I prioritize clear communication and transparency throughout the development lifecycle to ensure every deliverable exceeds expectations.
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Techlogix
Built a Raspberry Pi-based Kubernetes cluster using K3s for edge computing. Deployed across four nodes, leveraging MicroSD cards for storage and a network switch for communication. The lightweight K3s setup optimized resource usage while enabling containerized workloads at the edge. This self-hosted cluster provided a scalable, low-power computing environment for edge applications, demonstrating the feasibility of Kubernetes on ARM-based devices in constrained environments.
Implemented a CI/CD pipeline using Azure Pipelines to automate the deployment of an AI-powered API on AWS EC2. The pipeline handled the entire Docker workflow, including building, tagging, and pushing images to AWS ECR. On deployment, it connected to pre-configured EC2 instances via SSH, pulling and running the latest containerized API version. This setup ensured seamless updates, reduced manual effort, and improved deployment reliability, streamlining the AI API release process with efficient automation.
Developed test automation pipelines using Azure Pipelines to streamline functional testing in CI/CD workflows. Integrated PyTest-based test suites written by developers to ensure software reliability. Configured the pipeline to generate HTML and CSV test reports, which were automatically uploaded to AWS S3 for easy access and analysis. This implementation enhanced testing efficiency and reporting visibility, reducing manual effort while ensuring consistent quality in software releases.
Designed and deployed an on-premises cloud using Proxmox VE, optimized for running Docker Compose-based virtual machines. Configured custom VMs to host containerized workloads efficiently while ensuring resource isolation and scalability. Integrated automated backups and monitoring for reliability. This setup provided a self-hosted alternative to cloud services, enabling full control over deployments while optimizing performance for containerized applications.
Developed an interactive BASH script to automate MS SQL database backups with AWS S3 integration. The script supports both manual execution and scheduled backups via cron jobs, ensuring data availability and reliability. It automates database export, compression, and secure transfer to S3, optimizing storage usage. Implemented real-time console output for process visibility and error handling. This solution streamlined backup management, reducing manual effort while ensuring efficient and consistent data protection.
Bachelor of Science (BS) in Artificial Intelligence
2019-01-01-2023-01-01