
Detail-oriented Software Developer with hands-on experience in AWS cloud infrastructure and Pystack, focusing on optimizing software performance and debugging. Proven track record in building scalable cloud solutions and automating deployments to enhance application reliability. Expertise in cloud technologies and software optimization techniques, contributing to improved performance, scalability, and fault tolerance. Strong analytical skills enable a proactive approach to identifying and resolving issues in distributed systems.
Cloud Technologies: AWS (EC2, S3, Lambda, RDS, CloudFormation, SNS, CloudWatch)
DevOps Tools: Jenkins, Docker, Kubernetes, AWS CodePipeline
Stack Analysis: Pystack (for stack trace analysis and performance optimization)
Programming Languages: Python, Java, Shell Scripting
Database Management: MySQL, PostgreSQL, AWS RDS
Automation & CI/CD: Terraform, Ansible, AWS CloudFormation
Monitoring & Logging: AWS CloudWatch, CloudTrail
Version Control: Git, GitHub, Bitbucket
Containerization: Docker, Kubernetes
Cloud computing, Debugging
SHIKAKU MASTER-AN AI BASED APPROACH
Used python programming and developed an ai-driven application to solve shikaku puzzles efficiently. Implemented a backtracking algorithm enhanced with heuristic optimization and machine learning techniques, achieving a 95% accuracy rate in puzzle-solving. Designed an intuitive user interface that allows real-time interaction and solution visualisation. The project improved computation speed significantly, making it a valuable tool for puzzle enthusiasts.
CLOUD-BASED APPLICATION DEPLOYMENT ON AWS
Tools/Technologies: AWS EC2, S3, Lambda, RDS, CloudFormation
Designed and deployed a highly available cloud architecture for a web application using AWS EC2 for computing, S3 for static storage, RDS for database management, and Lambda for serverless functions.
Utilized CloudFormation for infrastructure-as-code, automating the provisioning of cloud resources to support the application's scalability.Implemented automatic scaling using AWS Auto Scaling to ensure optimal performance during peak loads.
PYSTACK INTEGRATION FOR PERFORMANCE OPTIMIZATION
Tools/Technologies: Pystack, Python, Docker
Integrated Pystack into an existing Python-based web application to optimize stack traces, identify performance bottlenecks, and improve overall response times. Used Pystack to analyze runtime data, enhancing the application's performance by reducing memory usage and processing time by 20%. Developed Docker containers for the application, allowing seamless deployment on various environments and improving debugging efficiency.