Open source projects and contributions showcasing cloud architecture, AI integration, and scalable system design.
Explore my complete portfolio of open source projects, contributions, and experiments.
github.com/pragyakeshap →Latest and most active projects from my GitHub repository.
Repository: github.com/pragyakeshap/rtc-scale-demo
Demonstration project for scaling WebRTC applications in production environments. Features GPU-accelerated media processing, latency-based autoscaling on GKE, and real-time monitoring with Prometheus. Showcases best practices for handling real-time communication at scale with optimal performance and resource utilization.
Repository: github.com/pragyakeshap/AI-Augmented-Cyber-Lab
Interactive cybersecurity training environment augmented with AI capabilities. Provides hands-on labs for security testing, vulnerability assessment, and threat detection using AI-powered analysis. Designed for learning and practicing modern security techniques in a safe, containerized environment.
Repository: github.com/pragyakeshap/docker-lockbox-scripts
Collection of security-hardening scripts and utilities for Docker containers. Implements container isolation, secrets management, and security best practices. Helps developers build more secure containerized applications by automating common security configurations and providing ready-to-use security patterns.
Repository: github.com/pragyakeshap/docker-cpu-drift-demo
Demonstration and analysis of CPU resource drift in Docker containers over time. Provides tools to measure, monitor, and understand CPU allocation inconsistencies in containerized environments. Useful for performance tuning and understanding resource management behavior in production Docker deployments.
Repository: github.com/pragyakeshap/docker-gpu-drift-demo
Experimental project demonstrating GPU resource allocation drift in containerized ML/AI workloads. Explores GPU memory management, utilization patterns, and performance variations in Docker containers. Essential for understanding GPU resource behavior when running AI/ML models in production container environments.