Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.

18 production-ready Claude Code plugins: git workflows, code review, spec-driven development, architecture patterns, resource optimization, and multi-LLM delegation. 142 skills, 109 commands, 47 agents.

Vue3 Gantt chart with powerful Resource View for task scheduling and resource planning.

⚡️ Transform AI/ML operations: Transparency, Control and Cost Optimization. ⚡️

A systems engineering simulator designed to optimize CPU scheduling and memory allocation. Built in C++, it demonstrates low-level resource management, algorithmic efficiency, and operating system principles. Focused on high-performance computing and hardware-software co-design.

A Kubernetes resource recommender that extends the API server to provide native suggestions.

🧟 Outsmart the apocalypse, one instance at a time.

Hospital database system built with Oracle APEX and SQL, featuring an interactive dashboard for real-time insights into patient distribution and doctor availability. Designed to optimize resource management and support hospital administration in data-driven decision-making.

MATLAB implementation of FairPlay - Fairness-driven Task Scheduling and Path Optimization in 6G Edge Networks

Smart Flight Crew Scheduling System

OptiPod is an open-source, Kubernetes-native operator that automatically rightsizes CPU and memory requests and limits for your workloads based on real-time and historical usage patterns.

Interactive Power BI analysis of 55,501+ patient records: demographics (age, gender, blood type), billing amounts, admission types, conditions, hospital load, and actionable insights for capacity planning and care delivery.

Detect wasteful Kubernetes autoscaling: analyze CPU vs pod metrics to optimize on-prem cluster costs and performance.

AI-powered Kubernetes resource optimization tool. Analyzes pod metrics and provides intelligent recommendations using GPT-4/Claude for cost reduction and performance improvement.

A leaf-based algo to optimize resources of cloud applications. Patterns of leaves can be used to decipher a nature-based resource optimization algorithm by analyzing the patterns in the leaves to determine the abundance and distribution of resources in a given area. The requirement of computing resources can be compared with requirement of a leaf.

Analyze historical Prometheus metrics to generate optimized Kubernetes resource recommendations. Supports multi-namespace scanning, Slack notifications, and generates both YAML patches and detailed reports for cost optimization.

CLI tool to analyze Azure resources and identify cost optimization opportunities with actionable recommendations

🚀 A Python repository showcasing optimization techniques for Machine Learning including LP, Newton's methods, LASSO, and convex optimization. 📈🐍

AI-powered Chief Operations Officer agent — the COO's right hand. Automates workflows, optimizes resource allocation, monitors operations in real-time, and drives operational excellence across the enterprise. Part of the YENSI AI Platform.

This script processes files within a project directory by minifying JavaScript files and copying other file types to a specified output directory. It leverages the Terser library for minification and tracks the size reduction achieved, reporting in kilobytes.