Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.
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Updated
Apr 24, 2025 - Python
Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.
17 production-ready Claude Code plugins: git workflows, code review, spec-driven development, architecture patterns, resource optimization, and multi-LLM delegation. 130 skills, 103 commands, 43 agents.
Vue3 Gantt chart with powerful Resource View for task scheduling and resource planning.
β‘οΈ Transform AI/ML operations: Transparency, Control and Cost Optimization. β‘οΈ
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.
π§ 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.
In modern telecommunications, Static Reservation is a crime. While some network nodes suffer from congestion, others hoard unused, Licenses, and Processing Power.The Network Godfather is a proactive Resource Orchestrator that transforms the network from a collection of rigid, over-provisioned nodes into a dynamic Liquid Resource Pool.
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.
π A Python repository showcasing optimization techniques for Machine Learning including LP, Newton's methods, LASSO, and convex optimization. ππ
CLI tool to analyze Azure resources and identify cost optimization opportunities with actionable recommendations
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.
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