MAS-H2: A Hierarchical Multi-Agent System for Holistic Cloud-Native Autoscaling
MAS-H2: A Hierarchical Multi-Agent System for Holistic Cloud-Native Autoscaling explores MAS-H2 is a hierarchical multi-agent system that proactively autoscales Kubernetes resources based on business policies, reducing resource waste and performance degradation.. Commercial viability score: 7/10 in Cloud Autoscaling.
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $9K - $13K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Builds On ThisMonoScale: Scaling Multi-Agent System with Monotonic ImprovementViability: 3.0
- Builds On ThisAGMARL-DKS: An Adaptive Graph-Enhanced Multi-Agent Reinforcement Learning for Dynamic Kubernetes SchedulingViability: 3.0
- Builds On ThisMulti-Agent Collaboration for Automated Design Exploration on High Performance Computing SystemsViability: 6.0
- Builds On ThisAgent Primitives: Reusable Latent Building Blocks for Multi-Agent SystemsViability: 5.0
- Builds On ThisSecurity Considerations for Multi-agent Systems