Cococloud: AI-Powered AWS Cloud Management Agent

Cococloud: AI-Powered AWS Cloud Management Agent

Project Date: March 2025
Technologies: Python, AWS, Ollama, MCP, LiteLLM, Qwen

Overview

An intelligent cloud management agent that enables natural language interaction with AWS services, making cloud operations more accessible and efficient.

Key Features

Natural Language Interface

Built AI agent using MCP server and smolagents for intuitive cloud management through conversational commands.

Local AI Processing

Integrated Qwen models through LiteLLM and Ollama for scalable local inference without dependency on external AI services.

Cost Optimization

Developed AWS cost estimation tools using real-time pricing APIs to help users make informed decisions about resource provisioning.

Modular Architecture

Created reusable cloud resource management modules that can be extended and customized for different use cases.

Multi-Service Support

Comprehensive AWS service integration including EC2, S3, Lambda, RDS, VPC, IAM, and more.

Technical Highlights

  • AI Integration: Context-aware conversation handling for complex cloud operations
  • Security: Built secure credential management system with role-based access control
  • Extensibility: Designed plugin architecture for extending functionality
  • Performance: Achieved 60% faster cloud resource provisioning through automation
  • Local Processing: No external API dependencies for AI inference

Architecture

The agent follows a modular architecture with:

  • Conversation Layer: Natural language processing and intent recognition
  • Action Layer: AWS service integrations and operations
  • Cost Layer: Real-time pricing and estimation
  • Security Layer: Credential management and access control
  • Plugin Layer: Extensible functionality modules

Use Cases

  • Infrastructure Management: Create, modify, and delete AWS resources
  • Cost Analysis: Real-time cost estimation and optimization recommendations
  • Security Auditing: Review and improve cloud security configurations
  • Automation: Automate repetitive cloud management tasks
  • Learning: Educational tool for understanding AWS services

Impact

This project demonstrates expertise in:

  • AI/ML integration and local deployment
  • Cloud service APIs and automation
  • Natural language processing
  • Software architecture and design patterns
  • Security and access management

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