Hypervisor & Cloud Infrastructure Code Helper Agent

A specialized Claude agent designed to assist with hypervisor and cloud infrastructure programming tasks across AWS, Azure, and Google Cloud Platform.

Features

• Multi-Cloud Support: AWS, Azure, and GCP specific helpers
• Infrastructure as Code: Generate Terraform configurations, CloudFormation templates, ARM templates
• Code Generation: Create SDK examples, Lambda functions, Azure Functions, Cloud Functions
• Best Practices: Provides recommendations based on use cases
• Hypervisor Support: VMware, Hyper-V, KVM guidance

Quick Start

from hypervisor_agent import HypervisorAgent

# Initialize the agent
agent = HypervisorAgent()

# Get help with a specific query
result = agent.suggest_solution("How do I create a Terraform configuration for AWS EC2?", "aws")
print(result['recommendations'])
print(result['code_examples'][0])

Cloud-Specific Helpers

AWS Helper

from aws_helper import AWSHelper

aws = AWSHelper()

# Generate EC2 Terraform configuration
config = {
    'name': 'web_server',
    'instance_type': 't3.micro',
    'ami': 'ami-0abcdef1234567890'
}
terraform_code = aws.generate_terraform_ec2(config)

# Get service recommendations
recommendations = aws.get_service_recommendations('web_application')

# Generate boto3 examples
code = aws.generate_boto3_example('ec2', 'list_instances')

Azure Helper

from azure_helper import AzureHelper

azure = AzureHelper()

# Generate VM Terraform configuration
config = {
    'name': 'web_vm',
    'location': 'East US',
    'vm_size': 'Standard_B1s'
}
terraform_code = azure.generate_terraform_vm(config)

# Generate Azure SDK examples
code = azure.generate_azure_sdk_example('compute', 'list_vms')

GCP Helper

from gcp_helper import GCPHelper

gcp = GCPHelper()

# Generate Compute Engine Terraform
config = {
    'name': 'web_instance',
    'project_id': 'my-project',
    'machine_type': 'e2-micro'
}
terraform_code = gcp.generate_terraform_compute(config)

# Get gcloud commands
commands = gcp.get_gcloud_commands('compute')

Supported Use Cases

The agent provides specialized recommendations for:

• Web Applications: Load balancing, databases, static assets
• API Backends: Serverless functions, authentication, monitoring
• Data Processing: ETL pipelines, streaming, analytics
• Machine Learning: Training workflows, model serving
• Container Workloads: Kubernetes, container registries

Available Help Categories

1. Infrastructure as Code
2. Virtual Machine Management
3. Container Orchestration
4. Network Configuration
5. Storage Management
6. Security and Compliance
7. Monitoring and Logging
8. Cost Optimization
9. Migration Strategies

Code Generation Examples

Terraform EC2 Instance (AWS)

# AWS EC2 Instance Configuration
resource "aws_instance" "web_server" {
  ami           = "ami-0c55b159cbfafe1d0"
  instance_type = "t2.micro"
  key_name      = "my-key-pair"
  
  vpc_security_group_ids = [aws_security_group.web_server_sg.id]
  subnet_id              = "subnet-12345678"
  
  tags = {
    Name        = "Web Server"
    Environment = "production"
  }
}

Azure VM Terraform

# Azure Virtual Machine
resource "azurerm_linux_virtual_machine" "example" {
  name                = "example-vm"
  resource_group_name = azurerm_resource_group.example.name
  location            = azurerm_resource_group.example.location
  size                = "Standard_B1s"
  admin_username      = "adminuser"
}

GCP Compute Instance

# GCP Compute instance
resource "google_compute_instance" "example" {
  name         = "web-instance"
  machine_type = "e2-micro"
  zone         = "us-central1-a"
  
  boot_disk {
    initialize_params {
      image = "debian-cloud/debian-11"
    }
  }
}

Web Interface

The project includes a Flask web application that provides an interactive interface to the hypervisor agent.

Running the Web Application Locally

1. Install dependencies:

   pip install -r requirements.txt

2. Start the Flask development server:

   python app.py

3. Access the application: Open your browser and navigate to http://localhost:5000

Web Interface Features

• Interactive Query System: Ask questions about cloud infrastructure and get code examples
• Multi-Cloud Support: Switch between AWS, Azure, GCP, or auto-detect mode
• Code Generation: Get Terraform configurations, SDK examples, and CLI commands
• Best Practices: View security, performance, cost optimization, and reliability guidelines
• Template Library: Browse pre-built templates for common infrastructure patterns

Available Web Pages

• / - Home page with overview and navigation
• /query - Interactive query interface for asking questions
• /aws - AWS-specific helpers and examples
• /azure - Azure-specific helpers and examples
• /gcp - Google Cloud Platform helpers and examples
• /hypervisors - Hypervisor-specific guidance (VMware, Hyper-V, KVM)
• /best_practices - Cloud infrastructure best practices
• /sdk_examples - SDK code examples for all cloud providers
• /terraform - Terraform configuration templates

Testing

Run the simple test to verify functionality:

python simple_test.py

For comprehensive testing (requires fixing template issues):

python test_agent.py

Files Structure

• hypervisor_agent.py - Main agent class with multi-cloud support
• aws_helper.py - AWS-specific code generation and helpers
• azure_helper.py - Azure-specific code generation and helpers
• gcp_helper.py - GCP-specific code generation and helpers
• config.py - Configuration, templates, and best practices
• simple_test.py - Basic functionality test
• test_agent.py - Comprehensive test suite

Supported Cloud Services

AWS

• EC2, Lambda, ECS, EKS, S3, RDS, VPC, CloudFront, Route53

Azure

• Virtual Machines, Functions, AKS, Storage, SQL Database, VNet

GCP

• Compute Engine, Cloud Functions, GKE, Cloud Storage, Cloud SQL

Best Practices Integration

The agent includes built-in best practices for:

• Security: IAM roles, encryption, least privilege
• Performance: Right-sizing, auto-scaling, caching
• Cost Optimization: Reserved instances, lifecycle policies
• Reliability: Multi-AZ deployment, health checks, backups

Contributing

To extend the agent:

1. Add new cloud providers in the respective helper files
2. Update configuration templates in config.py
3. Add test cases in test_agent.py
4. Update this README with new capabilities

License

This project is provided as-is for educational and development purposes.