Architecture
Overview
Vistara Architecture

Vistara Architecture

Understanding the foundational architecture that powers Vistara's AI platform. Learn how Zara integrates with Vistara OS to create a comprehensive AI development ecosystem.

Platform Architecture

Vistara is built on a layered architecture that provides the infrastructure needed for AI agent execution, workflow automation, and scalable development.

Vistara OS Layer
AI Agent Runtime
Workflow Engine
Vistara Platform Architecture

Architecture Overview

Vistara's architecture is designed to provide a robust, scalable foundation for AI-powered applications. The platform consists of multiple layers that work together to enable efficient AI agent execution and workflow automation.

Core Platform Components

System Architecture Layers

Application Layer

  • AI Agents: Intelligent agents that can understand, reason, and act
  • Workflows: Automated business processes and task sequences
  • Development Tools: Integrated development environment and APIs
  • User Interface: Web-based dashboard and management console

Zara Platform Layer

  • Agent Runtime: Execution environment for AI agents
  • Workflow Engine: Workflow creation and execution engine
  • API Gateway: Unified API interface for external integration
  • Service Mesh: Inter-service communication and routing

Vistara OS Layer

  • Process Management: Process lifecycle and resource allocation
  • Memory Management: Dynamic memory allocation and optimization
  • File System: Virtual file system with persistent storage
  • Network Stack: Network protocols and security
  • Security Layer: Multi-layer security and isolation

Zara Platform Integration

Zara is built on top of Vistara OS and provides high-level abstractions for AI agent development and workflow automation.

Integration Architecture

Key Integration Points

  • Resource Management: Zara requests resources from Vistara OS
  • Process Isolation: Secure separation between different agents
  • Memory Allocation: Dynamic memory allocation for AI workloads
  • Network Access: Controlled network access for external services
  • Security: Multi-layer security with agent isolation

System Requirements

Hardware Requirements

  • CPU: Minimum 4 cores, recommended 8+ cores
  • Memory: Minimum 8GB RAM, recommended 16GB+ RAM
  • Storage: Minimum 50GB available space, SSD recommended
  • Network: Stable internet connection for external API access

Software Requirements

  • Operating System: Linux (Ubuntu 20.04+), macOS 12+, Windows 11+
  • Node.js: Version 18.0.0 or higher
  • Docker: Version 20.10+ for containerized deployments
  • Git: For version control and deployment

Environment Requirements

  • API Keys: OpenAI, market data, and other service API keys
  • Network Access: Access to external APIs and services
  • Security: Firewall and network security configuration
  • Monitoring: System monitoring and logging infrastructure

Getting Started

Quick Setup

# Clone Vistara platform
git clone https://github.com/vistara-labs/vistara.git
cd vistara
 
# Install dependencies
npm install
 
# Configure environment
cp .env.example .env
# Edit .env with your API keys and settings
 
# Start the platform
npm run start

Configuration

// config.js
module.exports = {
  platform: {
    name: 'Vistara',
    version: '1.0.0',
    environment: process.env.NODE_ENV || 'production'
  },
  
  vistara: {
    os: {
      maxProcesses: 100,
      memoryLimit: '16GB',
      cpuLimit: '8 cores'
    }
  },
  
  zara: {
    agents: {
      maxConcurrent: 50,
      memoryLimit: '2GB',
      timeout: '5m'
    },
    
    workflows: {
      maxConcurrent: 100,
      retryAttempts: 3,
      timeout: '10m'
    }
  }
}

Environment Variables

# Platform Configuration
VISTARA_PLATFORM_ENV=production
VISTARA_LOG_LEVEL=info
VISTARA_SECURITY_LEVEL=high
 
# API Keys
OPENAI_API_KEY=your_openai_api_key
MARKET_API_KEY=your_market_api_key
SLACK_WEBHOOK=your_slack_webhook
 
# Resource Limits
VISTARA_MAX_AGENTS=50
VISTARA_MAX_WORKFLOWS=100
VISTARA_MEMORY_LIMIT=16GB

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