> ## Documentation Index
> Fetch the complete documentation index at: https://arivu.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Implementation Guide

> Step-by-step analysis and deployment checklist for all platforms

This guide provides a comprehensive analysis of Arivu's architecture and a detailed checklist for deploying across different platforms.

## Architecture Analysis (A-Z)

### Backend Components

<AccordionGroup>
  <Accordion title="API Server" defaultOpen icon="server">
    **Technology**: FastAPI + Uvicorn
    **Port**: 8000 (configurable)
    **Requirements**:

    * Python 3.10+
    * \~512 MB RAM minimum
    * Async-capable runtime

    **Key Endpoints**:

    * POST `/api/chat` - Execute queries
    * GET `/api/health` - Health check
    * WebSocket `/ws/live` - Real-time updates
    * GET `/api/traces` - Pipeline traces
    * GET `/api/sessions` - Session history
  </Accordion>

  <Accordion title="Database Connectors" icon="database">
    **Supported Databases**:

    * PostgreSQL (primary)
    * MySQL
    * SQLite
    * Snowflake
    * Databricks

    **Connection Pool**: SQLAlchemy with psycopg2/pymysql
    **Requirements**:

    * Network access to database
    * Proper credentials/auth
    * \~10-50 MS latency to DB is acceptable
  </Accordion>

  <Accordion title="LLM Integration" icon="brain">
    **Supported Providers**:

    * OpenAI (GPT-4, GPT-4o)
    * Anthropic (Claude)
    * Groq (Mixtral, Llama)
    * DeepSeek
    * HuggingFace (via Replicate)
    * Ollama (local)

    **Requirements**:

    * API keys stored in secrets manager
    * Internet access to LLM endpoints
    * Rate limiting awareness
    * Cost monitoring
  </Accordion>

  <Accordion title="Memory Backend" icon="layers">
    **Options**:

    **SQLite**: Local file-based

    * File: `arivu.db`
    * Storage: Local filesystem or mounted volume
    * Performance: Excellent for \<100 concurrent users
    * Scaling: Poor for distributed deployment

    **Redis**: Distributed in-memory

    * URL: `redis://host:port/db`
    * Storage: In-memory with optional persistence
    * Performance: Excellent for high concurrency
    * Scaling: Excellent with Redis Cluster
  </Accordion>

  <Accordion title="Cache Layer" icon="zap">
    **Caching Strategy**:

    * HTTP response caching (ETag, Last-Modified)
    * Redis cache for query results (300s TTL)
    * Frontend browser cache (manifest caching)
    * CDN caching for static assets

    **Cache Keys**:

    * Semantic similarity on queries
    * Session ID + query hash
    * LLM model version
  </Accordion>

  <Accordion title="Background Jobs" icon="activity">
    **Current Implementation**:

    * Synchronous within request
    * Pipeline execution inline
    * No message queue (yet)

    **For Large-Scale**:

    * Celery + Redis for async tasks
    * Schema refresh as background job
    * Report generation queue
  </Accordion>

  <Accordion title="Security & Auth" icon="lock">
    **API Key Authentication**:

    * Header: `X-API-Key`
    * Validation on all endpoints
    * Environment: `ARIVU_API_KEY`

    **User Context**:

    * Session-per-user isolation
    * User ID in logs for audit
    * No build-in RBAC (extensible)

    **Database Credentials**:

    * Never in code
    * Secrets manager (AWS/Azure/etc)
    * Rotation ready
  </Accordion>
</AccordionGroup>

### Frontend Components

<AccordionGroup>
  <Accordion title="Next.js Application" defaultOpen icon="layout-grid">
    **Technology**: Next.js 15.5.9 + React 19
    **Build Output**: Static HTML/JS/CSS
    **Port**: 3000 (dev), served on prod port
    **Build Size**: \~2-3 MB (gzipped)

    **Key Pages**:

    * `/` - Dashboard home
    * `/connections` - Database connections
    * `/llms` - LLM provider config
    * `/traces` - Pipeline tracing
    * `/chat` - Interactive query builder
  </Accordion>

  <Accordion title="Component Library" icon="components">
    **UI Framework**: Radix UI + Tailwind CSS
    **Icons**: Lucide React
    **Charts**: Chart.js (via CrayonAI)
    **Tables**: TanStack React Table
    **Notifications**: Sonner toasts

    **Asset Size**:

    * HTML: \~150 KB
    * JavaScript: \~1.5 MB (bundled)
    * CSS: \~300 KB
    * Custom fonts: \~500 KB
  </Accordion>

  <Accordion title="API Communication" icon="network">
    **Base URL**:

    * Dev: `http://localhost:8000`
    * Prod: `/api` (same origin)

    **Integration Points**:

    * `/api/chat` - Query execution
    * `/api/connections` - DB management
    * `/api/llms` - LLM settings
    * `/api/traces` - Execution traces
    * `/api/export` - Data export

    **Request Pattern**:

    * JSON request/response
    * CORS handling for cross-origin
    * Error propagation to UI
  </Accordion>

  <Accordion title="State Management" icon="state">
    **Approach**: React hooks + Context API
    **Page State**:

    * Session ID persisted
    * User preferences in localStorage
    * Query results in React state
    * Real-time updates via WebSocket

    **Session Persistence**:

    * LocalStorage: Settings, preferences
    * URL params: Query context
    * Cookies: Authentication (if needed)
  </Accordion>

  <Accordion title="Performance Optimization" icon="fast-forward">
    **Code Splitting**:

    * Dynamic imports for route pages
    * Lazy loading for modals/dialogs

    **Image Optimization**:

    * Next.js Image component
    * Responsive srcset
    * WebP format support

    **Caching Strategy**:

    * Static pages: 30 days
    * Dynamic pages: 1 hour
    * Scripts: 1 year (with hash)
  </Accordion>
</AccordionGroup>

### Supporting Infrastructure

<AccordionGroup>
  <Accordion title="Load Balancing" icon="scaling">
    **For Backend**:

    * HTTP Health checks every 30s
    * Sticky sessions for WebSocket
    * Round-robin for stateless APIs

    **For Frontend**:

    * DNS-level (Route 53, Azure DNS)
    * CloudFront/CDN for static
    * Geo-routing if multi-region
  </Accordion>

  <Accordion title="Monitoring & Logging" icon="monitor">
    **What to Track**:

    * API latency (p50, p95, p99)
    * Error rates by endpoint
    * Database query performance
    * LLM token usage and cost
    * Memory usage growth
    * Cache hit ratios

    **Log Aggregation**:

    * Centralized logging (CloudWatch, Datadog)
    * Structured JSON logs
    * Request tracing across services
  </Accordion>

  <Accordion title="Backup & Disaster Recovery" icon="backup">
    **Database Backups**:

    * Automated daily backups (7-30 day retention)
    * Point-in-time recovery capability
    * Cross-region replication (optional)
    * Test restores weekly

    **Configuration Backups**:

    * Git version control for IaC
    * Secrets in encrypted storage
    * Database connection strings in vault
  </Accordion>

  <Accordion title="Networking" icon="network">
    **VPC/Network Setup**:

    * Public subnets for ALB/frontend
    * Private subnets for backend/database
    * NAT Gateway for outbound traffic
    * Security groups (least privilege)

    **DNS Configuration**:

    * Apex domain → CDN/LB
    * API subdomain → Backend
    * WebSocket endpoint → Backend (sticky)
  </Accordion>
</AccordionGroup>

## Deployment Scenario Comparison

### Scenario 1: Startup (0-1000 MAU)

<Columns cols={2}>
  <Card title="Recommended Platform" icon="rocket">
    Railway or Render
  </Card>

  <Card title="Estimated Cost" icon="dollar-sign">
    \$10-20/month
  </Card>
</Columns>

```
Frontend: Vercel (free tier)
Backend: Railway/Render ($5-10)
Database: Railway PostgreSQL ($5-10)
Memory: SQLite (local) or Redis add-on
```

### Scenario 2: Small Business (1000-10000 MAU)

<Columns cols={2}>
  <Card title="Recommended Platform" icon="trending-up">
    DigitalOcean App Platform
  </Card>

  <Card title="Estimated Cost" icon="dollar-sign">
    \$40-60/month
  </Card>
</Columns>

```
Frontend: Vercel Pro or DigitalOcean App
Backend: DigitalOcean App ($12)
Database: DigitalOcean Managed DB ($15)
Memory: DigitalOcean Redis ($15)
CDN: Included
```

### Scenario 3: Mid-Market (10000-100000 MAU)

<Columns cols={2}>
  <Card title="Recommended Platform" icon="building">
    AWS ECS or Azure App Service
  </Card>

  <Card title="Estimated Cost" icon="dollar-sign">
    \$100-200/month
  </Card>
</Columns>

```
Frontend: CloudFront + S3 ($10-15)
Backend: ECS Fargate 2x tasks ($50)
Database: RDS PostgreSQL ($40-60)
Memory: ElastiCache Redis ($20)
Monitoring: CloudWatch logs ($20)
```

### Scenario 4: Enterprise (100000+ MAU)

<Columns cols={2}>
  <Card title="Recommended Platform" icon="crown">
    AWS EKS or Azure AKS
  </Card>

  <Card title="Estimated Cost" icon="dollar-sign">
    \$300-500/month
  </Card>
</Columns>

```
Frontend: Multi-CDN, Route 53 geo-routing
Backend: EKS auto-scaling ($100-150)
Database: RDS Aurora Multi-AZ ($80-100)
Memory: ElastiCache Redis Cluster ($50)
Monitoring: Datadog/NewRelic ($50-100)
DR: Multi-region hot standby ($100+)
```

## Platform Decision Matrix

<Tabs>
  <Tab title="Quick Decision Tree">
    1. **Budget?**
       * \< \$20/month → Railway, Render
       * \$20-100/month → DigitalOcean, Heroku
       * > \$100/month → AWS, Azure

    2. **Complexity tolerance?**
       * Very low → Vercel + Railway
       * Low → DigitalOcean, Render
       * Medium → AWS ECS
       * High → AWS EKS, Azure AKS

    3. **Existing cloud provider?**
       * AWS user → ECS or EKS
       * Azure user → App Service or AKS
       * None → DigitalOcean, Railway
  </Tab>

  <Tab title="Matrix">
    | Factor      | Railway | DigitalOcean | AWS    | Azure |
    | ----------- | ------- | ------------ | ------ | ----- |
    | Price       | \$      | \$\$         | \$\$\$ | \$\$  |
    | Ease        | ⭐⭐⭐⭐⭐   | ⭐⭐⭐⭐         | ⭐⭐     | ⭐⭐⭐   |
    | Scalability | ⭐⭐⭐     | ⭐⭐⭐⭐         | ⭐⭐⭐⭐⭐  | ⭐⭐⭐⭐⭐ |
    | Control     | ⭐⭐⭐     | ⭐⭐⭐⭐         | ⭐⭐⭐⭐⭐  | ⭐⭐⭐⭐⭐ |
  </Tab>
</Tabs>

## Universal Deployment Checklist

<Steps>
  <Step title="Pre-Deployment">
    * [ ] Code review and testing complete
    * [ ] Environment variables documented
    * [ ] Database migration tested locally
    * [ ] Docker image builds successfully
    * [ ] All dependencies in requirements.txt
    * [ ] API keys secured (no hardcoded values)
    * [ ] Health check endpoints configured
    * [ ] Monitoring/logging configured
  </Step>

  <Step title="Infrastructure Setup">
    * [ ] VPC/networking created
    * [ ] Database provisioned and tested
    * [ ] Redis/cache provisioned
    * [ ] Secrets manager configured
    * [ ] SSL certificates ready
    * [ ] DNS records configured
    * [ ] Load balancer configured
    * [ ] Auto-scaling policies defined
  </Step>

  <Step title="Deployment">
    * [ ] Docker images built and pushed
    * [ ] Task definitions/manifests created
    * [ ] Environment variables set
    * [ ] Database migrations run
    * [ ] Initial deployment (canary or blue-green)
    * [ ] Smoke tests passing
    * [ ] Monitoring alerts triggered
    * [ ] Team notified
  </Step>

  <Step title="Post-Deployment">
    * [ ] Health checks all green
    * [ ] Log aggregation working
    * [ ] Metrics dashboards visible
    * [ ] Alerts tested
    * [ ] Backup verified
    * [ ] Performance baseline established
    * [ ] Documentation updated
    * [ ] Incident response plan ready
  </Step>

  <Step title="Optimization">
    * [ ] Monitor CPU/memory usage
    * [ ] Identify bottlenecks
    * [ ] Adjust auto-scaling thresholds
    * [ ] Optimize database queries
    * [ ] Tune cache TTLs
    * [ ] Review error logs
    * [ ] Plan capacity for next quarter
  </Step>
</Steps>

## Platform-Specific Checklists

<Tabs>
  <Tab title="AWS ECS">
    * [ ] VPC created with public/private subnets
    * [ ] RDS database created and tested
    * [ ] ElastiCache Redis cluster created
    * [ ] ECR repositories created
    * [ ] IAM roles and policies configured
    * [ ] ECS cluster created
    * [ ] CloudWatch log groups created
    * [ ] ALB created and configured
    * [ ] Auto Scaling group configured
    * [ ] Route 53 DNS configured
    * [ ] CloudFront distribution created (optional)
    * [ ] S3 buckets for logs/backups created
  </Tab>

  <Tab title="Azure App Service">
    * [ ] Resource Group created
    * [ ] App Service Plan sized appropriately
    * [ ] Web App created
    * [ ] Azure SQL Database created
    * [ ] Azure Cache for Redis created
    * [ ] Container Registry created
    * [ ] Container image uploaded
    * [ ] Key Vault created
    * [ ] Managed Identity enabled
    * [ ] Application Gateway configured
    * [ ] Auto-scaling rules defined
    * [ ] Application Insights enabled
  </Tab>

  <Tab title="DigitalOcean">
    * [ ] Droplet created (if VPS) or App Platform app
    * [ ] PostgreSQL database created
    * [ ] Redis cluster created
    * [ ] Container Registry created
    * [ ] Image built and pushed
    * [ ] Domain configured
    * [ ] SSL certificate activated
    * [ ] Firewall configured
    * [ ] Monitoring alerts setup
    * [ ] Backups configured
    * [ ] App Platform connected to GitHub
  </Tab>

  <Tab title="Heroku/Railway">
    * [ ] Project created
    * [ ] GitHub connected
    * [ ] PostgreSQL add-on provisioned
    * [ ] Redis add-on provisioned
    * [ ] Environment variables set
    * [ ] Procfile configured
    * [ ] Buildpack selected
    * [ ] Deploy triggers configured
    * [ ] Custom domain configured
    * [ ] SSL enabled
    * [ ] Logs configured
    * [ ] Auto-scaling enabled (if available)
  </Tab>
</Tabs>

## Success Criteria

After deployment, verify:

<Columns cols={3}>
  <Card title="Performance" icon="zap">
    * API p99 latency \< 2s
    * Frontend load \< 3s
    * 99.9% uptime
  </Card>

  <Card title="Reliability" icon="shield-check">
    * Health checks 100% green
    * Automatic failover working
    * Zero data loss
    * Backups tested
  </Card>

  <Card title="Security" icon="lock">
    * No hardcoded secrets
    * HTTPS everywhere
    * Access logs present
    * Encryption enabled
  </Card>
</Columns>

## Next Steps

1. **Choose Your Platform**: Review the options and select based on your scenario
2. **Follow Platform Guide**: Go to AWS, Azure, or Other Platforms section
3. **Test Locally First**: Use Docker Compose to test the full stack
4. **Use This Checklist**: Mark off items as you complete them
5. **Set Up Monitoring**: Don't skip logging and alerting
6. **Plan Scaling**: Know your growth strategy beforehand