🚀 Power Your NRAI Instance

Discover the optimal hardware configuration for your intelligent automation needs. NRAI’s adaptive architecture scales seamlessly from development to enterprise-grade deployments.

🎯 Smart Resource Planning

NRAI’s revolutionary architecture prioritizes memory efficiency over raw CPU power, utilizing intelligent caching and predictive resource allocation to maximize performance per dollar spent.

🏠 Development Setup
🏢 Production Ready
🌐 Enterprise Scale

Perfect for testing, prototyping, and small-scale automation projects.

Minimum Configuration

Service	Memory	CPU	Storage	Purpose
NRAI Core	2 GB	1 vCPU	20 GB SSD	Main application engine
PostgreSQL	512 MB	0.5 vCPU	10 GB SSD	Data persistence
Redis	256 MB	0.5 vCPU	2 GB SSD	Job queue & caching

💡 Pro Tip: This configuration handles up to 100,000 workflow executions per month with excellent response times.

Designed for business-critical workflows with high availability requirements.

Recommended Configuration

Service	Memory	CPU	Storage	Purpose
NRAI Core	8 GB	2 vCPU	100 GB SSD	Enhanced processing power
PostgreSQL	4 GB	2 vCPU	200 GB SSD	Optimized database performance
Redis	2 GB	1 vCPU	20 GB SSD	High-speed job processing

🎯 Performance Target: Handles 5+ million executions monthly with sub-second response times.

Maximum performance for large organizations with complex automation needs.

High-Performance Configuration

Service	Memory	CPU	Storage	Purpose
NRAI Core	16 GB	4 vCPU	500 GB NVMe	Maximum throughput
PostgreSQL	8 GB	4 vCPU	1 TB NVMe	Enterprise database
Redis	4 GB	2 vCPU	100 GB NVMe	Ultra-fast job queue

⚡ Enterprise Power: Processes 50+ million executions monthly with guaranteed 99.9% uptime.

🧠 Intelligent Scaling Strategies

Dynamic Resource Allocation

NRAI’s AI-powered resource management automatically adjusts to your workload patterns:

🔍 Pattern Recognition

The system learns your workflow patterns and predicts resource needs before bottlenecks occur

⚡ Auto-Scaling

Resources scale up during peak times and down during quiet periods, optimizing costs

🎯 Load Balancing

Intelligent distribution of workloads across available resources for maximum efficiency

📊 Performance Optimization

Continuous monitoring and adjustment based on real-time performance metrics

Component-Specific Scaling

📈 Performance Benchmarks

Real-World Performance Data

🏃‍♂️ Execution Speed

Average Response Times:

Simple workflows: < 50ms
Complex integrations: < 500ms
AI-powered workflows: < 2s
Batch processing: 1000+ items/minute

📊 Throughput Capacity

Processing Volumes:

Development: 100K+ executions/month
Production: 5M+ executions/month
Enterprise: 50M+ executions/month
Peak burst: 10,000 concurrent jobs

Scaling Milestones

Monthly Executions	Recommended Setup	Expected Response Time	Cost Efficiency
0 - 100K	Development	< 100ms	⭐⭐⭐⭐⭐
100K - 1M	Production	< 200ms	⭐⭐⭐⭐
1M - 10M	Production+	< 300ms	⭐⭐⭐
10M+	Enterprise	< 500ms	⭐⭐

🔧 Advanced Configuration

Environment Variables for Performance

# Core Performance Settings
NRAI_MAX_MEMORY_USAGE=8192  # MB
NRAI_CPU_OPTIMIZATION=true
NRAI_CACHE_STRATEGY=intelligent

# Database Optimization
DB_CONNECTION_POOL_SIZE=20
DB_QUERY_TIMEOUT=30000
DB_STATEMENT_TIMEOUT=60000

# Redis Configuration
REDIS_MAX_CONNECTIONS=100
REDIS_COMMAND_TIMEOUT=5000
REDIS_RETRY_ATTEMPTS=3

# Monitoring & Observability
ENABLE_PERFORMANCE_METRICS=true
METRICS_COLLECTION_INTERVAL=60
LOG_PERFORMANCE_WARNINGS=true

Cloud Provider Recommendations

☁️ AWS
🌐 Google Cloud
🔷 Azure

Recommended Instance Types:

Development: t3.medium (2 vCPU, 4 GB RAM)
Production: m5.large (2 vCPU, 8 GB RAM)
Enterprise: m5.xlarge (4 vCPU, 16 GB RAM)

Storage Options:

Use gp3 volumes for cost-effective performance
Consider io2 for high-IOPS requirements
Enable EBS optimization for better throughput

Recommended Machine Types:

Development: e2-standard-2 (2 vCPU, 8 GB RAM)
Production: n2-standard-4 (4 vCPU, 16 GB RAM)
Enterprise: n2-standard-8 (8 vCPU, 32 GB RAM)

Storage Options:

Use SSD persistent disks for optimal performance
Enable automatic disk resizing
Consider regional persistent disks for HA

Recommended VM Sizes:

Development: Standard_B2s (2 vCPU, 4 GB RAM)
Production: Standard_D4s_v3 (4 vCPU, 16 GB RAM)
Enterprise: Standard_D8s_v3 (8 vCPU, 32 GB RAM)

Storage Options:

Use Premium SSD for production workloads
Enable accelerated networking
Consider availability zones for redundancy

🎯 Performance Monitoring

Key Metrics to Track

🚀 Response Time

Monitor average and 95th percentile response times for all workflow types

💾 Memory Usage

Track memory consumption patterns and identify potential leaks

🔄 Queue Depth

Monitor job queue sizes to prevent bottlenecks

📊 Pro Monitoring Tip: Set up alerts for response times > 1s, memory usage > 80%, and queue depth > 1000 jobs.

Get Started

Configuration

Architecture

System Requirements & Performance

🚀 Power Your NRAI Instance

🎯 Smart Resource Planning

Minimum Configuration

Recommended Configuration

High-Performance Configuration

🧠 Intelligent Scaling Strategies

Dynamic Resource Allocation

Component-Specific Scaling

📈 Performance Benchmarks

Real-World Performance Data

🏃‍♂️ Execution Speed

📊 Throughput Capacity

Scaling Milestones

🔧 Advanced Configuration

Environment Variables for Performance

Cloud Provider Recommendations

🎯 Performance Monitoring

Key Metrics to Track

🚀 Response Time

💾 Memory Usage

🔄 Queue Depth

🎯 Ready to Optimize Your NRAI Deployment?

Get Started

Configuration

Architecture

​🚀 Power Your NRAI Instance

​🎯 Smart Resource Planning

​Minimum Configuration

​Recommended Configuration

​High-Performance Configuration

​🧠 Intelligent Scaling Strategies

​Dynamic Resource Allocation

​Component-Specific Scaling

​📈 Performance Benchmarks

​Real-World Performance Data

🏃‍♂️ Execution Speed

📊 Throughput Capacity

​Scaling Milestones

​🔧 Advanced Configuration

​Environment Variables for Performance

​Cloud Provider Recommendations

​🎯 Performance Monitoring

​Key Metrics to Track

🚀 Response Time

💾 Memory Usage

🔄 Queue Depth

​🎯 Ready to Optimize Your NRAI Deployment?

🚀 Power Your NRAI Instance

🎯 Smart Resource Planning

Minimum Configuration

Recommended Configuration

High-Performance Configuration

🧠 Intelligent Scaling Strategies

Dynamic Resource Allocation

Component-Specific Scaling

📈 Performance Benchmarks

Real-World Performance Data

Scaling Milestones

🔧 Advanced Configuration

Environment Variables for Performance

Cloud Provider Recommendations

🎯 Performance Monitoring

Key Metrics to Track

🎯 Ready to Optimize Your NRAI Deployment?