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Ona Terminal CLI Deployment

Complete deployment guide for the Ona Terminal CLI tool and related services.

Overview

This guide covers deploying the Ona Terminal CLI tool and its supporting infrastructure. The Ona Terminal is an AI-powered command-line interface for energy asset management, forecasting, and automation.

Current Production State

Last Verified: 2025-01-10 (Status: PRODUCTION VERIFIED - Version 1.6.0)

Regional Architecture Overview

af-south-1 (Primary Production) - ✅ ACTIVE

Lambda Functions

The platform uses containerized Lambda functions for various services including:

API Gateway REST APIs

The platform uses AWS API Gateway to expose RESTful endpoints:

S3 Buckets

The platform uses S3 buckets for data storage:

DynamoDB Tables

The platform uses DynamoDB for metadata storage:

us-east-1 (Global Services) - ✅ ACTIVE

Lambda Functions (3 Deployed)

| Function Name | Purpose | Status | |—————|———|——–| | cloudwatch-monitoring-agent-api | CloudWatch monitoring | ✅ Active | | ona-front-end-prod-api-reques-RulePriorityFunction-* | ALB rules | ✅ Active | | ona-front-end-prod-api-reque-EnvControllerFunction-* | Environment control | ✅ Active |

Security Considerations

Best Practices

Before deploying to production, ensure you have:

  1. Secrets Management: Use AWS Secrets Manager or Parameter Store for sensitive configuration
  2. Security Scanning: Implement pre-commit security hooks and automated vulnerability scanning
  3. Access Control: Follow least-privilege access principles
  4. Monitoring: Set up security monitoring and alerting

Production Security

Service Coverage Analysis

Fully Deployed Services ✅ (95% Coverage)

Partially Deployed Services ⚠️ (40-60% Coverage)

Missing Services ❌ (0-20% Coverage)

Quick Start

Prerequisites

Development Installation

# Install Ona Terminal CLI
pip3.10 install ona-terminal

# Verify installation
ona --version

# Configure API key
ona configure --api-key YOUR_API_KEY

Production Installation

# Install with production dependencies
pip3.10 install ona-terminal[production]

# Set up environment variables
export ONA_API_KEY="your-production-api-key"
export ONA_REGION="af-south-1"
export ONA_ENVIRONMENT="production"

# Test connection
ona status

Docker Deployment

Local Development

# Build development image
docker build -f docker/Dockerfile.dev -t ona-terminal-dev .

# Run with volume mounting
docker run -it --rm \
  -v $(pwd):/app \
  -p 8000:8000 \
  -e ONA_API_KEY=your-dev-key \
  ona-terminal-dev

Production Docker

# Build production image
docker build -f docker/Dockerfile -t ona-terminal .

# Run production container
docker run -d \
  -p 8000:8000 \
  -e ONA_API_KEY=your-production-key \
  -e ONA_REGION=af-south-1 \
  --name ona-terminal-prod \
  ona-terminal

Docker Compose

# docker-compose.yml
version: '3.8'
services:
  ona-terminal:
    build: .
    ports:
      - "8000:8000"
    environment:
      - ONA_API_KEY=${ONA_API_KEY}
      - ONA_REGION=${ONA_REGION}
    volumes:
      - ./data:/app/data
    restart: unless-stopped

Systemd Service Deployment

Create Service File

# /etc/systemd/system/ona-terminal.service
[Unit]
Description=Ona Terminal CLI Service
After=network.target

[Service]
Type=simple
User=ona
WorkingDirectory=/opt/ona-terminal
Environment=ONA_API_KEY=your-api-key
Environment=ONA_REGION=af-south-1
ExecStart=/usr/local/bin/ona serve --host 0.0.0.0 --port 8000
Restart=always
RestartSec=10

[Install]
WantedBy=multi-user.target

Deploy Service

# Create user
sudo useradd -r -s /bin/false ona

# Create directory
sudo mkdir -p /opt/ona-terminal
sudo chown ona:ona /opt/ona-terminal

# Install service
sudo systemctl daemon-reload
sudo systemctl enable ona-terminal
sudo systemctl start ona-terminal

# Check status
sudo systemctl status ona-terminal

PolicyAnalyst LLM Deployment (AWS EC2)

Prerequisites

Step-by-Step Setup

# Update system
sudo apt update && sudo apt upgrade -y

# Install Python 3.10
sudo apt install -y python3.10 python3.10-pip python3.10-venv

# Install NVIDIA drivers
sudo apt install -y nvidia-driver-535

# Install CUDA toolkit
wget https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda_11.8.0_520.61.05_linux.run
sudo sh cuda_11.8.0_520.61.05_linux.run --silent --driver --toolkit --samples

# Set environment variables
echo 'export PATH=/usr/local/cuda-11.8/bin:$PATH' >> ~/.bashrc
echo 'export LD_LIBRARY_PATH=/usr/local/cuda-11.8/lib64:$LD_LIBRARY_PATH' >> ~/.bashrc
source ~/.bashrc

# Install vLLM and Ona Terminal
pip3.10 install vllm ona-terminal

# Test GPU
nvidia-smi
python3.10 -c "import torch; print(torch.cuda.is_available())"

Load Model

# Create model directory
mkdir -p /home/ubuntu/models
cd /home/ubuntu/models

# Download and load model
python3.10 -c "
from vllm import LLM
llm = LLM(model='mistralai/Mistral-7B-Instruct-v0.2', gpu_memory_utilization=0.9)
print('Model loaded successfully')
"

Monitoring and Logging

CloudWatch Integration

# Install CloudWatch agent
sudo apt install -y amazon-cloudwatch-agent

# Configure monitoring
sudo /opt/aws/amazon-cloudwatch-agent/bin/amazon-cloudwatch-agent-config-wizard

# Start agent
sudo systemctl enable amazon-cloudwatch-agent
sudo systemctl start amazon-cloudwatch-agent

Health Checks

# Check service health
curl http://localhost:8000/health

# Check API endpoints
curl -H "x-api-key: YOUR_API_KEY" \
  https://api.asoba.co/health

# Monitor logs
sudo journalctl -u ona-terminal -f

Security Considerations

Before Deployment

  1. Address Critical Security Issues:
    • Remove all hardcoded credentials
    • Fix 14 dependency vulnerabilities
    • Reduce wildcard imports from 950+ to <50
    • Implement AWS safety protocols
  2. Implement Secrets Management:
    • Use AWS Secrets Manager or Parameter Store
    • Rotate API keys regularly
    • Implement least-privilege access
  3. Security Scanning:
    • Set up pre-commit security hooks
    • Implement automated vulnerability scanning
    • Regular security audits

Production Security

Troubleshooting

Common Issues

API Connection Errors

# Check API key
ona configure --list

# Test API connectivity
curl -H "x-api-key: YOUR_API_KEY" \
  https://api.asoba.co/health

# Check AWS credentials
aws sts get-caller-identity

GPU Issues (PolicyAnalyst)

# Check NVIDIA drivers
nvidia-smi

# Check CUDA installation
nvcc --version

# Test PyTorch GPU
python3.10 -c "import torch; print(torch.cuda.is_available())"

Service Issues

# Check service status
sudo systemctl status ona-terminal

# View logs
sudo journalctl -u ona-terminal -f

# Restart service
sudo systemctl restart ona-terminal

Performance Issues

# Monitor system resources
htop
nvidia-smi  # For GPU monitoring
df -h       # Disk usage

# Check API performance
ab -n 100 -c 10 -H "x-api-key: YOUR_API_KEY" \
  https://api.asoba.co/health

Support

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