زنبور سبز مایل به سبز: پیمایش در چشم انداز بومی ابر

# SSH Access Configuration
- Restrict port 22 to specific IP ranges
- Implement strict SSH key-based authentication

# Web Service Ports
- HTTP (port 80): Frontend accessibility
- Custom API Port (port 3000): Backend service communication

ssh -i greenish-bee.pem ec2-user@your-ec2-ip
git clone greenish-bee github repo
cd your-project-folder

#!/bin/bash
# Automated Docker Deployment Script

# System Preparation
sudo yum update -y

# Docker Installation
sudo yum install -y docker
sudo systemctl start docker
sudo systemctl enable docker

# User Permission Configuration
sudo usermod -aG docker ec2-user

# Multi-Stage Build for Optimal Resource Utilization
FROM node:18-alpine AS build-stage
WORKDIR /app
COPY package.json ./
RUN npm install
COPY . .
RUN npm run build

FROM nginx:alpine
COPY --from=build-stage /app/build /usr/share/nginx/html
EXPOSE 80
CMD ["nginx", "-g", "daemon off;"]

FROM node:18-alpine
WORKDIR /app
COPY package.json ./
RUN npm install
COPY . .
EXPOSE 3000
CMD ["node", "server.js"]

#!/bin/bash
echo "🚀 Greenish Bee Deployment Automation"

# Version Control Integration
git pull origin main

# Build Processes
docker build -t greenish-bee-dashboard ./frontend
docker build -t greenish-bee-api ./backend

# Container Deployment
docker-compose up -d --build

import boto3
import psutil
import time
import json

class ResourceMonitor:
    def __init__(self, log_group='GreenishBeeLogs'):
        self.logs_client = boto3.client('logs')
        self.cloudwatch = boto3.client('cloudwatch')
        self.log_group = log_group

    def collect_comprehensive_metrics(self):
        return {
            'cpu_usage': psutil.cpu_percent(interval=1),
            'memory_usage': psutil.virtual_memory().percent,
            'disk_usage': psutil.disk_usage('/').percent,
            'network_sent': psutil.net_io_counters().bytes_sent,
            'network_recv': psutil.net_io_counters().bytes_recv
        }

    def log_and_alert_metrics(self, metrics):
        # CloudWatch Metric Submission
        self.cloudwatch.put_metric_data(
            Namespace='GreenishBeeMetrics',
            MetricData=[
                {
                    'MetricName': 'CPUUtilization',
                    'Value': metrics['cpu_usage']
                },
                {
                    'MetricName': 'MemoryUtilization',
                    'Value': metrics['memory_usage']
                }
            ]
        )

        # Potential Alert Mechanism
        self.trigger_alerts_if_needed(metrics)

#!/bin/bash
BACKUP_BUCKET="greenish-bee-backups"
TIMESTAMP=$(date +%Y%m%d-%H%M%S)

# Comprehensive Backup Strategy
tar -czf "/tmp/greenish_bee_backup_${TIMESTAMP}.tar.gz" \
    /app/greenish-bee \
    /var/log \
    /etc/docker/compose

# S3 Upload with Versioning
aws s3 cp "/tmp/greenish_bee_backup_${TIMESTAMP}.tar.gz" \
    "s3://${BACKUP_BUCKET}/backups/"

class AlertSystem:
    def __init__(self, notification_channels=['email', 'slack']):
        self.channels = notification_channels
        self.threshold_config = {
            'cpu_threshold': 80,
            'memory_threshold': 85,
            'disk_threshold': 90
        }

    def evaluate_system_health(self, metrics):
        alerts = []
        if metrics['cpu_usage'] > self.threshold_config['cpu_threshold']:
            alerts.append(f"High CPU Usage: {metrics['cpu_usage']}%")

        return alerts