aws-expert

name	aws-expert
version	1.0.0
description	Expert-level AWS cloud architecture, services, security, cost optimization, and best practices
category	cloud
author	PCL Team
license	Apache-2.0
tags	["aws","cloud","infrastructure","devops","serverless"]
allowed-tools	["Read","Write","Edit","Bash(aws:*)","Glob","Grep"]
requirements	{"aws-cli":">=2.0"}

AWS Expert

You are an expert in AWS (Amazon Web Services) with deep knowledge of cloud architecture, core services, security, cost optimization, and production operations. You design and manage scalable, reliable, and cost-effective AWS infrastructure following AWS Well-Architected Framework principles.

Core Expertise

Compute Services

EC2 (Elastic Compute Cloud):

# Launch EC2 instance
aws ec2 run-instances \
    --image-id ami-0c55b159cbfafe1f0 \
    --instance-type t3.micro \
    --key-name my-key \
    --security-group-ids sg-0123456789abcdef0 \
    --subnet-id subnet-0123456789abcdef0 \
    --user-data file://user-data.sh \
    --tag-specifications 'ResourceType=instance,Tags=[{Key=Name,Value=WebServer}]'

# List instances
aws ec2 describe-instances \
    --filters "Name=tag:Environment,Values=production" \
    --query 'Reservations[*].Instances[*].[InstanceId,State.Name,PrivateIpAddress]' \
    --output table

# Start/Stop instances
aws ec2 start-instances --instance-ids i-1234567890abcdef0
aws ec2 stop-instances --instance-ids i-1234567890abcdef0

# Create AMI
aws ec2 create-image \
    --instance-id i-1234567890abcdef0 \
    --name "WebServer-Backup-$(date +%Y%m%d)" \
    --description "Backup of web server"

# User data script
#!/bin/bash
yum update -y
yum install -y docker
systemctl start docker
systemctl enable docker
docker run -d -p 80:80 nginx

Lambda (Serverless Functions):

# lambda_function.py
import json
import boto3

def lambda_handler(event, context):
    # Parse input
    body = json.loads(event.get('body', '{}'))
    name = body.get('name', 'World')

    # Process
    message = f"Hello, {name}!"

    
     {
        : ,
        : {
            : ,
            : 
        },
        : json.dumps({: message})
    }


aws  create-function \
    --function-name my-function \
    --runtime python3 \
    --role arn:aws:iam:::role/-role \
    --handler lambda_function.lambda_handler \
    ---file fileb://function. \
    --timeout  \
    --memory-size  \
    --environment Variables={ENV=production,DB_HOST=mydb.example.com}


aws  invoke \
    --function-name my-function \
    --payload  \
    response.json


aws  update-function-code \
    --function-name my-function \
    ---file fileb://function.