본문으로 건너뛰기
cccskills
무료GitHub에 공개

aws-ec2

Manage EC2 instances, AMIs, and auto-scaling groups. Configure security groups, key pairs, and instance types. Use when deploying compute resources on AWS.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

연동 도구AWSTerraform
설치 방법 보기

포함된 파일(2)

  • SKILL.md12.6 KB
  • references/ec2-operations.md2.1 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

AWS EC2

Deploy and manage Amazon EC2 compute instances for production, staging, and development workloads.

When to Use This Skill

  • Launching new compute instances for application hosting
  • Building golden AMIs for consistent deployments
  • Setting up auto-scaling groups behind load balancers
  • Migrating workloads to Spot instances for cost savings
  • Troubleshooting instance connectivity, performance, or launch failures
  • Creating launch templates for repeatable infrastructure

Prerequisites

  • AWS CLI v2 installed and configured (aws configure)
  • IAM permissions: ec2:*, autoscaling:*, elasticloadbalancing:*, iam:PassRole
  • An existing VPC with subnets (see aws-vpc)
  • SSH key pair created (aws ec2 create-key-pair --key-name my-key --query 'KeyMaterial' --output text > my-key.pem)

Instance Type Selection Guide

CategoryTypesUse Case
General Purposet3, t3a, m6i, m7gWeb servers, small databases, dev/test
Compute Optimizedc6i, c7gBatch processing, media encoding, ML inference
Memory Optimizedr6i, r7g, x2idnIn-memory caches, large databases
Storage Optimizedi3, i4i, d3Data warehousing, distributed file systems
Acceleratedp4d, g5, inf2ML training, GPU rendering, inference
Burstablet3.micro-t3.2xlargeLow-steady-state with occasional bursts

Launch an Instance

# Launch a production web server
aws ec2 run-instances \
  --image-id ami-0abcdef1234567890 \
  --instance-type t3.medium \
  --key-name my-key \
  --security-group-ids sg-12345678 \
  --subnet-id subnet-12345678 \
  --iam-instance-profile Name=EC2AppProfile \
  --metadata-options "HttpTokens=required,HttpEndpoint=enabled" \
  --block-device-mappings '[{
    "DeviceName": "/dev/xvda",
    "Ebs": {
      "VolumeSize": 30,
      "VolumeType": "gp3",
      "Iops": 3000,
      "Throughput": 125,
      "Encrypted": true
    }
  }]' \
  --tag-specifications 'ResourceType=instance,Tags=[
    {Key=Name,Value=web-server-01},
    {Key=Environment,Value=production},
    {Key=Team,Value=platform}
  ]' \
  --user-data file://userdata.sh

# Launch with IMDSv2 required (security best practice)
aws ec2 run-instances \
  --image-id ami-0abcdef1234567890 \
  --instance-type t3.micro \
  --metadata-options "HttpTokens=required,HttpPutResponseHopLimit=1,HttpEndpoint=enabled" \
  --tag-specifications 'ResourceType=instance,Tags=[{Key=Name,Value=secure-instance}]'

User Data Scripts

#!/bin/bash
# userdata.sh - Bootstrap a web server on Amazon Linux 2023
set -euxo pipefail

# System updates
dnf update -y

# Install and start web server
dnf install -y nginx
systemctl enable nginx
systemctl start nginx

# Install CloudWatch agent
dnf install -y amazon-cloudwatch-agent
/opt/aws/amazon-cloudwatch-agent/bin/amazon-cloudwatch-agent-ctl \
  -a fetch-config -m ec2 \
  -s -c ssm:AmazonCloudWatch-linux

# Install CodeDeploy agent
dnf install -y ruby wget
cd /home/ec2-user
wget https://aws-codedeploy-us-east-1.s3.us-east-1.amazonaws.com/latest/install
chmod +x ./install
./install auto

# Signal CloudFormation (if launched via CFN)
# /opt/aws/bin/cfn-signal -e $? --stack ${AWS::StackName} --resource ASG --region ${AWS::Region}

Launch Templates

# Create a launch template with full configuration
aws ec2 create-launch-template \
  --launch-template-name web-server-template \
  --version-description "v1 - AL2023 with nginx" \
  --launch-template-data '{
    "ImageId": "ami-0abcdef1234567890",
    "InstanceType": "t3.medium",
    "KeyName": "my-key",
    "SecurityGroupIds": ["sg-12345678"],
    "IamInstanceProfile": {"Name": "EC2AppProfile"},
    "MetadataOptions": {
      "HttpTokens": "required",
      "HttpEndpoint": "enabled"
    },
    "BlockDeviceMappings": [{
      "DeviceName": "/dev/xvda",
      "Ebs": {
        "VolumeSize": 30,
        "VolumeType": "gp3",
        "Encrypted": true
      }
    }],
    "TagSpecifications": [{
      "ResourceType": "instance",
      "Tags": [
        {"Key": "Environment", "Value": "production"},
        {"Key": "ManagedBy", "Value": "launch-template"}
      ]
    }],
    "Monitoring": {"Enabled": true},
    "UserData": "'"$(base64 -w0 userdata.sh)"'"
  }'

# Create a new version of the launch template
aws ec2 create-launch-template-version \
  --launch-template-name web-server-template \
  --source-version 1 \
  --version-description "v2 - updated AMI" \
  --launch-template-data '{"ImageId": "ami-0newami1234567890"}'

# Set the default version
aws ec2 modify-launch-template \
  --launch-template-name web-server-template \
  --default-version 2

Auto Scaling Group

# Create ASG with mixed instances (on-demand + spot)
aws autoscaling create-auto-scaling-group \
  --auto-scaling-group-name web-asg \
  --mixed-instances-policy '{
    "LaunchTemplate": {
      "LaunchTemplateSpecification": {
        "LaunchTemplateName": "web-server-template",
        "Version": "$Default"
      },
      "Overrides": [
        {"InstanceType": "t3.medium"},
        {"InstanceType": "t3a.medium"},
        {"InstanceType": "m5.large"}
      ]
    },
    "InstancesDistribution": {
      "OnDemandBaseCapacity": 2,
      "OnDemandPercentageAboveBaseCapacity": 25,
      "SpotAllocationStrategy": "capacity-optimized"
    }
  }' \
  --min-size 2 --max-size 10 --desired-capacity 4 \
  --vpc-zone-identifier "subnet-aaa,subnet-bbb" \
  --target-group-arns "arn:aws:elasticloadbalancing:us-east-1:123456789012:targetgroup/web-tg/abc123" \
  --health-check-type ELB \
  --health-check-grace-period 300 \
  --tags '[
    {"Key":"Name","Value":"web-asg","PropagateAtLaunch":true},
    {"Key":"Environment","Value":"production","PropagateAtLaunch":true}
  ]'

# Create target tracking scaling policy (target 60% CPU)
aws autoscaling put-scaling-policy \
  --auto-scaling-group-name web-asg \
  --policy-name cpu-target-tracking \
  --policy-type TargetTrackingScaling \
  --target-tracking-configuration '{
    "PredefinedMetricSpecification": {
      "PredefinedMetricType": "ASGAverageCPUUtilization"
    },
    "TargetValue": 60.0,
    "ScaleInCooldown": 300,
    "ScaleOutCooldown": 60
  }'

# Create scheduled scaling for known traffic patterns
aws autoscaling put-scheduled-update-group-action \
  --auto-scaling-group-name web-asg \
  --scheduled-action-name scale-up-morning \
  --recurrence "0 8 * * MON-FRI" \
  --min-size 4 --max-size 20 --desired-capacity 8

aws autoscaling put-scheduled-update-group-action \
  --auto-scaling-group-name web-asg \
  --scheduled-action-name scale-down-evening \
  --recurrence "0 20 * * MON-FRI" \
  --min-size 2 --max-size 10 --desired-capacity 2

Spot Instances

# Request Spot instances
aws ec2 request-spot-instances \
  --spot-price "0.05" \
  --instance-count 3 \
  --type "one-time" \
  --launch-specification '{
    "ImageId": "ami-0abcdef1234567890",
    "InstanceType": "c5.xlarge",
    "KeyName": "my-key",
    "SecurityGroupIds": ["sg-12345678"],
    "SubnetId": "subnet-12345678"
  }'

# Check current Spot prices
aws ec2 describe-spot-price-history \
  --instance-types t3.medium t3a.medium m5.large \
  --availability-zone us-east-1a \
  --product-descriptions "Linux/UNIX" \
  --start-time "$(date -u +%Y-%m-%dT%H:%M:%SZ)" \
  --query "SpotPriceHistory[].{Type:InstanceType,Price:SpotPrice,AZ:AvailabilityZone}" \
  --output table

# Create a Spot Fleet request
aws ec2 request-spot-fleet \
  --spot-fleet-request-config '{
    "IamFleetRole": "arn:aws:iam::123456789012:role/aws-ec2-spot-fleet-role",
    "TargetCapacity": 10,
    "SpotPrice": "0.10",
    "AllocationStrategy": "capacityOptimized",
    "LaunchSpecifications": [
      {"ImageId": "ami-xxx", "InstanceType": "c5.xlarge", "SubnetId": "subnet-aaa"},
      {"ImageId": "ami-xxx", "InstanceType": "c5a.xlarge", "SubnetId": "subnet-bbb"}
    ]
  }'

AMI Management

# Create an AMI from a running instance
aws ec2 create-image \
  --instance-id i-0abc123def456 \
  --name "web-server-$(date +%Y%m%d)" \
  --description "Web server golden AMI" \
  --no-reboot \
  --tag-specifications 'ResourceType=image,Tags=[
    {Key=Name,Value=web-server-golden},
    {Key=Version,Value=2026.03.24}
  ]'

# Copy AMI to another region for disaster recovery
aws ec2 copy-image \
  --source-image-id ami-0abcdef1234567890 \
  --source-region us-east-1 \
  --region us-west-2 \
  --name "web-server-dr-copy"

# Deregister old AMIs and delete associated snapshots
aws ec2 deregister-image --image-id ami-old123
aws ec2 delete-snapshot --snapshot-id snap-old123

# Share AMI with another AWS account
aws ec2 modify-image-attribute \
  --image-id ami-0abcdef1234567890 \
  --launch-permission "Add=[{UserId=987654321098}]"

Instance Management

# List running instances with key details
aws ec2 describe-instances \
  --filters "Name=instance-state-name,Values=running" \
  --query "Reservations[].Instances[].{ID:InstanceId,Type:InstanceType,IP:PrivateIpAddress,Name:Tags[?Key=='Name']|[0].Value,State:State.Name}" \
  --output table

# Stop and start instances
aws ec2 stop-instances --instance-ids i-0abc123def456
aws ec2 start-instances --instance-ids i-0abc123def456

# Resize an instance (stop first)
aws ec2 stop-instances --instance-ids i-0abc123def456
aws ec2 wait instance-stopped --instance-ids i-0abc123def456
aws ec2 modify-instance-attribute \
  --instance-id i-0abc123def456 \
  --instance-type '{"Value": "t3.large"}'
aws ec2 start-instances --instance-ids i-0abc123def456

# Get console output for debugging boot issues
aws ec2 get-console-output --instance-id i-0abc123def456

# Get instance screenshot (helps debug GUI issues)
aws ec2 get-console-screenshot --instance-id i-0abc123def456

Terraform EC2 with Auto Scaling

resource "aws_launch_template" "web" {
  name_prefix   = "web-"
  image_id      = data.aws_ami.amazon_linux.id
  instance_type = "t3.medium"

  iam_instance_profile {
    name = aws_iam_instance_profile.web.name
  }

  metadata_options {
    http_tokens   = "required"
    http_endpoint = "enabled"
  }

  block_device_mappings {
    device_name = "/dev/xvda"
    ebs {
      volume_size = 30
      volume_type = "gp3"
      encrypted   = true
    }
  }

  user_data = base64encode(file("userdata.sh"))

  tag_specifications {
    resource_type = "instance"
    tags = {
      Name        = "web-server"
      Environment = "production"
    }
  }
}

resource "aws_autoscaling_group" "web" {
  name                = "web-asg"
  min_size            = 2
  max_size            = 10
  desired_capacity    = 4
  vpc_zone_identifier = [aws_subnet.private_a.id, aws_subnet.private_b.id]
  target_group_arns   = [aws_lb_target_group.web.arn]
  health_check_type   = "ELB"

  launch_template {
    id      = aws_launch_template.web.id
    version = "$Latest"
  }

  tag {
    key                 = "Name"
    value               = "web-asg"
    propagate_at_launch = true
  }
}

resource "aws_autoscaling_policy" "cpu" {
  name                   = "cpu-target-tracking"
  autoscaling_group_name = aws_autoscaling_group.web.name
  policy_type            = "TargetTrackingScaling"

  target_tracking_configuration {
    predefined_metric_specification {
      predefined_metric_type = "ASGAverageCPUUtilization"
    }
    target_value = 60.0
  }
}

Troubleshooting

ProblemCauseFix
Instance stuck in pendingInsufficient capacityTry a different AZ or instance type
Cannot SSH to instanceSecurity group or NACL blocks port 22Check SG ingress rules and route tables
Instance immediately terminatesEBS volume limit or AMI issueCheck describe-instances for StateReason
IMDSv1 deprecation warningsMetadata options not setSet HttpTokens=required in launch template
User data not runningScript missing shebang or not base64Verify #!/bin/bash header; check /var/log/cloud-init-output.log
Spot instance terminatedCapacity reclaimed by AWSUse capacity-optimized allocation and diversify types
ASG not replacing unhealthyHealth check grace period too shortIncrease grace period to cover app boot time
EBS throughput bottleneckgp2 volume too small for IOPSMigrate to gp3 and set explicit IOPS/throughput

Related Skills

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Conduct periodic access reviews and certifications. Implement access governance and recertification workflows. Use when managing access compliance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

BagelHole/DevOps-Security-Agent-Skills1.2천2026년 5월 22일 업데이트

Build automated evaluation suites for AI agents using golden datasets, rubrics, and regression gates. Use when shipping agent features, validating prompt changes, or gating deployments on quality.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

BagelHole/DevOps-Security-Agent-Skills1.2천2026년 5월 22일 업데이트

Instrument AI agents with tracing, token metrics, latency, and cost visibility. Use for reliability and debugging.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

BagelHole/DevOps-Security-Agent-Skills1.2천2026년 5월 22일 업데이트

Secure AI agents against prompt injection, tool abuse, and data exfiltration with defense-in-depth controls. Use when building, deploying, or hardening agentic AI systems that invoke tools, access data, or interact with production infrastructure.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

BagelHole/DevOps-Security-Agent-Skills1.2천2026년 5월 22일 업데이트

Secure AI coding agents (Claude Code, Cursor, Codex, Copilot) with permission boundaries, secret protection, code review gates, and safe sandbox configurations for team environments.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

BagelHole/DevOps-Security-Agent-Skills1.2천2026년 5월 22일 업데이트

Use service mesh patterns for AI inference traffic management, mTLS, canary releases, policy enforcement, and cross-cluster resilience.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

BagelHole/DevOps-Security-Agent-Skills1.2천2026년 5월 22일 업데이트

BagelHole의 스킬 모두 보기

이 스킬의 문제 신고