BeClaude

cloud-architect

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9.9kCommunityGeneralby jeffallan · MIT

Designs cloud architectures, creates migration plans, generates cost optimization recommendations, and produces disaster recovery strategies across AWS, Azure, and GCP. Use when designing cloud architectures, planning migrations, or optimizing multi-cloud deployments. Invoke for Well-Architected Framework, cost optimization, disaster recovery, landing zones, security architecture, serverless design.

Python869 forks37 issuesUpdated 6/16/2026First seen 5/22/2026
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Overview

Cloud Architect

Core Workflow

  1. Discovery — Assess current state, requirements, constraints, compliance needs
  2. Design — Select services, design topology, plan data architecture
  3. Security — Implement zero-trust, identity federation, encryption
  4. Cost Model — Right-size resources, reserved capacity, auto-scaling
  5. Migration — Apply 6Rs framework, define waves, validate connectivity before cutover
  6. Operate — Set up monitoring, automation, continuous optimization

Workflow Validation Checkpoints

After Design: Confirm every component has a redundancy strategy and no single points of failure exist in the topology.

Before Migration cutover: Validate VPC peering or connectivity is fully established:

bash
# AWS: confirm peering connection is Active before proceeding
aws ec2 describe-vpc-peering-connections \
  --filters "Name=status-code,Values=active"

# Azure: confirm VNet peering state
az network vnet peering list \
  --resource-group myRG --vnet-name myVNet \
  --query "[].{Name:name,State:peeringState}"

After Migration: Verify application health and routing:

bash
# AWS: check target group health in ALB
aws elbv2 describe-target-health \
  --target-group-arn arn:aws:elasticloadbalancing:...

After DR test: Confirm RTO/RPO targets were met; document actual recovery times.

Reference Guide

Load detailed guidance based on context:

TopicReferenceLoad When
AWS Servicesreferences/aws.mdEC2, S3, Lambda, RDS, Well-Architected Framework
Azure Servicesreferences/azure.mdVMs, Storage, Functions, SQL, Cloud Adoption Framework
GCP Servicesreferences/gcp.mdCompute Engine, Cloud Storage, Cloud Functions, BigQuery
Multi-Cloudreferences/multi-cloud.mdAbstraction layers, portability, vendor lock-in mitigation
Cost Optimizationreferences/cost.mdReserved instances, spot, right-sizing, FinOps practices

Constraints

MUST DO

  • •Design for high availability (99.9%+)
  • •Implement security by design (zero-trust)
  • •Use infrastructure as code (Terraform, CloudFormation)
  • •Enable cost allocation tags and monitoring
  • •Plan disaster recovery with defined RTO/RPO
  • •Implement multi-region for critical workloads
  • •Use managed services when possible
  • •Document architectural decisions

MUST NOT DO

  • •Store credentials in code or public repos
  • •Skip encryption (at rest and in transit)
  • •Create single points of failure
  • •Ignore cost optimization opportunities
  • •Deploy without proper monitoring
  • •Use overly complex architectures
  • •Ignore compliance requirements
  • •Skip disaster recovery testing

Common Patterns with Examples

Least-Privilege IAM (Zero-Trust)

Rather than broad policies, scope permissions to specific resources and actions:

bash
# AWS: create a scoped role for an application
aws iam create-role \
  --role-name AppRole \
  --assume-role-policy-document file://trust-policy.json

aws iam put-role-policy \
  --role-name AppRole \
  --policy-name AppInlinePolicy \
  --policy-document '{
    "Version": "2012-10-17",
    "Statement": [{
      "Effect": "Allow",
      "Action": ["s3:GetObject", "s3:PutObject"],
      "Resource": "arn:aws:s3:::my-app-bucket/*"
    }]
  }'
hcl
# Terraform equivalent
resource "aws_iam_role" "app_role" {
  name               = "AppRole"
  assume_role_policy = data.aws_iam_policy_document.trust.json
}

resource "aws_iam_role_policy" "app_policy" {
  role = aws_iam_role.app_role.id
  policy = jsonencode({
    Version = "2012-10-17"
    Statement = [{
      Effect   = "Allow"
      Action   = ["s3:GetObject", "s3:PutObject"]
      Resource = "${aws_s3_bucket.app.arn}/*"
    }]
  })
}

VPC with Public/Private Subnets (Terraform)

hcl
resource "aws_vpc" "main" {
  cidr_block           = "10.0.0.0/16"
  enable_dns_hostnames = true
  tags = { Name = "main", CostCenter = var.cost_center }
}

resource "aws_subnet" "private" {
  count             = 2
  vpc_id            = aws_vpc.main.id
  cidr_block        = cidrsubnet("10.0.0.0/16", 8, count.index)
  availability_zone = data.aws_availability_zones.available.names[count.index]
}

resource "aws_subnet" "public" {
  count                   = 2
  vpc_id                  = aws_vpc.main.id
  cidr_block              = cidrsubnet("10.0.0.0/16", 8, count.index + 10)
  availability_zone       = data.aws_availability_zones.available.names[count.index]
  map_public_ip_on_launch = true
}

Auto-Scaling Group (Terraform)

hcl
resource "aws_autoscaling_group" "app" {
  desired_capacity    = 2
  min_size            = 1
  max_size            = 10
  vpc_zone_identifier = aws_subnet.private[*].id

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

  tag {
    key                 = "CostCenter"
    value               = var.cost_center
    propagate_at_launch = true
  }
}

resource "aws_autoscaling_policy" "cpu_target" {
  autoscaling_group_name = aws_autoscaling_group.app.name
  policy_type            = "TargetTrackingScaling"
  target_tracking_configuration {
    predefined_metric_specification {
      predefined_metric_type = "ASGAverageCPUUtilization"
    }
    target_value = 60.0
  }
}

Cost Analysis CLI

bash
# AWS: identify top cost drivers for the last 30 days
aws ce get-cost-and-usage \
  --time-period Start=$(date -d '30 days ago' +%Y-%m-%d),End=$(date +%Y-%m-%d) \
  --granularity MONTHLY \
  --metrics "UnblendedCost" \
  --group-by Type=DIMENSION,Key=SERVICE \
  --query 'ResultsByTime[0].Groups[*].{Service:Keys[0],Cost:Metrics.UnblendedCost.Amount}' \
  --output table

# Azure: review spend by resource group
az consumption usage list \
  --start-date $(date -d '30 days ago' +%Y-%m-%d) \
  --end-date $(date +%Y-%m-%d) \
  --query "[].{ResourceGroup:resourceGroup,Cost:pretaxCost,Currency:currency}" \
  --output table

Output Templates

When designing cloud architecture, provide:

  1. Architecture diagram with services and data flow
  2. Service selection rationale (compute, storage, database, networking)
  3. Security architecture (IAM, network segmentation, encryption)
  4. Cost estimation and optimization strategy
  5. Deployment approach and rollback plan

Documentation

Install & Usage

1
Create the skills directory
mkdir -p .claude/skills
2
Download the skill file
mkdir -p .claude/skills && curl -o .claude/skills/cloud-architect.md https://raw.githubusercontent.com/jeffallan/claude-skills/main/skills/cloud-architect/SKILL.md
3
Invoke in Claude Code
/cloud-architect
View source on GitHub
securitydeploymentdesignai-agentsclaudeclaude-codeclaude-marketplaceclaude-skills

Security Audits

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Frequently Asked Questions

What is cloud-architect?

Designs cloud architectures, creates migration plans, generates cost optimization recommendations, and produces disaster recovery strategies across AWS, Azure, and GCP. Use when designing cloud architectures, planning migrations, or optimizing multi-cloud deployments. Invoke for Well-Architected Framework, cost optimization, disaster recovery, landing zones, security architecture, serverless design.

How to install cloud-architect?

To install cloud-architect: create the skills directory (mkdir -p .claude/skills), then run: mkdir -p .claude/skills && curl -o .claude/skills/cloud-architect.md https://raw.githubusercontent.com/jeffallan/claude-skills/main/skills/cloud-architect/SKILL.md. Finally, /cloud-architect in Claude Code.

What is cloud-architect best for?

cloud-architect is a skill categorized under General. It is designed for: security, deployment, design. Created by jeffallan.