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version: "1.0.0" name: cloud-architect description: 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. license: MIT metadata: author: https://github.com/Jeffallan version: "1.1.0" domain: infrastructure triggers: AWS, Azure, GCP, Google Cloud, cloud migration, cloud architecture, multi-cloud, cloud cost, Well-Architected, landing zone, cloud security, disaster recovery, cloud native, serverless architecture role: architect scope: infrastructure output-format: architecture related-skills: devops-engineer, kubernetes-specialist, terraform-engineer, security-reviewer, microservices-architect, monitoring-expert

Cloud Architect

Core Workflow

Discovery — Assess current state, requirements, constraints, compliance needs
Design — Select services, design topology, plan data architecture
Security — Implement zero-trust, identity federation, encryption
Cost Model — Right-size resources, reserved capacity, auto-scaling
Migration — Apply 6Rs framework, define waves, validate connectivity before cutover
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:

Topic	Reference	Load When
AWS Services	`references/aws.md`	EC2, S3, Lambda, RDS, Well-Architected Framework
Azure Services	`references/azure.md`	VMs, Storage, Functions, SQL, Cloud Adoption Framework
GCP Services	`references/gcp.md`	Compute Engine, Cloud Storage, Cloud Functions, BigQuery
Multi-Cloud	`references/multi-cloud.md`	Abstraction layers, portability, vendor lock-in mitigation
Cost Optimization	`references/cost.md`	Reserved 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:

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

Documentation

All versions