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/aws-well-architected-review

Perform an AWS Well-Architected Framework review of the current workload IaC and architecture, generating findings and GitHub issues for improvements.

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Perform an AWS Well-Architected Framework review of the current workload IaC and architecture, generating findings and GitHub issues for improvements.

SKILL.md

aws-well-architected-review.SKILL.md
name: aws-well-architected-review
description: 'Perform an AWS Well-Architected Framework review of the current workload IaC and architecture, generating findings and GitHub issues for improvements.'

AWS Well-Architected Review

This workflow performs a structured AWS Well-Architected Framework (WAF) review against your workload's IaC files and deployed infrastructure. It identifies risks across all 6 WAF pillars and creates GitHub issues to track remediation.

Prerequisites

  • AWS CLI configured and authenticated
  • IaC files present in the repository (Terraform, CloudFormation, CDK, or SAM)
  • GitHub MCP server configured and authenticated

Workflow Steps

Step 1: Load Well-Architected Framework Reference

Fetch current AWS WAF best practices:

  • `https://docs.aws.amazon.com/wellarchitected/latest/framework/welcome.html`
  • Pillar-specific lenses relevant to the workload type (Serverless, SaaS, etc.)

Step 2: Discover IaC & Architecture

Scan the repository for IaC files:

  • Terraform: `**/*.tf`
  • CloudFormation/SAM: `**/*.yaml`, `**/*.json` (CFn templates)
  • CDK: `lib/**/*.ts`, `bin/**/*.ts`, `cdk.json`

Identify key AWS services in use (compute, data, networking, security, observability) and generate a Mermaid architecture diagram.

Step 3: Pillar-by-Pillar Review

Pillar 1: Operational Excellence

  • [ ] All infrastructure defined as IaC (no manual console changes)
  • [ ] Consistent tagging strategy applied across all resources
  • [ ] CloudWatch alarms defined for key metrics
  • [ ] Automated deployment pipeline present (no manual deployments)
  • [ ] CloudTrail enabled for audit logging
  • [ ] Runbooks or operational documentation present

Pillar 2: Security

  • [ ] IAM roles use least-privilege policies (no `*` actions without justification)
  • [ ] No hardcoded credentials in IaC or code
  • [ ] Secrets managed via Secrets Manager or SSM Parameter Store
  • [ ] S3 buckets have public access blocked and server-side encryption enabled
  • [ ] Sensitive resources placed in private subnets
  • [ ] Security groups restrict inbound to minimum required ports/CIDRs
  • [ ] KMS encryption enabled for sensitive data stores (RDS, EBS, S3, SQS, DynamoDB)
  • [ ] SSL/TLS enforced on all endpoints (`enforceSSL: true`)
  • [ ] GuardDuty enabled (`aws guardduty list-detectors`)
  • [ ] AWS WAF configured on public-facing APIs and CloudFront distributions
  • [ ] MFA delete enabled on critical S3 buckets

Pillar 3: Reliability

  • [ ] Multi-AZ deployments for production databases (RDS Multi-AZ, DynamoDB Global Tables)
  • [ ] Auto Scaling configured with appropriate policies for EC2/ECS
  • [ ] S3 versioning and lifecycle policies configured
  • [ ] RDS automated backups enabled with appropriate retention period
  • [ ] DynamoDB Point-in-Time Recovery (PITR) enabled
  • [ ] Dead Letter Queues (DLQ) configured for Lambda, SQS, SNS
  • [ ] Route 53 health checks configured for DNS failover
  • [ ] Lambda reserved concurrency set to prevent noisy-neighbor throttling

Pillar 4: Performance Efficiency

  • [ ] Right-sized instance types (Lambda memory, EC2 type, RDS class)
  • [ ] Graviton/ARM instances used where available (Lambda `arm64`, EC2 Graviton)
  • [ ] Caching implemented (ElastiCache, DAX, CloudFront, API Gateway caching)
  • [ ] CloudFront used for global static content delivery
  • [ ] Aurora Serverless or DynamoDB On-Demand for variable load patterns
  • [ ] Lambda Provisioned Concurrency for latency-critical synchronous paths

Pillar 5: Cost Optimization

  • [ ] EC2 Reserved Instances or Savings Plans for steady-state workloads
  • [ ] S3 lifecycle policies moving data to cheaper storage tiers
  • [ ] Lambda `arm64` architecture adopted (20% cost reduction)
  • [ ] VPC Endpoints for S3/DynamoDB to avoid NAT Gateway charges
  • [ ] gp2 EBS volumes migrated to gp3 (same performance, 20% cheaper)
  • [ ] Development/test environments have auto-shutdown schedules
  • [ ] AWS Budgets and Cost Anomaly Detection configured
  • [ ] Unattached EBS volumes and idle EC2 instances identified

Pillar 6: Sustainability

  • [ ] Graviton/ARM instances selected where available
  • [ ] Serverless/managed services preferred over always-on EC2
  • [ ] S3 lifecycle policies reduce unnecessary long-term data storage
  • [ ] Auto Scaling configured to avoid over-provisioning
  • [ ] Region selection considers AWS renewable energy commitments

Step 4: Risk Classification

For each finding, classify:

  • **High Risk**: Security vulnerability, single point of failure, no backup/recovery
  • **Medium Risk**: Suboptimal reliability, cost inefficiency, performance concern
  • **Low Risk**: Best practice deviation, minor optimization opportunity

Step 5: User Confirmation

🏗️ AWS Well-Architected Review Summary

📊 Review Results:
• IaC Files Analyzed: X
• AWS Services Identified: Y
• Total Findings: Z
  • High Risk: A (immediate action required)
  • Medium Risk: B (should address soon)
  • Low Risk: C (nice to have)

🔴 Top High Risk Findings:
1. [Pillar]: [Finding] — [Why it matters]
2. [Pillar]: [Finding] — [Why it matters]

💡 This will create Z individual GitHub issues + 1 EPIC issue.

❓ Proceed with creating GitHub issues? (y/n)

Step 6: Create Individual Finding Issues

Label with "well-architected" and the pillar name (e.g., "security", "reliability").

**Title**: `[WAF-<PILLAR>] [Brief Finding] — [Risk Level]`

**Body**:

## 🏗️ Well-Architected Finding: [Brief Title]

**Pillar**: [Name] | **Risk Level**: [High/Medium/Low] | **Effort**: [Low/Medium/High]

### 📋 Description
[Clear explanation of the finding and why it matters]

### 🔧 Remediation

**IaC Fix** (preferred):
```hcl
# Terraform example
resource "aws_s3_bucket_server_side_encryption_configuration" "example" {
  bucket = aws_s3_bucket.example.id
  rule {
    apply_server_side_encryption_by_default {
      sse_algorithm = "aws:kms"
    }
  }
}

**AWS CLI fallback**:

aws s3api put-bucket-encryption --bucket <name> \
  --server-side-encryption-co
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