senior-cloud-architect
# Senior Cloud Architect
What this skill does
# Senior Cloud Architect
Expert cloud architecture and infrastructure design across AWS, GCP, and Azure.
## Keywords
cloud, aws, gcp, azure, terraform, infrastructure, vpc, eks, ecs, lambda,
cost-optimization, disaster-recovery, multi-region, iam, security, migration
---
## Quick Start
```bash
# Analyze infrastructure costs
python scripts/cost_analyzer.py --account production --period monthly
# Run DR validation
python scripts/dr_test.py --region us-west-2 --type failover
# Audit security posture
python scripts/security_audit.py --framework cis --output report.html
# Generate resource inventory
python scripts/inventory.py --accounts all --format csv
```
---
## Tools
| Script | Purpose |
|--------|---------|
| `scripts/cost_analyzer.py` | Analyze cloud spend by service, environment, and tag |
| `scripts/dr_test.py` | Validate disaster recovery failover procedures |
| `scripts/security_audit.py` | Audit against CIS benchmarks and compliance frameworks |
| `scripts/inventory.py` | Inventory all resources across accounts and regions |
---
## Cloud Platform Comparison
| Service | AWS | GCP | Azure |
|---------|-----|-----|-------|
| Compute | EC2, ECS, EKS | GCE, GKE | VMs, AKS |
| Serverless | Lambda | Cloud Functions | Azure Functions |
| Storage | S3 | Cloud Storage | Blob Storage |
| Database | RDS, DynamoDB | Cloud SQL, Spanner | SQL DB, CosmosDB |
| ML | SageMaker | Vertex AI | Azure ML |
| CDN | CloudFront | Cloud CDN | Azure CDN |
---
## Workflow 1: Design a Production AWS Architecture
1. **Define requirements** -- Identify compute, storage, database, and networking needs. Determine RTO/RPO targets.
2. **Provision VPC with Terraform:**
```hcl
module "vpc" {
source = "terraform-aws-modules/vpc/aws"
version = "~> 5.0"
name = "${var.project}-${var.environment}"
cidr = var.vpc_cidr
azs = ["${var.region}a", "${var.region}b", "${var.region}c"]
private_subnets = var.private_subnets
public_subnets = var.public_subnets
enable_nat_gateway = true
single_nat_gateway = var.environment != "production"
enable_dns_hostnames = true
tags = local.common_tags
}
```
3. **Deploy compute** -- ECS/EKS in private subnets behind an ALB in public subnets. Use at least 2 AZs for redundancy.
4. **Configure database** -- RDS Multi-AZ for production, single-AZ for staging. Set backup retention to 30 days (production) or 7 days (non-production).
5. **Add caching layer** -- ElastiCache (Redis) between application and database.
6. **Layer security** -- WAF on CloudFront, NACLs on subnets, security groups on instances. Apply least-privilege IAM.
7. **Validate** -- Run `python scripts/security_audit.py --framework cis` and resolve all high-severity findings.
### Reference Architecture
```
Route 53 (DNS) -> CloudFront + WAF -> ALB
-> ECS/EKS Cluster (AZ-a) + ECS/EKS Cluster (AZ-b)
-> ElastiCache (Redis)
-> RDS Multi-AZ (Primary + Standby)
```
## Workflow 2: Optimize Cloud Costs
1. **Audit current spend** -- `python scripts/cost_analyzer.py --account production --period monthly`
2. **Right-size instances** -- Identify instances with avg CPU <10% and max CPU <30% as downsize candidates:
```python
# Pseudocode for right-sizing logic
if avg_cpu < 10 and max_cpu < 30:
recommendation = 'downsize'
elif avg_cpu > 80:
recommendation = 'upsize'
else:
recommendation = 'optimal'
```
3. **Convert steady-state workloads** to Reserved Instances or Savings Plans:
| Type | Discount | Commitment | Use Case |
|------|----------|------------|----------|
| On-Demand | 0% | None | Variable workloads |
| Reserved | 30-72% | 1-3 years | Steady-state |
| Savings Plans | 30-72% | 1-3 years | Flexible compute |
| Spot | 60-90% | None | Fault-tolerant batch |
4. **Enforce cost allocation tags** -- Require `Environment`, `Project`, `Owner`, `CostCenter` on all resources. Alert on untagged resources after 24 hours.
5. **Validate** -- Re-run cost analyzer and confirm savings target achieved.
## Workflow 3: Plan Disaster Recovery
1. **Select DR strategy** based on RTO/RPO requirements:
| Strategy | RTO | RPO | Cost |
|----------|-----|-----|------|
| Backup & Restore | Hours | Hours | $ |
| Pilot Light | Minutes | Minutes | $$ |
| Warm Standby | Minutes | Seconds | $$$ |
| Multi-Site Active | Seconds | Near-zero | $$$$ |
2. **Configure cross-region replication** -- Database replication to secondary region. S3 cross-region replication for object storage.
3. **Set up Route 53 failover routing** -- Health checks on primary. Automatic DNS failover to secondary.
4. **Define backup policy:**
- Database: continuous replication, 35-day retention, cross-region, encrypted
- Application data: daily, 90-day retention, lifecycle to IA at 30d, Glacier at 90d
- Configuration: on-change via git + S3, unlimited retention
5. **Test** -- `python scripts/dr_test.py --region us-west-2 --type failover` and confirm RTO/RPO targets met.
## Workflow 4: Audit Security Posture
1. **Run audit** -- `python scripts/security_audit.py --framework cis --output report.html`
2. **Review network segmentation** -- Public subnets contain only NAT GW, ALB, bastion. Private subnets contain application tier. Data subnets contain RDS, Redis, Elasticsearch.
3. **Enforce least-privilege IAM** -- Every policy scoped to specific resources and conditions:
```json
{
"Effect": "Allow",
"Action": ["s3:GetObject", "s3:PutObject"],
"Resource": "arn:aws:s3:::my-bucket/uploads/*",
"Condition": {
"StringEquals": { "aws:PrincipalTag/Team": "engineering" },
"IpAddress": { "aws:SourceIp": ["10.0.0.0/8"] }
}
}
```
4. **Verify encryption** -- Data encrypted at rest (KMS) and in transit (TLS 1.2+).
5. **Validate** -- Re-run audit and confirm all critical and high findings resolved.
---
## AWS Well-Architected Pillars (Decision Checklist)
- **Operational Excellence**: IaC everywhere? Monitoring and alerting? Runbooks for incidents?
- **Security**: Least-privilege IAM? Encryption at rest and in transit? VPC segmentation?
- **Reliability**: Multi-AZ? Auto-scaling? DR tested?
- **Performance**: Right-sized instances? Caching layer? CDN for static assets?
- **Cost Optimization**: Reserved capacity for steady-state? Spot for batch? Unused resources cleaned?
- **Sustainability**: Efficient regions? Right-sized compute? Data lifecycle policies?
---
## Reference Materials
| Document | Path |
|----------|------|
| AWS Patterns | [references/aws_patterns.md](references/aws_patterns.md) |
| GCP Patterns | [references/gcp_patterns.md](references/gcp_patterns.md) |
| Multi-Cloud Strategies | [references/multi_cloud.md](references/multi_cloud.md) |
| Cost Optimization Guide | [references/cost_optimization.md](references/cost_optimization.md) |
---
## Troubleshooting
| Problem | Cause | Solution |
|---------|-------|----------|
| Cross-region latency exceeds 200ms | No regional caching or CDN configured | Deploy CloudFront/Cloud CDN with edge locations closest to user base; enable regional API Gateway caches |
| Terraform state lock conflicts across teams | Shared state backend without proper locking | Use DynamoDB (AWS) or GCS (GCP) state locking with per-team state file partitioning via workspaces |
| Multi-cloud DNS failover not triggering | Health check thresholds too lenient or misconfigured endpoints | Set health check interval to 10s, failure threshold to 3, and verify endpoint returns 200 on the exact path monitored |
| IAM permission errors after cross-account migration | Trust policies not updated for new account IDs | Update AssumeRole trust policies with correct account principals and external IDs; validate with `aws sts assume-role` |
| Cloud costs spike unexpectedly after scaling event | Auto-scaling max limits set too high or no budget alerts | Set hard max instance counts per ASG, configure billing alertsRelated in Cloud & DevOps
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