| name | cloud |
| description | Cloud computing, IaaS, PaaS, SaaS, and cloud-native development |
| license | MIT |
| compatibility | opencode |
| metadata | {"audience":"developers","category":"cloud-computing"} |
What I do
- Design cloud architectures
- Choose appropriate cloud services
- Optimize cloud costs
- Ensure cloud security
- Implement cloud-native patterns
When to use me
When building cloud-native applications, migrating to cloud, or designing scalable systems.
Cloud Service Models
IaaS (Infrastructure as a Service)
- Virtual machines
- Networking
- Storage
- Examples: AWS EC2, GCP Compute Engine, Azure VMs
- Pros: Full control, flexibility
- Cons: Management overhead
PaaS (Platform as a Service)
- Runtime environments
- Databases
- Message queues
- Examples: Heroku, Cloud Run, App Service
- Pros: Less management
- Cons: Less control
SaaS (Software as a Service)
- Complete applications
- Examples: Salesforce, Office 365, Slack
- Pros: No management
- Cons: Least customization
Cloud Concepts
Compute
- Virtual machines
- Containers (ECS, EKS, AKS, GKE)
- Serverless (Lambda, Cloud Functions, Azure Functions)
- Container instances
Storage
- Object storage (S3, GCS, Blob)
- Block storage (EBS, PD, Managed Disks)
- File storage (EFS, Filestore)
- Archive storage (Glacier, Archive)
Networking
- VPCs and subnets
- Load balancers
- CDN
- DNS
- VPN/Direct Connect
- Private endpoints
Databases
- RDBMS (RDS, Cloud SQL, Azure SQL)
- NoSQL (DynamoDB, Cosmos DB, MongoDB Atlas)
- Caching (ElastiCache, Memorystore)
- Data warehousing (Redshift, BigQuery, Synapse)
Security
- Identity management (IAM)
- Security groups
- Encryption at rest/transit
- Key management (KMS)
- Firewall rules
- Compliance certifications
Cost Optimization
- Right-sizing resources
- Reserved instances
- Spot/preemptible instances
- Savings plans
- Cost monitoring
- Auto-scaling
Cloud-Native Patterns
- Microservices
- Containerization
- Orchestration
- Service mesh
- Observability
- CI/CD automation
- Infrastructure as Code