Quick reference — service models, deployment models, region/AZ terms, shared responsibility split, and pricing models.
IaaSPaaSRegionsShared Responsibility
Service Models
| Model | You manage | Example |
|---|
| IaaS | OS + up | EC2, Azure VM, Compute Engine |
| PaaS | App + data | App Service, Beanstalk, App Engine |
| FaaS | Function code | Lambda, Azure Functions |
| SaaS | Config + data | M365, Gmail, Salesforce |
Rule of thumb: the higher up the stack (IaaS → SaaS), the less you manage and the less control you have.
Deployment Models
| Model | Meaning |
|---|
| Public | Shared provider infra (AWS/Azure/GCP) |
| Private | Dedicated to one org, on-prem or hosted |
| Hybrid | Public + private linked (Outposts, Arc) |
| Multi-cloud | More than one public provider |
Location Hierarchy
| Term | What it is |
|---|
| Region | Geographic area, e.g. us-east-1, westeurope |
| Availability Zone | Isolated data center(s) in a region |
| Edge / PoP | CDN cache location near users |
List regions / zones
aws ec2 describe-regions --output table
aws ec2 describe-availability-zones --output text
az account list-locations -o tsv
gcloud compute regions list
Shared Responsibility
| Item | Owner |
|---|
| Physical DC, hardware, hypervisor | Provider |
| Guest OS + patching (IaaS) | Customer |
| IAM / access policies | Customer |
| App code + data + encryption config | Customer |
Provider secures OF the cloud; customer secures IN the cloud.
Scaling
| Type | Action | Note |
|---|
| Vertical (up) | Bigger machine | Has a ceiling, needs reboot |
| Horizontal (out) | More machines | Cloud default, fault tolerant |
Pricing Models
| Model | Discount | Use for |
|---|
| On-Demand | None | Spiky / unpredictable |
| Reserved / Savings Plan | up to ~72% | Steady baseline (1-3 yr) |
| Spot / Preemptible | up to ~90% | Interruptible batch / ML |
Ingress (data in) is usually free; egress (data out) is billed. Idle resources still cost money.
Well-Architected Pillars
Operational excellence · Security · Reliability · Performance efficiency · Cost optimization · Sustainability.
