Getting Started With Cloud / Cloud Service Models
IaaS, PaaS, SaaS, FaaS And Managed Services
A plain-language guide to cloud service models and the responsibilities that change with each one.
A plain-language guide to cloud service models and the responsibilities that change with each one.
Use the brief to sharpen a real cloud upskill conversation: what is the decision, what evidence matters, and what should remain human-led?
Capture one design rule you would reuse when reviewing an AI workload, assistant, or operating model.
Executive note
The Core Idea
Cloud service models describe how much of the technology stack the provider operates and how much the customer team operates. This helps teams choose the right balance between control, speed, responsibility, and flexibility.
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Plain-English Vocabulary
Azure examples include Virtual Machines for IaaS, App Service for PaaS, Microsoft 365 for SaaS, and Azure Functions for FaaS. AWS uses similar concepts with EC2, Elastic Beanstalk or App Runner, SaaS products, and Lambda.
- IaaS: Infrastructure as a Service. You rent virtual machines, networks, and storage, then operate more of the stack yourself.
- PaaS: Platform as a Service. You deploy applications onto a managed platform without managing the underlying servers directly.
- SaaS: Software as a Service. You use a finished application operated by the provider.
- FaaS: Function as a Service. You run small event-driven pieces of code without managing a long-running server.
- Managed service: a broad term for services where the provider operates more of the platform, such as databases, queues, search, or analytics.
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Realistic Scenario
A team needs a document processing workflow. With IaaS, they may run their own servers and install the processing software. With PaaS, they deploy the application to a managed runtime. With FaaS, each uploaded document triggers a function. With SaaS, they may buy a product that already handles the workflow.
Each option changes time to value and operating responsibility.
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Why It Matters
These models shape cost, support, compliance, skill needs, and delivery speed. IaaS gives control but increases maintenance. SaaS moves faster but may limit customization. PaaS and managed services often provide a useful middle ground.
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Common Misunderstandings
- PaaS is not less serious than IaaS; it often improves reliability by standardizing operations.
- SaaS is not outside architecture; integration, identity, data, and exit options still matter.
- FaaS is not ideal for every workload; long-running or highly stateful workloads may fit better elsewhere.
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Recommended Practices
- Prefer higher-level managed services when they meet security, control, and integration needs.
- Use IaaS when legacy constraints or special control requirements justify it.
- Discuss exit, data ownership, and integration early for SaaS.
- Match the service model to team skills and support expectations.
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How To Talk About This With IT
Ask: "How much control do we need, and how much operational responsibility are we willing to keep?"