Catalog
concept#Cloud#Platform#Architecture#Integration

Cloud Service Models (IaaS, PaaS, SaaS)

Core models for delivering IT resources in the cloud that define responsibility boundaries and management tasks between provider and consumer.

Cloud service models (IaaS, PaaS, SaaS) define layers of responsibility and abstraction for delivering computing resources over the internet.
Established
Medium

Classification

  • Medium
  • Technical
  • Architectural
  • Intermediate

Technical context

Identity providers (OAuth, SAML)CI/CD pipeline and deployment toolsMonitoring and observability tools

Principles & goals

Clear separation of responsibilities between provider and consumerSelect model based on operational and compliance requirementsPrefer managed services for repetitive operational tasks
Discovery
Enterprise, Domain

Use cases & scenarios

Compromises

  • Data residency and compliance breaches if used unchecked
  • Provider outages or service disturbances impact operations
  • Unexpected costs from scaling or add-on services
  • Automate provisioning and configuration
  • Design for failure and isolation (resilience principles)
  • Use managed services for recurring tasks

I/O & resources

  • Application profile (stateful/stateless, load patterns)
  • Security and compliance requirements
  • Cost and operational constraints
  • Recommended service model and rationale
  • Architecture overview with responsibility diagram
  • Implementation and migration plan

Description

Cloud service models (IaaS, PaaS, SaaS) define layers of responsibility and abstraction for delivering computing resources over the internet. They clarify control, operational tasks and typical use cases, guiding architectural decisions and vendor selection. The distinction influences security, compliance and integration patterns between provider and consumer.

  • Faster time-to-market via infrastructure abstraction
  • Reduced operational overhead with PaaS/SaaS
  • Scalability and flexible resource consumption

  • Limited control and customization in SaaS
  • Potential vendor lock-in with platform-specific services
  • Divergent security and compliance responsibilities

  • Time to provision

    Time from decision to production-ready deployment of an environment.

  • Operational cost per month

    Monthly costs for infrastructure, licenses and management.

  • Availability / MTTR

    Measure of service availability and mean time to recovery.

Startup uses PaaS for rapid product development

A small team reduces infrastructure overhead via PaaS and accelerates releases.

Company runs existing workloads in IaaS

Legacy systems remain on VMs to ensure compatibility and plan migration incrementally.

Organization uses SaaS for standard productivity tools

Email, collaboration and CRM are consumed as SaaS to reduce operational costs.

1

Perform inventory and requirements analysis

2

Compare models (IaaS/PaaS/SaaS) based on defined criteria

3

Build and test a pilot environment

4

Go-live with monitoring, SLA setup and handover to operations

⚠️ Technical debt & bottlenecks

  • Hard-coded provider APIs in application components
  • Monolith moved to IaaS without cloud-native patterns
  • Missing automation for scaling and recovery
vendor-lockinnetwork-bandwidthoperational-automation
  • Choosing SaaS for highly customized core processes
  • Operating IaaS long-term without automation
  • Using PaaS when regulations require full control
  • Underestimating hidden costs (e.g. data egress)
  • Missing exit strategy from a provider
  • Unaccounted integration effort with existing systems
Cloud architecture and designDevOps and automation skillsSecurity and compliance expertise
Scalability for variable loadsSecurity and compliance requirementsTime-to-market and development productivity
  • Regulatory requirements and data residency
  • Existing legacy dependencies
  • Budget and contractual restrictions with providers