Catalog
concept#Cloud#Architecture#Platform#Security

Cloud Deployment Model

Describes patterns for delivering IT resources in public, private, hybrid or community clouds and across SaaS/PaaS/IaaS service variants.

The cloud deployment model defines patterns for delivering IT resources across public, private, hybrid or community clouds and includes SaaS/PaaS/IaaS variants.
Established
Medium

Classification

  • Medium
  • Technical
  • Architectural
  • Intermediate

Technical context

Identity providers (SAML, OIDC)CI/CD pipelines and infrastructure automationMonitoring and observability tools

Principles & goals

Choose a model based on cost, security, control and scalabilityConsider compliance and data residency earlyInclude operational capabilities and automation as decision criteria
Discovery
Enterprise, Domain

Use cases & scenarios

Compromises

  • Lack of operational capabilities leads to high operating costs
  • Wrong data locality can create legal and compliance risks
  • Unclear responsibilities between provider and customer
  • Involve compliance and security owners early
  • Automate provisioning, security and monitoring
  • Ensure cost transparency via tagging and budget reporting

I/O & resources

  • Application requirements and SLOs
  • Data classification and legal requirements
  • Budget constraints and existing infrastructure
  • Recommended deployment model
  • Implications for operations and security
  • Migration and integration plan

Description

The cloud deployment model defines patterns for delivering IT resources across public, private, hybrid or community clouds and includes SaaS/PaaS/IaaS variants. It supports architectural decisions, governance, operations and compliance mapping. Decision criteria include cost, security, control, scalability and operational capabilities.

  • Enables targeted trade-offs between flexibility and control
  • Supports compliance via deliberate data locality and isolation
  • Improves cost transparency through mapping to service models

  • No silver bullet: each model carries specific restrictions
  • Hybrid solutions often increase complexity and integration effort
  • Vendor-specific services can limit portability

  • Total cost of ownership (TCO)

    Measure of all direct and indirect costs over the lifecycle

  • Availability / uptime

    Percentage of time the service is available

  • Mean time to recovery (MTTR)

    Average time to recover after an outage

Global SaaS startup

Product initially ran entirely in the public cloud; later introduced regional private tenants for legal compliance.

Financial institution with private cloud

Critical core banking systems in a private cloud, less critical services operated as SaaS.

University hybrid architecture

Research and sensitive data on-premise, teaching platforms in the public cloud for scalability.

1

Conduct requirements gathering and data classification

2

Evaluate deployment options and document trade-offs

3

Run a pilot in the selected model

4

Implement operational concepts, SLAs and disaster plans

⚠️ Technical debt & bottlenecks

  • Monolithic applications without cloud-native design
  • Manual provisioning and missing IaC artifacts
  • Insufficient observability and alerting configuration
Network latencyData replicationIdentity and access integration
  • Storing sensitive personal data in public cloud without encryption
  • Building a private cloud but not defining operational processes
  • Hybrid integration without clear network separation and authentication
  • Underestimating integration effort between clouds
  • Ignoring hidden recurring costs
  • Missing SLA alignment between provider and customer
Cloud architecture and networkingSecurity and compliance expertiseOperational automation and infrastructure as code
Data sovereignty and complianceScalability and performance requirementsOperational automation and cost optimization
  • Regulatory requirements for data locality
  • Existing legacy systems with limited portability
  • Budget and personnel constraints for self-hosting