Skip to content

Cloud Deployment Models


Cloud deployment models define where cloud infrastructure is located, who has access to it, and how it’s managed. Understanding these models is essential for designing solutions that meet sovereignty, security, and compliance requirements.

Cloud Deployment Architectures

Cloud Deployment Models showing Public, Private, Hybrid, and Multi-cloud architectures Figure 1: Cloud deployment model architectures and their relationships

Cloud Deployment Models Overview

Cloud Deployment Models Overview Figure 2: Four primary cloud deployment models and their characteristics

Services delivered over the public internet and shared across organizations. Resources owned and operated by third-party providers (Microsoft Azure, AWS, Google Cloud).

  • Multi-tenant architecture with shared infrastructure
  • Internet-based access with global availability
  • Provider-managed infrastructure and operations
  • Pay-per-use pricing model
  • No upfront capital investment
  • Virtually unlimited scalability
  • 99.9%+ uptime SLAs
  • Access to latest technologies
  • Limited control over data location
  • Compliance complexity for regulated industries
  • Internet connectivity dependency

Web applications, development/testing, big data analytics, backup/DR, collaboration tools

Dedicated infrastructure for a single organization, located on-premises or hosted by provider.

  • Single-tenant with dedicated resources
  • Enhanced security with isolated environment
  • Customizable to specific requirements
  • Performance predictability with no “noisy neighbors”

On-Premises: Organization’s data center, full control Hosted: Provider-managed, dedicated hardware Virtual Private Cloud (VPC): Isolated section within public cloud

  • Complete security and compliance control
  • Predictable performance
  • Full customization capabilities
  • Higher capital investment
  • Limited scalability
  • Full management responsibility

Regulated industries (healthcare, finance), sensitive data, mission-critical applications

Examples: Azure Local (connected and disconnected modes), VMware Private Cloud, on-premises Hyper-V

Combines public and private clouds, enabling data and application sharing while maintaining distinct boundaries.

  • Multi-environment integration with unified management
  • Workload portability between environments
  • Flexible resource allocation for optimal placement

Cloud Bursting: Scale to public cloud during peak demand Data Locality: Keep sensitive data on-premises, use cloud for processing Disaster Recovery: Primary on-premises, backup/DR in cloud

  • Workload flexibility and gradual migration
  • Cost optimization (base in private, burst to public)
  • Balance compliance with innovation
  • Access to latest cloud services
  • Multi-environment complexity
  • Network connectivity requirements
  • Cross-platform expertise needed

Gradual cloud migration, variable workloads, compliance with innovation needs, DR/business continuity

Technologies: Azure Arc, Azure Local (connected), AWS Outposts, Google Anthos, VMware Cloud Foundation

Using services from multiple cloud providers simultaneously to avoid vendor lock-in or leverage best-of-breed capabilities.

  • Multiple providers with diverse technology stacks
  • Best-of-breed service selection
  • Distributed architecture across clouds

Diversified Portfolio: Different apps on different clouds Active-Active: Same apps on multiple clouds for redundancy Specialized Services: Best capabilities from each provider

  • Avoid vendor lock-in
  • Increased resilience and redundancy
  • Optimize service selection per use case
  • Management complexity across platforms
  • Multi-platform expertise required
  • Integration and data transfer complexity
  • Multiple billing relationships

Vendor independence strategy, global enterprises, high-availability needs, specialized service requirements

AspectPublic CloudPrivate CloudHybrid CloudMulti-Cloud
CostLowHighMediumVariable
ControlLowHighMediumMedium
ScalabilityHighLimitedHighHigh
SecuritySharedDedicatedMixedVariable
ComplianceStandardCustomFlexibleComplex
ManagementSimpleComplexMediumComplex

Public Cloud: Cost optimization, standard compliance, rapid scaling, limited IT resources Private Cloud: Data sovereignty, regulated industry, predictable workloads, custom security Hybrid Cloud: Gradual migration, variable workloads, data locality + cloud benefits Multi-Cloud: Vendor independence, best-of-breed services, high availability

Regulatory: Data residency, compliance frameworks, data sensitivity Technical: Performance needs, workload predictability, integration requirements Business: Risk tolerance, cost priorities, vendor independence Organizational: IT expertise, scaling speed, complexity tolerance

Financial Services (Hybrid): Core banking in private cloud, web/analytics in public cloud Healthcare (Private + SaaS): Patient records private, collaboration tools SaaS Global Retailer (Multi-Cloud): AWS for e-commerce, Azure for AI, Google for data warehouse Startup (Public): Single provider, maximize SaaS/PaaS for rapid scaling

Cloud-Native: Build new apps in cloud directly Lift-and-Shift: Move existing apps with minimal changes Modernization: Refactor for cloud-native architectures Hybrid-First: Keep critical systems on-premises, gradual migration

Cloud deployment models provide different approaches to leveraging cloud benefits while meeting specific requirements:

  • Public Cloud offers maximum cost efficiency and scalability
  • Private Cloud provides maximum control and customization
  • Hybrid Cloud balances control with cloud benefits
  • Multi-Cloud maximizes choice and reduces vendor dependence

The optimal approach depends on your specific requirements for cost, control, compliance, and complexity tolerance.

  1. ✅ Review deployment model characteristics and trade-offs
  2. ✅ Assess which models align with your organization’s needs
  3. ✅ Continue to Cloud Benefits and Considerations
  4. ✅ Complete the Knowledge Check after all Module 1 content


Last Updated: November 2025