Cloud computing has fundamentally reshaped how organizations deploy and manage IT infrastructure. Rather than purchasing servers, configuring networks, and maintaining data centers in-house, businesses can now provision computing resources on demand — scaling up or down as requirements change. But “the cloud” is not a monolithic concept. The deployment model an organization chooses — public, private, or hybrid — carries significant implications for security posture, regulatory compliance, cost structure, and operational flexibility.
This guide provides a detailed comparison of the three primary cloud deployment models, examines the service layers (IaaS, PaaS, SaaS), and analyzes the security and regulatory considerations that should inform cloud strategy decisions.
What is cloud computing?
Cloud computing is the delivery of computing services — servers, storage, databases, networking, software, and analytics — over the internet or private networks, on a pay-per-use or subscription basis. Instead of owning and maintaining physical infrastructure, organizations consume resources as a service, managed by a cloud provider or their own operations team.
The National Institute of Standards and Technology (NIST) defines five essential characteristics of cloud computing:
- On-demand self-service — users provision resources without requiring human interaction with the provider
- Broad network access — services are available over the network through standard mechanisms
- Resource pooling — provider resources are pooled to serve multiple consumers using a multi-tenant model
- Rapid elasticity — capabilities can be elastically provisioned and released to scale with demand
- Measured service — resource usage is monitored, controlled, and reported transparently
These characteristics apply across all deployment models, but the way they manifest differs significantly between public, private, and hybrid environments.
Public cloud
Definition and architecture
Public cloud refers to computing services offered by third-party providers over the public internet, available to anyone who wants to purchase them. The infrastructure — data centers, servers, networking equipment, storage arrays — is owned and operated entirely by the cloud provider. Multiple customers (tenants) share the same physical infrastructure, with logical isolation enforced through virtualization and software-defined networking.
The three dominant public cloud providers in 2026 are:
- Amazon Web Services (AWS) — the market leader with the broadest service portfolio, operating 34+ regions globally. Key services include EC2 (compute), S3 (storage), RDS (managed databases), and Lambda (serverless).
- Microsoft Azure — deeply integrated with the Microsoft ecosystem (Active Directory, Microsoft 365, Dynamics). Strong in hybrid scenarios through Azure Arc and Azure Stack. Operates 60+ regions.
- Google Cloud Platform (GCP) — known for data analytics (BigQuery), machine learning (Vertex AI), and Kubernetes leadership (GKE). Operates 40+ regions with a strong emphasis on sustainability.
Other notable providers include Oracle Cloud Infrastructure (OCI), IBM Cloud, Alibaba Cloud, and European sovereign cloud initiatives like OVHcloud and IONOS.
Advantages of public cloud
Scalability without capital investment. Public cloud eliminates the need to purchase hardware upfront. Organizations pay only for resources consumed, converting capital expenditure (CapEx) into operational expenditure (OpEx). Scaling from ten to ten thousand virtual machines is a matter of API calls, not procurement cycles.
Global reach. Major providers operate data centers across dozens of regions worldwide. Deploying an application close to end users in Asia, Europe, and North America simultaneously requires no physical infrastructure investment.
Managed services. Providers offer hundreds of managed services — from databases and message queues to machine learning platforms and IoT hubs — reducing the operational burden on internal teams. Patching, upgrades, and availability are handled by the provider.
Innovation velocity. Public cloud providers release thousands of new features annually. Organizations gain access to cutting-edge capabilities — GPU clusters for AI training, quantum computing simulators, edge computing nodes — without building them internally.
Built-in redundancy. Major providers design their infrastructure with redundancy at every level: multiple availability zones within a region, cross-region replication, and automated failover mechanisms. Achieving similar resilience on-premises requires substantial investment.
Disadvantages and risks
Data sovereignty concerns. When data resides in a provider’s infrastructure, it may be subject to the jurisdiction of the country where the data center is located. For EU organizations, this raises questions about US-based providers and the extraterritorial reach of laws like the US CLOUD Act.
Vendor lock-in. Migrating between providers is often complex and costly. Proprietary services, APIs, and data formats create dependencies that are difficult to unwind. An application deeply integrated with AWS Lambda, DynamoDB, and SQS cannot be trivially moved to Azure or GCP.
Cost unpredictability. While pay-as-you-go pricing is flexible, it can also be surprising. Misconfigured auto-scaling, forgotten resources, data egress charges, and premium support tiers can result in bills that significantly exceed forecasts.
Multi-tenancy risks. Although logical isolation between tenants is robust, the shared physical infrastructure introduces a theoretical attack surface. Side-channel attacks, noisy neighbor effects on performance, and provider-side misconfigurations represent residual risks that the customer cannot fully control.
Limited customization. Organizations cannot configure the underlying hardware, hypervisor, or network fabric. For workloads requiring specialized hardware (specific CPU architectures, FPGA cards, or non-standard storage configurations), public cloud options may be insufficient.
Typical use cases
- Web applications and SaaS products requiring global distribution
- Development and testing environments that need rapid provisioning and teardown
- Big data analytics and machine learning workloads with variable compute demands
- Disaster recovery as a service (DRaaS) — replicating on-premises systems to cloud for failover
- Startups and organizations that need to move fast without large upfront infrastructure investment
Private cloud
Definition and architecture
Private cloud is cloud infrastructure operated solely for a single organization. The hardware may be physically located in the organization’s own data center (on-premises private cloud) or hosted by a third-party provider in a dedicated environment (hosted private cloud). The defining characteristic is single tenancy — no other organization shares the infrastructure.
Private cloud uses the same underlying technologies as public cloud — virtualization, software-defined networking, orchestration platforms — but deploys them within a controlled, dedicated environment. Common technology stacks include:
- VMware vSphere / vCloud — the most widely deployed enterprise virtualization platform
- OpenStack — open source cloud computing platform used by telecommunications companies and large enterprises
- Microsoft Azure Stack HCI / Azure Stack Hub — enables Azure services in on-premises data centers
- Nutanix — hyperconverged infrastructure combining compute, storage, and networking
On-premises vs hosted private cloud
On-premises private cloud means the organization owns, operates, and maintains all hardware in its own data centers. This provides maximum control but requires significant capital investment in hardware, facilities (power, cooling, physical security), and skilled personnel.
Hosted private cloud means a third-party provider manages dedicated hardware for the organization in the provider’s data center. The organization gets single-tenant isolation without the burden of facility management. Providers like Rackspace, OVHcloud, and specialized European hosting companies offer this model.
The choice between the two often depends on existing investments, available expertise, and regulatory requirements. Organizations with existing data centers and skilled teams may prefer on-premises. Those wanting private cloud benefits without building facilities typically choose hosted.
Advantages of private cloud
Control and customization. The organization controls every layer of the stack — from hardware selection and network topology to hypervisor configuration and storage architecture. This is essential for workloads with specific performance requirements or hardware dependencies.
Security and compliance. Single-tenant infrastructure eliminates multi-tenancy risks entirely. The organization controls physical access to hardware, manages encryption keys locally, and can implement security policies without negotiating with a shared service provider. For industries subject to strict regulations — financial services, healthcare, defense, critical infrastructure — this level of control can simplify compliance.
Predictable performance. Without noisy neighbors competing for resources, private cloud delivers consistent, predictable performance. Latency-sensitive applications, real-time systems, and high-frequency trading platforms benefit from this consistency.
Data residency certainty. Data physically resides in locations the organization controls, eliminating ambiguity about jurisdictional exposure. This is increasingly important under GDPR, where organizations must demonstrate exactly where personal data is processed and stored.
Disadvantages of private cloud
High capital expenditure. Building and maintaining a private cloud requires substantial upfront investment in hardware, data center facilities, and networking equipment. A mid-sized private cloud deployment can cost hundreds of thousands to millions of euros before a single workload runs.
Operational complexity. The organization is responsible for everything: hardware lifecycle management, patching, capacity planning, disaster recovery, and 24/7 operations. This demands a skilled team of infrastructure engineers, which can be difficult and expensive to recruit and retain.
Limited scalability. Scaling requires purchasing and deploying additional hardware — a process measured in weeks or months, not minutes. Organizations must over-provision to handle peak demand, resulting in underutilized capacity during normal operations.
Innovation lag. Adopting new services and capabilities requires internal development and deployment. While public cloud providers release managed AI, analytics, and IoT services continuously, private cloud operators must build or integrate these capabilities themselves.
Typical use cases
- Financial institutions processing sensitive transactions under strict regulatory oversight
- Healthcare organizations managing patient data subject to medical confidentiality requirements
- Government agencies and defense contractors handling classified or sensitive information
- Industrial systems requiring low-latency, high-reliability compute at the edge
- Organizations with massive, predictable workloads where the economics of owned infrastructure outperform cloud pricing
Hybrid cloud
Definition and architecture
Hybrid cloud combines private infrastructure (on-premises or hosted) with public cloud services, connected through orchestration technology that enables workloads and data to move between environments. The key distinction from simply using both public and private cloud is integration — a true hybrid cloud operates as a unified platform with consistent management, networking, and security policies across environments.
The architecture typically includes:
- Private infrastructure — on-premises data center or hosted private cloud running core workloads
- Public cloud services — one or more public providers handling scalable, less sensitive workloads
- Interconnection layer — dedicated network connections (AWS Direct Connect, Azure ExpressRoute, GCP Cloud Interconnect), VPN tunnels, or SD-WAN overlays providing secure, low-latency communication between environments
- Unified management plane — tools like Azure Arc, Google Anthos, or VMware Tanzu that provide consistent deployment, monitoring, and policy enforcement across environments
- Identity federation — single identity system (typically Active Directory or an IDaaS platform) spanning both environments
When to use hybrid cloud
Hybrid cloud is not inherently superior to pure public or pure private. It is the right choice when specific conditions exist:
Regulatory constraints with scalability needs. When regulations require certain data to remain on-premises, but the organization also needs elastic scalability for other workloads. Example: a bank keeping core transaction processing on-premises while using public cloud for customer-facing mobile applications and analytics.
Cloud bursting. When normal operations fit within private cloud capacity, but periodic spikes (seasonal traffic, batch processing, marketing campaigns) require additional resources. Rather than over-provisioning private infrastructure for peak demand, organizations burst into public cloud temporarily.
Gradual migration. Organizations moving from on-premises to cloud rarely do so in a single step. Hybrid cloud provides a migration path where workloads move incrementally, with both environments coexisting during the transition.
Disaster recovery. Using public cloud as a disaster recovery target for on-premises systems provides geographic redundancy without the cost of a secondary physical data center.
Data gravity. When large datasets reside on-premises (terabytes or petabytes of historical data), it may be impractical or prohibitively expensive to move them to public cloud. Hybrid architecture allows analytics workloads to run close to the data while using cloud for other functions.
Challenges of hybrid cloud
Complexity. Managing two fundamentally different environments with consistent security, networking, and policies is significantly more complex than managing either one alone. Hybrid cloud requires expertise in both on-premises infrastructure and cloud-native services.
Network latency. Communication between on-premises and cloud environments introduces latency that does not exist within a single data center or cloud region. Applications designed for low-latency intra-datacenter communication may not perform well in a hybrid architecture without significant rearchitecting.
Security surface expansion. The interconnection between environments creates additional attack vectors. VPN tunnels, API gateways, and identity federation must be carefully secured. A compromise in either environment can potentially propagate to the other.
Cost optimization difficulty. Tracking and optimizing costs across two billing models (CapEx for private, OpEx for public) is more complex than managing either alone. Data egress charges for moving data between environments can be substantial.
Public vs private vs hybrid cloud — comparison
| Aspect | Public Cloud | Private Cloud | Hybrid Cloud |
|---|---|---|---|
| Upfront cost | None (OpEx model) | High (CapEx + OpEx) | Moderate (existing private + cloud OpEx) |
| Ongoing cost | Pay-per-use, variable | Predictable, staff-dependent | Combined, harder to optimize |
| Scalability | Near-unlimited, minutes | Limited by hardware, weeks | Elastic via cloud bursting |
| Security control | Shared responsibility | Full organizational control | Split across environments |
| Compliance | Provider certifications, shared | Full organizational ownership | Flexible data placement |
| Performance | Variable (multi-tenant) | Predictable (single-tenant) | Depends on workload placement |
| Vendor lock-in risk | High (proprietary services) | Low (own infrastructure) | Moderate (management tools) |
| Operational burden | Low (managed by provider) | High (fully self-managed) | Highest (both environments) |
| Innovation access | Immediate (managed services) | Delayed (must build/integrate) | Selective (choose per workload) |
| Best for | Startups, SaaS, variable workloads | Regulated industries, sensitive data | Mixed requirements, migration |
Multi-cloud vs hybrid cloud
These terms are frequently confused but describe different strategies:
Hybrid cloud integrates private and public infrastructure into a unified environment. The emphasis is on connecting on-premises resources with cloud services.
Multi-cloud uses multiple public cloud providers simultaneously. An organization might run its container workloads on GKE (Google), its enterprise applications on Azure (for Active Directory integration), and its data lake on AWS (for S3 and Redshift). The emphasis is on avoiding single-provider dependency and leveraging best-of-breed services.
The two strategies are not mutually exclusive. An organization can operate a hybrid multi-cloud environment — private infrastructure connected to multiple public clouds. However, this maximizes both flexibility and complexity.
Key considerations for multi-cloud:
- Portability — containerized workloads (Kubernetes) and infrastructure-as-code (Terraform) improve portability across providers
- Data synchronization — keeping data consistent across providers adds latency and complexity
- Skill requirements — each provider has its own services, APIs, and best practices, requiring broader team expertise
- Cost management — optimizing spend across multiple providers requires sophisticated tooling (FinOps)
Cloud service models — IaaS, PaaS, SaaS
Cloud computing is delivered through three fundamental service models, each abstracting a different layer of the technology stack:
Infrastructure as a Service (IaaS)
IaaS provides virtualized computing resources over the internet: virtual machines, storage volumes, and networks. The provider manages the physical infrastructure; the customer manages everything from the operating system upward — middleware, runtime, applications, and data.
Examples: AWS EC2, Azure Virtual Machines, Google Compute Engine, DigitalOcean Droplets.
When to use: When the organization needs maximum control over the operating system and software stack. Common for lift-and-shift migrations, custom applications with specific OS requirements, and workloads needing specialized configurations.
Platform as a Service (PaaS)
PaaS provides a platform for developing, running, and managing applications without dealing with the underlying infrastructure. The provider manages the operating system, middleware, and runtime; the customer focuses on application code and data.
Examples: AWS Elastic Beanstalk, Azure App Service, Google App Engine, Heroku.
When to use: When development teams want to focus on writing code rather than managing infrastructure. Ideal for web applications, APIs, and microservices where the platform handles scaling, patching, and load balancing automatically.
Software as a Service (SaaS)
SaaS delivers complete applications over the internet on a subscription basis. The provider manages everything — infrastructure, platform, and application — while the customer simply uses the software through a browser or API.
Examples: Microsoft 365, Salesforce, Google Workspace, Slack, Zoom.
When to use: When the organization needs standard business applications (email, CRM, collaboration) without the burden of hosting, maintaining, and updating them internally.
The shared responsibility shift
As you move from IaaS to PaaS to SaaS, more responsibility shifts to the provider:
- IaaS — customer manages OS, middleware, applications, data, access controls
- PaaS — customer manages applications, data, access controls
- SaaS — customer manages data and access controls only
Understanding this shift is critical for security planning. Each layer the customer controls is a layer the customer must secure.
Cloud security — threats and the shared responsibility model
Cloud security is not a binary property of the deployment model. It depends on how the environment is configured, monitored, and maintained. The most common cloud security incidents result from customer misconfigurations, not provider infrastructure failures.
Common cloud security threats
Misconfiguration. The leading cause of cloud security breaches. Publicly exposed storage buckets (S3, Azure Blob), overly permissive IAM policies, unencrypted databases, and disabled logging have caused some of the largest data breaches in recent years.
Identity and access management failures. Overprivileged accounts, lack of multi-factor authentication (MFA), leaked API keys, and inadequate service account management create pathways for unauthorized access.
Insecure APIs. Cloud-native applications rely heavily on APIs. Unauthenticated endpoints, inadequate rate limiting, and injection vulnerabilities in API layers expose backend systems.
Data exfiltration. Attackers who gain access to cloud environments can exfiltrate data through legitimate channels — copying data to external storage, sending it through allowed outbound connections, or using DNS tunneling.
Supply chain attacks. Third-party container images, open source dependencies, and CI/CD pipeline compromises can introduce malicious code into cloud-deployed applications.
Insider threats. Cloud environments with overly broad access policies amplify the impact of insider threats. A single compromised or malicious account with administrative access can affect the entire environment.
The shared responsibility model
Every major cloud provider operates under a shared responsibility model that clearly delineates security duties:
Provider responsibility (security OF the cloud):
- Physical security of data centers
- Hardware maintenance and lifecycle management
- Hypervisor and host operating system security
- Network infrastructure security
- Service availability and patching of managed services
Customer responsibility (security IN the cloud):
- Data classification and encryption (at rest and in transit)
- Identity and access management (IAM policies, MFA, least privilege)
- Operating system patching and configuration (for IaaS)
- Network configuration (security groups, NACLs, firewall rules)
- Application security (code, dependencies, vulnerability management)
- Logging, monitoring, and incident response
The boundary shifts depending on the service model. With IaaS, the customer carries most of the security burden. With SaaS, the provider handles nearly everything, but the customer remains responsible for access management and data governance.
Security best practices across all cloud models
- Enforce least privilege — every identity (human or machine) should have only the permissions required for its function
- Enable MFA everywhere — particularly for administrative and privileged accounts
- Encrypt data at rest and in transit — use provider-managed or customer-managed keys depending on compliance requirements
- Implement comprehensive logging — enable cloud-native logging services (CloudTrail, Azure Monitor, Cloud Audit Logs) and forward logs to a SIEM
- Automate security baselines — use infrastructure-as-code to enforce consistent security configurations and detect drift
- Regular penetration testing — test cloud environments for misconfigurations and vulnerabilities on a scheduled basis
- Segment networks — use VPCs, subnets, and security groups to limit lateral movement in case of compromise
Cloud computing and regulatory compliance
Regulatory frameworks increasingly address cloud computing directly, reflecting its pervasive role in processing sensitive data. European organizations must navigate several overlapping regulations.
GDPR (General Data Protection Regulation)
GDPR does not prohibit cloud computing, but imposes requirements that directly affect deployment choices:
- Data processing agreements (DPA) — organizations must have a DPA with every cloud provider processing personal data, specifying processing purposes, security measures, and sub-processor management
- Data residency — personal data transfers outside the EU/EEA require legal mechanisms (Standard Contractual Clauses, adequacy decisions). All major providers now offer EU data residency options
- Right to erasure — organizations must be able to demonstrate that personal data can be completely deleted from cloud systems, including backups and replicas
- Data protection impact assessments (DPIA) — required for high-risk processing activities, which may include cloud migrations involving personal data
NIS2 (Network and Information Security Directive)
NIS2, applicable since October 2024, significantly expands the scope of cybersecurity obligations for essential and important entities across the EU:
- Supply chain security — organizations must assess cybersecurity risks from their suppliers and service providers, including cloud providers
- Incident reporting — significant cybersecurity incidents must be reported within 24 hours (early warning) and 72 hours (full notification) to the relevant CSIRT
- Business continuity — organizations must maintain backup management, disaster recovery, and crisis management capabilities — directly relevant to cloud architecture decisions
- Management accountability — senior management is personally liable for ensuring compliance, elevating cloud security decisions to the board level
DORA (Digital Operational Resilience Act)
DORA, applicable from January 2025, specifically targets financial entities and their ICT service providers:
- ICT risk management framework — financial entities must identify and classify all ICT-related risks, including those from cloud dependencies
- Third-party risk management — critical ICT third-party providers (including major cloud providers) may be subject to direct oversight by European Supervisory Authorities
- Digital operational resilience testing — regular testing, including threat-led penetration testing (TLPT), of cloud-based systems
- Concentration risk — organizations must assess and mitigate the risk of over-reliance on a single cloud provider
Practical compliance strategies
- Map data flows — document exactly what data is processed in which environment, by which provider, in which jurisdiction
- Choose appropriate data residency — configure cloud regions to ensure personal and sensitive data remains within required jurisdictions
- Implement encryption with key management — consider customer-managed encryption keys (CMEK) for the most sensitive workloads, keeping key material outside the cloud provider’s control
- Maintain exit strategies — document and periodically test the ability to migrate away from a cloud provider, addressing concentration risk under DORA and supply chain risk under NIS2
- Conduct regular risk assessments — evaluate cloud providers against regulatory requirements on a scheduled basis, not just at initial onboarding
Best practices for cloud adoption
Successful cloud adoption is an organizational transformation, not just a technology decision. The following practices apply regardless of the chosen deployment model:
Start with a cloud strategy document. Define which workloads belong in which environment, what security and compliance requirements apply, and what success metrics will be tracked. Making these decisions ad hoc leads to sprawl, inconsistency, and security gaps.
Implement FinOps discipline. Cloud cost management requires dedicated processes and tooling. Establish budgets, alerts, and regular cost reviews. Use reserved instances or committed use discounts for predictable workloads. Tag all resources for cost allocation.
Adopt infrastructure as code. Define all infrastructure through code (Terraform, Pulumi, CloudFormation, Bicep) stored in version control. This ensures reproducibility, enables peer review of infrastructure changes, and provides an audit trail. Manual console configurations lead to drift and undocumented changes.
Design for failure. Cloud infrastructure will experience failures — individual instances, availability zones, and even entire regions can be disrupted. Design applications to tolerate failures through redundancy, health checks, circuit breakers, and automated failover.
Invest in cloud-native security tooling. Use cloud security posture management (CSPM) tools to continuously scan for misconfigurations. Implement cloud workload protection platforms (CWPP) for runtime security. Deploy cloud access security brokers (CASB) to monitor SaaS usage.
Build cloud expertise. The skills required for cloud operations differ significantly from traditional on-premises infrastructure management. Invest in training and certification for infrastructure, security, and development teams. Consider managed services for areas where internal expertise is insufficient.
Establish governance frameworks. Define policies for resource provisioning, access management, network configuration, and data classification. Automate policy enforcement through tools like Open Policy Agent (OPA), AWS Service Control Policies, or Azure Policy.
Cloud from a cybersecurity perspective
Cloud adoption changes the threat landscape in ways that require deliberate adaptation of security strategies.
The perimeter dissolves. Traditional network perimeter security (firewalls protecting a defined internal network) does not translate to cloud environments where resources are distributed, APIs are exposed, and users connect from everywhere. Zero trust architecture — verifying every request regardless of source — becomes essential.
Identity becomes the control plane. In cloud environments, identity and access management replaces network position as the primary security mechanism. Compromising an administrative identity can be more damaging than breaching a network perimeter. Protecting identities through MFA, conditional access policies, privileged access management (PAM), and continuous authentication monitoring is paramount.
Visibility requires intentional effort. On-premises, network monitoring tools can observe all traffic passively. In cloud environments, visibility requires actively enabling logging services, configuring log forwarding, and integrating cloud-native telemetry with security monitoring platforms. Organizations that do not invest in cloud-specific visibility operate blind.
Automation is a security tool. The speed and scale of cloud environments make manual security processes inadequate. Automated compliance checking, infrastructure drift detection, vulnerability scanning, and incident response workflows are necessary to maintain security posture at cloud speed.
Data protection extends beyond the perimeter. When data moves between environments, providers, and regions, protection must travel with it. Encryption, data loss prevention (DLP), and information rights management ensure that data remains protected regardless of where it resides.
The choice between public, private, and hybrid cloud is ultimately a risk management decision. Each model offers a different balance of control, flexibility, cost, and complexity. The right choice depends on the organization’s specific regulatory obligations, security requirements, technical capabilities, and business objectives — not on marketing narratives about any model being universally superior.
Related topics
See also:
