What is cloud computing?
Cloud computing is an approach to delivering computing resources through internet-based platforms rather than locally managed hardware. Instead of purchasing and maintaining physical infrastructure, organizations can access computing services such as storage, processing capacity, and software on demand.
Cloud platforms allow organizations to scale resources dynamically based on demand. Applications, databases, and analytics systems can run on infrastructure provided by cloud environments while users access them remotely.
This model enables organizations to build and operate digital systems without managing the underlying physical hardware.
Why cloud computing matters
Traditional IT infrastructure often requires organizations to purchase hardware in advance and maintain it over time. This approach can be expensive, difficult to scale, and slow to adapt to changing demands.
Cloud computing addresses these challenges by providing flexible infrastructure that can scale as workloads change. Organizations can deploy applications, manage data, and run analytics workloads without investing heavily in physical infrastructure.
As digital services and data volumes grow, cloud computing has become a foundational platform for building modern applications and supporting data-driven operations.
Key concepts of cloud computing
Elastic computing resources
Infrastructure that can scale automatically based on workload demand.
On-demand services
Resources that can be provisioned when needed without long-term infrastructure planning.
Shared infrastructure
Computing resources that are managed and delivered through centralized platforms.
Service delivery models
Different ways cloud platforms provide infrastructure, platforms, or software services.
Distributed environments
Cloud systems that operate across multiple geographic regions and data centers.
How cloud computing works
Cloud computing environments deliver computing resources through centralized platforms.
- Infrastructure provisioning – Virtual computing resources are created within cloud environments.
- Application deployment – Software applications are deployed on cloud infrastructure.
- Resource scaling – Systems automatically adjust computing capacity based on demand.
- Remote access – Users and applications access resources through internet-based interfaces.
- Monitoring and management – Cloud platforms track system performance and resource usage.
This model allows organizations to operate applications and services without managing physical hardware.
Key components of cloud computing environments
Compute infrastructure
Virtual machines or container environments that run applications.
Storage systems
Platforms that store structured and unstructured data.
Networking services
Systems that manage connectivity between applications and services.
Security and identity systems
Mechanisms that control access and protect resources.
Monitoring and management tools
Systems that track performance and usage.
Reference architecture (conceptual)
Cloud computing environments consist of multiple layers. At the base is the infrastructure layer, which provides compute, storage, and networking resources. Above this layer are platform services that support application development, data processing, and analytics.
Applications and digital services operate within the application layer, where users interact with systems. Governance and monitoring layers ensure security, reliability, and performance across the environment.
This architecture enables organizations to run applications, analytics systems, and AI workloads on scalable infrastructure.
Types of cloud computing models
Infrastructure as a Service (IaaS)
Provides virtual infrastructure such as compute and storage resources.
Platform as a Service (PaaS)
Provides environments for developing and deploying applications.
Software as a Service (SaaS)
Delivers complete applications through cloud platforms.
Each model provides a different level of control and abstraction.
Cloud computing vs on-premise infrastructure
| Aspect | Cloud Computing | On-Premise Infrastructure |
| Infrastructure ownership | Managed by cloud provider | Managed by organization |
| Scalability | Dynamic and elastic | Limited by installed hardware |
| Deployment speed | Rapid provisioning | Requires hardware setup |
| Cost structure | Usage-based | Capital investment |
Common enterprise use cases
- Hosting enterprise applications
• Running analytics and data platforms
• Supporting machine learning workloads
• Delivering digital services and web applications
• Managing scalable storage and data processing
Benefits of cloud computing
- Scalable computing resources
• Faster application deployment
• Reduced infrastructure management
• Flexible resource usage based on demand
• Supports analytics and AI workloads
Challenges and failure modes
- Managing costs across cloud services
• Integrating cloud systems with legacy infrastructure
• Ensuring data security and compliance
• Managing distributed environments
Enterprise adoption considerations
- Cloud strategy aligned with enterprise architecture
• Security and governance policies for cloud environments
• Migration planning for existing systems
• Integration with data platforms and applications
Where cloud computing fits in enterprise architecture
Cloud computing provides the infrastructure layer that supports modern applications, data platforms, and artificial intelligence systems. It enables organizations to deploy scalable environments where applications and analytics workloads can operate without relying on local infrastructure.
Within enterprise architectures, cloud platforms frequently host data platforms, machine learning systems, and digital services that support business operations.
Common tool categories used with cloud computing
- Infrastructure management platforms
• Cloud networking and security systems
• Monitoring and resource management tools
• Cloud-based data platform technologies
What’s next for cloud computing
- Expansion of cloud-native application development
• Growth of distributed and multi-cloud environments
• Integration with artificial intelligence and data platforms