Cloud computing refers to delivering computing services like computing power, storage, and software over the internet, often referred to as "the cloud." It shifts traditional computing from local servers or personal devices to remote servers accessible through the web. This model offers scalability, flexibility, and cost efficiency by enabling users to scale resources up or down as needed without investing in physical hardware upfront.
The "pay-as-you-go" model is a cornerstone of cloud computing economics. Organizations typically pay only for the resources they use, reducing waste and optimizing budgets. Additionally, it democratizes computing technologies, as individuals and businesses can access large-scale infrastructure and advanced tools without the need for major capital investments.
This is part of a series of articles about cloud cost management
Here are the four primary models used to deliver services in the cloud.
IaaS provides businesses with virtualized computing infrastructure over the internet, such as servers, storage, and networking. Virtual machines let users configure and deploy environments tailored to specific needs without managing physical hardware. This model enables developers to scale systems dynamically while maintaining control over operating systems and applications.
A significant advantage of IaaS is cost savings—it eliminates upfront hardware expenses and reduces IT maintenance burdens. Providers like AWS, Microsoft Azure, and Google Cloud offer high levels of availability and flexibility, addressing varying workloads such as application hosting or data analysis.
PaaS simplifies application development by providing an environment for building, testing, deploying, and managing software. It abstracts the complexities of infrastructure management, allowing developers to focus solely on writing code. Platforms often include pre-built tools, frameworks, and APIs that significantly speed up development cycles.
By leveraging PaaS, organizations gain efficiency and consistency. Examples include platforms like Google App Engine and AWS Elastic Beanstalk, which serve applications without requiring intricate server maintenance.
SaaS delivers software applications over the internet, eliminating the need for local installation or management. Users access these tools through a browser, paying subscription fees while relying on providers to handle backend maintenance and security. SaaS applications range from productivity suites like Google Workspace to CRM platforms like Salesforce.
The ease of use and accessibility make SaaS attractive for businesses of all sizes. It provides automatic software updates, ensuring users always have access to the latest features without downtime.
FaaS, often called serverless computing, lets developers execute code in response to events without provisioning or maintaining servers. The abstraction from server management allows teams to focus purely on application logic. Examples include AWS Lambda and Azure Functions that execute functions triggered by specific events, such as API calls.
This model suits event-driven applications where scaling happens automatically, reducing costs significantly for intermittent workloads. Unlike traditional models, FaaS bills users only for execution time, creating a cost-efficient ecosystem for short-lived tasks.
The public cloud is operated by third-party providers who deliver resources like servers and storage over the internet. These resources are shared among multiple organizations, making public clouds cost-efficient and universally accessible. Leading providers such as AWS, Microsoft Azure, and Google Cloud dominate the market with enterprise-grade offerings.
Public cloud services are ideal for businesses seeking scalable solutions with minimal infrastructure investment. However, they also require solid security measures since data resides on shared infrastructure.
Private clouds are dedicated to a single organization, offering greater control and security compared to public clouds. These clouds can be hosted on-premises or by a third-party provider. The exclusivity ensures data compliance and customization suitable for industries with stringent regulations like finance or healthcare.
Although private clouds provide unmatched privacy and performance, they require significant investments in hardware and maintenance. Businesses adopt private clouds for critical workloads, where data sovereignty and latency are key factors.
Hybrid clouds integrate public and private cloud environments, allowing data and applications to move between them. This flexibility lets businesses optimize resource allocation based on specific workload requirements. For instance, an organization can keep sensitive data in a private cloud while leveraging the public cloud for scalability.
Hybrid models foster innovation by blending cloud resources while avoiding vendor lock-in. Solutions like Microsoft Azure Arc and VMware facilitate seamless integration.
A community cloud serves multiple organizations with shared concerns, such as industry-specific regulatory requirements. Resources are collaboratively managed, reducing individual costs while ensuring tailored compliance. These clouds support niche applications and foster collaboration among trusted entities like research institutions.
Community clouds benefit industries like education or healthcare by addressing mutual priorities without exposing data externally.
Multi-cloud involves using services from multiple cloud providers, avoiding reliance on a single vendor. Organizations adopt multi-cloud strategies to enhance redundancy, optimize performance, and negotiate better pricing. These deployments allow businesses to match specific workloads with the most suitable provider.
While multi-cloud promotes flexibility and resilience, managing different platforms and environments can be complex. Solutions like Kubernetes help streamline orchestration across providers, making multi-cloud management more achievable.
The concept of cloud computing dates back to the 1960s when computer scientist John McCarthy suggested that computation could be delivered as a public utility. However, the practical implementation began in the late 1990s and early 2000s with the rise of internet bandwidth and virtualization technologies.
Salesforce pioneered early cloud software with its SaaS (software as a service) model in 1999, allowing users to access their customer relationship management (CRM) applications over the internet. Amazon Web Services (AWS) launched in 2006, introducing infrastructure as a service (IaaS) by offering storage and compute capacity on demand. This innovation laid the groundwork for other major providers like Microsoft Azure and Google Cloud.
Virtualization, distributed computing, and the development of large-scale data centers were key enablers. These technologies allowed multiple users to share the same physical infrastructure efficiently, a fundamental principle of cloud computing.
The evolution of cloud services has expanded to include platform as a service (PaaS) and a variety of specialized offerings, setting the stage for the modern cloud ecosystem that supports everything from startups to global enterprises.
Cloud computing architecture consists of several integrated components that enable the delivery of computing services over the internet. These components are typically divided into two broad categories: frontend and backend.
The frontend is the user-facing part of the cloud architecture. It includes client devices (such as desktops, laptops, or smartphones) and the interfaces used to access cloud services, like web browsers or mobile apps. This layer handles user interaction and sends service requests to the backend.
Frontends typically incorporate client-side applications or portals through which users can interact with cloud services. These interfaces are designed for accessibility and may support online consoles, dashboards, or command-line tools.
The backend is where the core cloud infrastructure resides. It includes the physical servers, storage systems, virtualization layers, and the software responsible for managing cloud resources. Key components include:
Middleware connects the frontend and backend, managing communication and data formatting. APIs (application programming interfaces) expose cloud functions in a standardized way, enabling integration and automation.
Security and management layers
Security is embedded across all architectural layers. This includes encryption, identity and access management (IAM), firewalls, and compliance monitoring tools. Additionally, management tools provide visibility and control, allowing administrators to monitor usage, configure policies, and ensure system health.
Redundancy and scalability
Cloud architectures are designed for fault tolerance and elasticity. Redundant systems and data replication ensure high availability. Scalability mechanisms—such as load balancers and auto-scaling groups—allow services to dynamically adjust to changes in demand, maintaining performance and reliability.
Cloud computing offers a wide range of advantages for individuals, businesses, and organizations by shifting IT resources to on-demand, scalable internet-based services. These benefits contribute to increased agility, lower costs, and enhanced operational performance.
While cloud computing has become a foundation of modern IT strategies, it also raises important challenges for organizations.
While cloud computing reduces upfront costs, uncontrolled consumption can lead to budget overruns. On-demand pricing models and auto-scaling can cause costs to spike unexpectedly if not monitored. Common pitfalls include orphaned resources, overprovisioning, and inefficient architecture.
Effective cost management involves using tools for cost tracking, setting budgets and alerts, and leveraging reserved or spot instances for predictable workloads. FinOps practices, which involve collaborative financial operations between IT and finance, help align cloud spending with business goals and improve forecasting accuracy.
Data stored in the cloud is often hosted across multiple geographies and accessed via the internet, increasing its exposure to threats. Cloud environments are attractive targets for cyberattacks, including data breaches, denial-of-service (DoS) attacks, and insider threats. Shared infrastructure models also raise concerns about data leakage between tenants.
To mitigate risks, cloud providers implement layered security measures like encryption, firewalls, and access controls. However, the responsibility is shared—organizations must configure security policies correctly, manage access credentials, and ensure endpoint protection.
Regulatory compliance in the cloud can be challenging due to varying laws across jurisdictions. Organizations handling sensitive data must adhere to regulations like GDPR, HIPAA, or SOC 2. Ensuring compliance involves understanding how and where data is stored, who has access, and how it's processed.
Public clouds may store data in global data centers, complicating compliance with data residency laws. Businesses must select providers that offer compliance certifications and configurable options for data locality, encryption, and audit logging. Regular assessments and legal consultation are crucial to maintaining alignment with regulatory standards.
Relying on a single cloud provider can limit flexibility and increase switching costs. Proprietary tools and services may be deeply integrated into workflows, making migration to another provider complex and costly.
To reduce lock-in, organizations can design applications using open standards, containerization, and multi-cloud strategies. Abstraction layers like Kubernetes or Terraform help maintain portability across platforms.
Cloud computing services span a wide range of offerings, categorized by their functionality and the problems they solve. Below are representative examples across major service types:
Cloud platforms offer scalable storage solutions for data archiving, real-time access, and backup. Services like Amazon S3, Google Cloud Storage, and Azure Blob Storage allow businesses to store large volumes of unstructured data at a low cost. These systems support tiered storage options, enabling users to optimize costs based on access frequency.
Backup and disaster recovery are also critical applications. Automated snapshots, replication across regions, and versioning ensure data durability and fast recovery in case of failures. Cloud storage eliminates the need for physical drives, offering increased resilience and accessibility.
Cloud computing has become a standard for hosting websites and web applications. Providers deliver dynamic provisioning of resources, load balancing, and content delivery networks (CDNs) to maintain performance under varying traffic conditions.
All major hosting providers now offer cloud hosting options, where websites run on servers hosted in a cloud environment. Dedicated cloud hosting platforms like AWS Elastic Beanstalk, Google App Engine, and Azure App Services simplify deployment while providing autoscaling and integrated monitoring.
Cloud environments are ideal for processing and analyzing massive datasets. They provide on-demand access to storage, high-performance computing, and analytics tools without upfront infrastructure investment. Services like AWS EMR, Google BigQuery, and Azure Synapse Analytics facilitate tasks such as ETL processing, real-time data streaming, and machine learning.
By centralizing data and analytics tools in the cloud, organizations can derive insights faster, scale workloads as needed, and integrate various data sources across the business.
Developers use cloud-based platforms to build, test, and deploy software in isolated and reproducible environments. These environments can be provisioned instantly, ensuring consistency across development, staging, and production.
CI/CD pipelines, containerization (e.g., Docker), and orchestration tools (e.g., Kubernetes) are often hosted in the cloud. This setup reduces infrastructure overhead, supports agile development practices, and accelerates release cycles. Cloud-based testing tools also allow for performance testing at scale.
Cloud providers like AWS, Azure, and Google Cloud offer ‘well-architected frameworks’ that guide users in designing secure, reliable, and efficient systems. These frameworks address key pillars: operational excellence, security, reliability, performance efficiency, and cost optimization.
Using architectural best practices reduces technical debt, improves scalability, and ensures systems meet business objectives. Regular reviews and automated assessments can highlight areas for improvement and prevent configuration drift over time.
Optimizing resource usage is critical for cost and performance efficiency. Organizations should regularly audit workloads to identify underutilized or idle resources. Rightsizing instances, leveraging auto-scaling, and adopting serverless or containerized solutions improve resource efficiency.
Cloud cost management tools can help dynamically allocate resources based on demand. Policies such as scheduled shutdowns for development environments further control usage and reduce unnecessary expenditure.
Comprehensive monitoring and logging provide visibility into system health, performance, and security. Cloud platforms offer native tools for collecting metrics, generating alerts, and analyzing logs. These capabilities enable proactive issue detection and response.
Centralized log management supports audit trails, compliance tracking, and root cause analysis. Integration with SIEM (security information and event management) systems enhances threat detection and incident response across distributed environments.
Encrypting data both at rest and in transit is fundamental to protecting sensitive information. Cloud providers offer built-in encryption services, but organizations should manage encryption keys securely—using key management systems (KMS) or bring-your-own-key (BYOK) models for added control.
Transport Layer Security (TLS) secures communication channels, while volume and object storage encryption ensure data confidentiality at rest. Regular audits and compliance with encryption standards (e.g., AES-256) help maintain strong data protection practices.
The zero trust model is an advanced security model that verifies every request, regardless of origin. It assumes no implicit trust within the network, enforcing strict authentication, authorization, and continuous validation. Zero trust mitigates risks from compromised accounts and lateral movement within systems.
Implementation of zero trust in the cloud includes using identity providers, multi-factor authentication, least-privilege access, and network segmentation. These controls reduce attack surfaces and improve incident response by enforcing granular security policies across cloud environments.
Related content: Read our guide to cloud cost management tools