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17+ Essential Cloud Computing Models You Should Know in 2025
Updated on 07 January, 2025
9.19K+ views
• 24 min read
Table of Contents
- What Are Cloud Computing Models? Understanding the Basics
- List of Top 17+ Cloud Computing Models You Need to Know
- Comparing Cloud Service Models: Key Differences and Use Cases
- The Benefits of Cloud Computing Models for Businesses and Individuals
- Overcoming the Challenges and Limitations of Cloud Computing Models
- How to Choose the Right Cloud Computing Model?
- How upGrad Helps You Master Cloud Computing?
Are you tired of dealing with outdated hardware, costly upgrades, and limited storage space? Imagine a solution that offers flexibility, scalability, and efficiency—all without the hassle of maintaining physical infrastructure. That’s the promise of cloud computing.
But what exactly are cloud computing models, and how do they fit into modern IT? Whether it’s cloud service models like IaaS, PaaS, or SaaS, or the ability to scale resources effortlessly, understanding these concepts is critical for staying ahead in today’s tech-driven world.
This guide demystifies cloud computing, exploring its key models, role in IT infrastructure, and the incredible opportunities it unlocks. Get ready to simplify your understanding and discover how the cloud can transform your career and business.
What Are Cloud Computing Models? Understanding the Basics
Cloud computing models are like different ways to customize a house—you pick the setup that fits your needs best. They’re divided into service models (how you use the cloud) and deployment models (where and how the cloud is set up).
1. Service Models
Think of these as the "what" you’re getting from the cloud:
- IaaS (Infrastructure as a Service): You rent the basics—servers, storage, and networking. It’s like renting land to build your own house.
- PaaS (Platform as a Service): You get tools to develop and run apps without managing the infrastructure. Imagine a pre-built kitchen ready for you to cook.
- SaaS (Software as a Service): Fully built software that you can use right away, like moving into a fully furnished apartment.
2. Deployment Models
These describe "where" the cloud lives:
- Public Cloud: Shared space, like a co-working office. Cost-effective but shared with others.
- Private Cloud: A personal setup just for you, like a home office. More control but costs more.
- Hybrid Cloud: A mix of both—like working from home and visiting the office when needed.
Now, let’s learn why cloud models matter? Choosing the right model is important because it affects:
- Cost: Public clouds are cheaper; private clouds offer control but at a higher price.
- Performance: Match the model to your workload for smoother operations.
- Security: Sensitive data may need the extra protection of private or hybrid clouds.
Here are a few examples of scalability and flexibility in action:
- Example 1: A startup uses SaaS for tools like Gmail and Zoom—it’s quick and low-maintenance.
- Example 2: A gaming company uses IaaS to rent servers during peak gaming seasons and scales down later.
- Example 3: Hospitals use Hybrid Clouds to keep sensitive patient data private while using public cloud tools for everyday tasks.
Cloud models help you make the most of technology by tailoring it to your needs. Think about your budget, goals, and security needs when choosing one!
You can also enhance your expertise in cloud computing and develop critical skills to advance your career with upGrad’s Cloud Computing Courses.
Also Read: Cloud Computing Architecture: Comprehensive Guide For Beginners
Now that you have a basic understanding of cloud computing models, let’s dive deeper into the top models shaping the future of technology and their specific applications.
List of Top 17+ Cloud Computing Models You Need to Know
Cloud computing has expanded into diverse models tailored to specific needs, making it crucial to understand their differences. Each model offers unique features, benefits, and use cases, helping businesses optimize performance, costs, and security.
Here’s a comparative table cloud computing models:
Model |
Unique Benefit |
Key Features |
Best Fit For |
IaaS | Full control over computing resources | Pay-as-you-go, high scalability | Hosting websites, scalable testing setups |
PaaS | Simplifies Android app creation | Pre-configured tools, scalable runtime | Developers needing fast deployment tools |
SaaS | Ready-to-use software with no setup | Fully managed, easy access | CRM, productivity tools |
FaaS | Executes code without server management | Event-driven, cost-efficient | Real-time processes, IoT |
CaaS | Simplifies containerized app management | Container orchestration, API-driven | Microservices, rapid testing |
DBaaS | Removes the complexity of database management | Automated backups, scalable storage | Data-centric apps, analytics-heavy tools |
DRaaS | Keeps operations running during disruptions | Continuous replication, fast recovery | Critical data protection, disaster readiness |
NaaS | Virtual networking services for flexible connectivity | Scalable bandwidth, centralized mgmt | Remote work environments, network tuning |
AIaaS | Democratizes access to AI tools | Pre-trained AI models, customization | Automating insights, improving workflows |
STaaS | On-demand, scalable storage | Redundant backups, accessible storage | Archiving, data sharing |
CaaS (Compliance) | Eases meeting regulatory requirements | Automated checks, detailed audits | Privacy compliance, audit readiness |
BaaS (Backup) | Ensures secure, automated backups | Off-site storage, scheduled restoration | Business continuity for all sizes |
SECaaS | Provides dynamic, cloud-driven security | Threat monitoring, updated solutions | Cybersecurity for small and large firms |
IDaaS | Streamlines identity and access management | SSO, MFA, role-based access | Enterprise identity security |
BaaS (Blockchain) | Makes blockchain tech accessible | Smart contracts, scalable infra | Transparent supply chains, crypto apps |
This table highlights the distinct value each model brings to specific scenarios, helping you quickly identify which cloud service fits your needs.
Also Read: Cloud Computing Architecture [With Components & Advantages]
Below is a breakdown of the 15 service models and 5 deployment models that will give you a clear picture of what’s available and how they fit into your goals.
Types of Cloud Service Models
Cloud service models—like IaaS, PaaS, and SaaS—offer different levels of control and functionality. They help you choose the best solution for tasks like building apps, managing data, or using ready-made tools.
1. Infrastructure as a Service (IaaS)
Infrastructure as a Service (IaaS) is a cloud model that delivers fundamental computing resources—such as servers, storage, and networking—on demand.
It provides a virtualised infrastructure that you can configure and manage. It is perfect for businesses needing flexibility and control without the expense of maintaining physical hardware.
Key Features:
- Pay-as-you-go pricing: Only pay for the resources you use, helping to optimize costs.
- High scalability and flexibility: Easily scale up or down based on workload demands.
- Minimal management overhead: The cloud provider handles hardware maintenance and updates, letting you focus on your applications.
Examples:
- Amazon EC2: Provides scalable virtual servers for any workload.
- Google Compute Engine: Offers reliable and customizable virtual machines.
Use Cases:
- Website hosting: Host websites with adjustable resources to handle traffic fluctuations.
- Development and testing environments: Create isolated environments for building and testing software without disrupting production systems.
IaaS is a versatile choice for businesses seeking cost-effective, scalable, and easily manageable infrastructure solutions.
Also Read: Google Cloud Certification: Complete Guide to Benefits, Types and More
2. Platform as a Service (PaaS)
A ready-to-use platform that can be used by developers to build, test, and deploy applications. It handles the underlying infrastructure like servers, storage, and networking.
PaaS allows developers to focus solely on coding and innovation, rather than infrastructure management.
Key Features:
- Pre-configured development tools: Includes frameworks, databases, and APIs to streamline application development.
- Simplified app deployment: Enables developers to deploy applications with minimal setup or configuration.
- Scalable runtime environment: Automatically adjusts resources to accommodate changes in app usage or demand.
Examples:
- Microsoft Azure App Service: Simplifies the process of building and hosting web apps on the cloud.
- Heroku: A user-friendly platform for deploying and managing apps built in various programming languages.
Use Cases:
- Building web or mobile apps: Ideal for developing scalable and feature-rich applications.
- Collaborative software development: Facilitates teamwork with integrated tools and streamlined workflows.
PaaS is a great choice for developers who want to accelerate application development without the hassle of managing infrastructure.
Also Read: Azure Portal Insightful Resources [Handy Guide]
3. Software as a Service (SaaS)
SaaS offers ready-to-use software applications accessible via the internet. Users can access these tools directly through a browser, so you don't need to worry about installation and maintenance.
SaaS solutions are fully managed by the provider, allowing users to focus on productivity rather than technical setup.
Key Features:
- Fully managed by the provider: The service provider handles updates, security, and maintenance.
- Accessible from any device: Use the software on any device with internet access.
- No installation required: Simply log in and start using the application without needing to download or configure anything.
Examples:
- Google Workspace (Docs, Sheets): Provides cloud-based tools for collaboration and productivity.
- Salesforce: Offers powerful customer relationship management (CRM) solutions.
Use Cases:
- CRM systems: Manage customer interactions, sales pipelines, and analytics in one platform.
- Office productivity: Streamline tasks like document creation, collaboration, and communication with easy-to-use tools.
SaaS is perfect for businesses and individuals seeking efficient, cost-effective software solutions without the complexity of managing infrastructure or updates.
Also Read: What is SaaS (Software as a Service) in Cloud Computing?
4. Function as a Service (FaaS)
Function as a Service (FaaS), often referred to as serverless computing, allows you to execute code in response to specific events without worrying about the underlying infrastructure.
With FaaS, you can focus entirely on writing and deploying your functions, while the cloud provider handles server management, scaling, and maintenance.
Key Features:
- Event-driven execution: Code is triggered by events such as API requests, file uploads, or database changes.
- Cost-efficient (pay-per-execution): You’re only charged for the time your code runs, reducing unnecessary expenses.
- Automatic scaling: Resources adjust dynamically based on demand, ensuring efficient performance during high-usage periods.
Examples:
- AWS Lambda: Execute code in response to events like API calls or database updates.
- Google Cloud Functions: Build lightweight, event-driven microservices in the cloud.
Use Cases:
- Real-time file processing: Automate tasks like resizing images or processing uploaded documents.
- IoT applications: Process and respond to data from IoT devices in real time, such as sensor readings or alerts.
FaaS is ideal for developers building lightweight, event-driven applications, offering scalability and cost-efficiency without the need for server management.
Also Read: Top 10 IoT Real-World Applications in 2025 You Should Be Aware Of
5. Container as a Service (CaaS)
Container as a Service (CaaS) provides a platform for managing and deploying containers, which are lightweight software units that package code, dependencies, and runtime environments.
With CaaS, developers and IT teams can efficiently deploy, scale, and manage containerized applications without worrying about the underlying infrastructure.
Key Features:
- Simplified container orchestration: Automates container deployment, scaling, and networking using tools like Kubernetes.
- Scalability for container workloads: Seamlessly scales container resources based on demand, ensuring optimal performance.
- API-driven management: Offers APIs for easy integration and customization of container workflows.
Examples:
- Kubernetes: A powerful open-source platform for container orchestration.
- Docker Cloud: Simplifies deploying and managing containerised applications in the cloud.
Use Cases:
- Microservices architecture: Supports the deployment and management of modular, independent services for scalable and resilient applications.
- Continuous integration/continuous deployment (CI/CD): Streamlines testing and deployment cycles by leveraging containers for consistent environments.
CaaS is an excellent choice for teams embracing modern development practices like microservices and CI/CD, offering flexibility, scalability, and efficient resource management.
Also Read: What is Docker Container? Function, Components, Benefits & Evolution
6. Database as a Service (DBaaS)
Database as a Service (DBaaS) provides fully managed database solutions, eliminating the need for users to set up, maintain, or troubleshoot database infrastructure.
With DBaaS, businesses can focus on using their data effectively without worrying about the technical complexities of database management.
Key Features:
- Automated backups and updates: Ensures data security and keeps your database up-to-date with minimal effort.
- Scalable storage: Adjusts storage capacity dynamically to accommodate growing datasets.
- High availability: Built-in redundancy and failover mechanisms ensure reliable database performance.
Examples:
- AWS RDS: Offers managed relational database services with support for multiple database engines.
- Google Cloud SQL: Provides a fully managed relational database service for MySQL, PostgreSQL, and SQL Server.
Use Cases:
- Data-driven apps: Power applications that require robust and scalable databases for handling user data or transactions.
- Business analytics: Store and process large volumes of data for generating insights and reports.
DBaaS is ideal for businesses looking to streamline database management while maintaining high performance and reliability.
Also Read: DBMS Tutorial For Beginners: Everything You Need To Know
7. Disaster Recovery as a Service (DRaaS)
Disaster Recovery as a Service (DRaaS) provides cloud-based solutions to ensure business continuity during unexpected events like system failures, cyberattacks, or natural disasters.
By backing up data and IT infrastructure, DRaaS enables businesses to recover quickly and minimize disruptions.
Key Features:
- Rapid recovery times: Restores systems and data quickly to reduce operational downtime.
- Continuous data replication: Keeps data updated in real-time, ensuring an accurate backup at all times.
- Reduced downtime: Maintains business operations even in the face of major disruptions.
Examples:
- Zerto: Specializes in disaster recovery and data protection with continuous replication.
- VMware Site Recovery: Provides automated disaster recovery in a hybrid cloud environment.
Use Cases:
- Protecting critical business data: Safeguards sensitive data from loss due to hardware failure or cyberattacks.
- Compliance with disaster recovery policies: Helps organizations meet regulatory requirements for data protection and recovery.
DRaaS is essential for businesses that prioritize data security and operational continuity, offering peace of mind in the event of unforeseen incidents.
Also Read: What is Disaster Management? Importance, Stages, Guidelines, and More
8. Network as a Service (NaaS)
Network as a Service (NaaS) provides virtualized network infrastructure and services over the internet. It allows businesses to outsource networking tasks, such as connectivity, routing, and bandwidth management, eliminating the need for physical networking hardware.
Key Features:
- Flexible bandwidth allocation: Adjust network capacity on demand to handle varying workloads.
- Centralised network management: Simplify monitoring and managing networks through a single interface.
- Reduced hardware dependency: Replace costly physical hardware with cloud-based solutions.
Examples:
- Cisco Meraki: Offers cloud-managed networking solutions for secure and scalable connectivity.
- AWS Direct Connect: Provides a dedicated network connection to Amazon Web Services for improved performance.
Use Cases:
- Secure remote access: Enable remote employees to connect to company resources securely and efficiently.
- Optimising network performance: Improve the speed and reliability of business-critical applications with flexible, cloud-based networking.
NaaS is a cost-effective and scalable solution for businesses seeking to streamline their network operations while enhancing connectivity and performance.
Also Read: Computer Networking Basics: Network Types, Technologies, Topologies, Pros and Cons
9. Artificial Intelligence as a Service (AIaaS)
Artificial Intelligence as a Service (AIaaS) delivers AI tools and frameworks through the cloud, making advanced AI capabilities accessible without requiring in-depth expertise or significant infrastructure investment.
Businesses can leverage these services to integrate AI functionalities into their operations easily.
Key Features:
- Pre-trained machine learning models: Access ready-to-use models for common AI tasks like language processing and image recognition.
- Scalable AI infrastructure: Adjust resources dynamically to handle increasing workloads or large datasets.
- Customisable AI services: Tailor AI models and tools to meet specific business requirements.
Examples:
- IBM Watson: Provides a suite of AI tools for natural language processing, data analysis, and more.
- Google AI Platform: Offers end-to-end AI development tools, from data preparation to model deployment.
Use Cases:
- Sentiment analysis: Understand customer feedback and opinions by analysing text data.
- Image recognition: Automate tasks like detecting objects in photos or verifying identities.
AIaaS empowers businesses to harness AI capabilities quickly and efficiently, driving innovation and enhancing decision-making processes.
If you are interested in learning more about the use cases of AI in the real world, then explore upGrad’s free course on the applications of AI and enhance your knowledge!
Also Read: Future Scope of Artificial Intelligence in Various Industries
upGrad’s Exclusive Software Development Webinar for you –
SAAS Business – What is So Different?
10. Storage as a Service (STaaS)
Storage as a Service (STaaS) provides cloud-based storage solutions that allow businesses and individuals to store, manage, and back up data securely.
With STaaS, users can access their data anytime, anywhere, without worrying about physical storage limitations.
Key Features:
- On-demand storage capacity: Easily scale storage up or down to meet changing data requirements.
- Redundant storage for data protection: Data is replicated across multiple servers to prevent loss in case of failures.
- Integration with other cloud services: Seamlessly connect with applications for efficient workflows and data access.
Examples:
- Google Drive: Offers secure storage with collaboration tools for teams and individuals.
- Dropbox: Provides cloud-based file storage with easy sharing and syncing capabilities.
Use Cases:
- File sharing and backup: Store important files securely and share them with others easily.
- Archiving: Preserve large volumes of data for compliance or future reference without maintaining physical storage.
STaaS is an affordable and flexible option for managing data storage needs, providing reliability and accessibility for businesses and individuals alike.
Also Read: Best Cloud Storage Services: Future-Proof Your Data
11. Compliance as a Service (CaaS)
Compliance as a Service (CaaS) provides cloud-based tools and solutions to help organizations meet regulatory requirements and industry standards. It automates compliance processes, reducing manual effort and the risk of non-compliance.
Key Features:
- Automated compliance checks: Continuously monitor systems to ensure adherence to regulations.
- Risk management tools: Identify and mitigate potential compliance risks proactively.
- Detailed audit trails: Maintain comprehensive records of compliance activities for transparency and reporting.
Examples:
- TrustArc: Delivers privacy compliance solutions tailored to global standards like GDPR.
- LogicGate: Offers risk and compliance management software with customizable workflows.
Use Cases:
- Data privacy compliance (e.g., GDPR): Ensure data handling practices meet legal requirements.
- Audit preparation: Simplify the process of preparing for internal or external audits with detailed documentation.
CaaS enables organisations to stay compliant efficiently, minimising risks and saving time while maintaining trust with customers and stakeholders.
Also Read: GDPR Compliance and Why You Should Know About it as a Marketer?
12. Backup as a Service (BaaS)
Backup as a Service (BaaS) offers automated cloud-based solutions for securely backing up critical data. It ensures businesses can recover their data quickly in the event of data loss, hardware failure, or cyberattacks, providing peace of mind and operational continuity.
Key Features:
- Secure off-site storage: Data is stored in the cloud, protecting it from local hardware failures or disasters.
- Scheduled backups: Automates the backup process with regular, scheduled intervals to ensure data is always up-to-date.
- Rapid data restoration: Enables quick recovery of lost data to minimize downtime and disruption.
Examples:
- Veeam Backup: Provides advanced cloud backup and recovery solutions with robust security features.
- Carbonite: Offers scalable backup services tailored to small businesses and enterprises.
Use Cases:
- Small business data protection: Protect sensitive business data from accidental deletion or ransomware attacks.
- Enterprise disaster recovery: Quickly restore critical systems and data during large-scale disruptions.
BaaS is an essential service for businesses of all sizes, ensuring data is secure, accessible, and easily recoverable when needed.
Also Read: AI-Driven Cybersecurity: How AI Helps Protect Your Data?
13. Security as a Service (SECaaS)
Security as a Service (SECaaS) provides cloud-based security solutions, offering businesses comprehensive protection against cyber threats. It includes services like threat monitoring, malware detection, and identity protection, all managed and updated by the provider to ensure maximum security.
Key Features:
- Cloud-based threat detection: Continuously monitors for potential threats and vulnerabilities.
- Regular updates to security tools: Ensures that tools are always up-to-date to defend against emerging threats.
- Scalable security solutions: Adjusts resources based on the size and needs of the organization.
Examples:
- Symantec: Delivers robust threat intelligence and malware protection services.
- Palo Alto Prisma: Provides advanced cloud security solutions for network and application protection.
Use Cases:
- Identity protection: Safeguards sensitive user data with tools like multi-factor authentication.
- Malware detection: Detects and mitigates malicious software to prevent data breaches and system compromise.
SECaaS is an efficient and scalable way for businesses to bolster their security posture without the need for extensive on-premise resources.
You can also strengthen your knowledge about cybersecurity and its role in protecting business infrastructure through this upGrad free course on cybersecurity essentials!
Also Read: Anomoly Detection With Machine Learning: What You Need To Know?
14. Identity as a Service (IDaaS)
Identity as a Service (IDaaS) provides cloud-based solutions for managing user identities and access. It centralizes identity management, making it easier for organisations to secure and control access to their systems and applications.
Key Features:
- Single sign-on (SSO): Simplifies user access by allowing them to log in once for multiple applications.
- Multi-factor authentication (MFA): Adds an extra layer of security by requiring additional verification methods.
- Centralized identity management: Enables administrators to manage user roles and permissions from a single platform.
Examples:
- Okta: Offers robust identity management solutions with SSO and MFA.
- Microsoft Azure AD: Provides integrated identity services for enterprise applications and cloud platforms.
Use Cases:
- Secure enterprise authentication: Protects sensitive systems with advanced authentication methods.
- Role-based access: Assigns access levels based on user roles to ensure appropriate permissions.
IDaaS is essential for organizations seeking to enhance security, streamline user access, and simplify identity management in a cloud-driven environment.
Also Read: Top Azure Certifications for Career Advancement
15. Blockchain as a Service (BaaS)
Blockchain as a Service (BaaS) provides cloud-based solutions for building, hosting, and managing blockchain networks and applications. It allows businesses to leverage blockchain technology without the complexity of setting up and maintaining their own infrastructure.
Key Features:
- Managed blockchain infrastructure: Handles setup, maintenance, and updates for blockchain networks.
- Customisable smart contracts: Enables businesses to create and deploy tailored smart contracts to automate processes.
- Scalable blockchain networks: Offers the flexibility to scale blockchain solutions as business needs grow.
Examples:
- IBM Blockchain: Provides tools for building secure and transparent blockchain applications.
- Amazon Managed Blockchain: Simplifies the deployment and management of scalable blockchain networks.
Use Cases:
- Supply chain tracking: Ensures transparency and traceability in logistics and supply chains.
- Cryptocurrency applications: Develops and supports applications like digital wallets and payment systems.
BaaS makes blockchain technology more accessible, enabling organizations to focus on innovation while the provider handles the technical complexities.
Also Read: Blockchain Technology in Cryptocurrency: Benefits, Challenges & Structure
Types of Cloud Deployment Models
Cloud deployment models describe how cloud services are implemented and accessed. Each model offers distinct features and benefits, catering to different business needs such as scalability, security, and control.
The five primary deployment models—Public Cloud, Private Cloud, Hybrid Cloud, Multi-Cloud, and Community Cloud—allow organisations to choose the best approach based on their requirements.
Public Cloud
The public cloud is a shared environment where services are provided over the internet by third-party providers. It is cost-effective and widely used due to its accessibility and scalability.
Key Features:
- Shared resources available to multiple users.
- Low initial cost with pay-as-you-go pricing.
- High scalability to accommodate fluctuating demands.
Best Fit For:
- Startups and small businesses needing affordable infrastructure.
- Applications with unpredictable or variable workloads.
Examples:
- Amazon Web Services (AWS)
- Microsoft Azure
The public cloud is ideal for businesses seeking a cost-efficient, scalable solution for general workloads.
Also Read: What is a Cloud Server? Definition, Types, and How They Work
Private Cloud
A private cloud is dedicated to a single organization, offering enhanced control and security. It can be hosted on-premises or by a third-party provider.
Key Features:
- Exclusive use by one organization.
- Greater control over data and infrastructure.
- Customizable security and compliance measures.
Best Fit For:
- Businesses handling sensitive data, such as in healthcare or finance.
- Organizations with strict regulatory requirements.
Examples:
- VMware vSphere
- OpenStack
The private cloud is the best choice for organizations prioritising data security and regulatory compliance.
Also Read: Most Asked VMware Interview Questions And Answers - For Freshers and Experienced
Hybrid Cloud
A hybrid cloud combines public and private clouds, allowing businesses to enjoy the benefits of both. It enables data and applications to move between the environments as needed.
Key Features:
- Flexibility to optimize workloads across public and private clouds.
- Enhanced security for sensitive data in the private cloud.
- Cost-efficiency for non-sensitive workloads in the public cloud.
Best Fit For:
- Businesses balancing cost with security.
- Organizations with diverse workloads requiring different environments.
Examples:
- Microsoft Azure Hybrid
- Google Anthos
The hybrid cloud offers flexibility and cost optimization, making it ideal for businesses with varying workload requirements.
Multi-Cloud
A multi-cloud setup uses services from multiple cloud providers. It avoids vendor lock-in and allows organizations to select the best services from each provider.
Key Features:
- Redundancy to improve reliability and uptime.
- Flexibility to optimize costs and performance.
- Enhanced disaster recovery options.
Best Fit For:
- Large enterprises needing varied services.
- Businesses prioritizing reliability and avoiding dependency on a single provider.
Examples:
- AWS and Google Cloud combined
- IBM Cloud alongside Azure
Multi-cloud provides unmatched flexibility and reliability for organizations requiring diverse cloud services.
Also Read: Google Cloud vs AWS: Difference Between Google Cloud & AWS
Community Cloud
A community cloud is a shared infrastructure designed for a specific group or industry with similar requirements, such as compliance or operational goals.
Key Features:
- Shared costs and resources among the community.
- Customised for the group’s specific needs.
- Enhanced collaboration within the community.
Best Fit For:
- Government agencies sharing resources.
- Research organizations collaborating on projects.
Examples:
- Government Cloud Services
- Academic research clouds
Community cloud fosters collaboration and cost-sharing, making it perfect for industries with shared goals and standards.
Each deployment model offers unique benefits, and the choice depends on your organisation's priorities, such as cost, security, scalability, and compliance.
Also Read: How to Learn Cloud Computing in 2025: 5 Proven Steps to Master the Skills and Advance Your Career
With so many models available, how do they compare in terms of functionality and purpose? Here’s a look at how the main service models—like IaaS, PaaS, and SaaS—differ and when to use them.
Comparing Cloud Service Models: Key Differences and Use Cases
Cloud service models—Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS)—offer varying levels of control, scalability, and ease of use.
Each model serves distinct use cases, from custom application development to fully managed software solutions, helping businesses choose the right option based on their operational needs.
Service Models Comparison (IaaS vs. PaaS vs. SaaS)
When choosing between IaaS, PaaS, and SaaS, it's essential to understand their key differences and the use cases they serve. The following table provides a comparative overview to help you make informed decisions.
Service Model |
Use Case |
Key Features |
Popular Providers |
IaaS | Hosting websites, running custom applications | Scalable infrastructure, pay-as-you-go pricing | Amazon EC2, Google Compute Engine |
PaaS | Developing and deploying applications | Pre-configured tools, simplified deployment | Microsoft Azure App Service, Heroku |
SaaS | Productivity tools, CRM systems | Fully managed software, no setup required | Google Workspace, Salesforce |
Also Read: Deploying Machine Learning Models on Heroku
Deployment Models Comparison (Public vs. Private vs. Hybrid)
Different deployment models—Public, Private, and Hybrid Cloud—offer varying levels of security, scalability, and cost implications. The table below highlights these differences to assist in selecting the right model.
Deployment Model |
Security Level |
Scalability |
Cost Implications |
Public Cloud | Moderate | High, suitable for dynamic needs | Low initial cost, pay-as-you-go |
Private Cloud | High, with dedicated resources | Limited to organization’s capacity | High upfront investment |
Hybrid Cloud | Balances public and private security | High, flexible across workloads | Medium, combining public and private costs |
These comparisons provide a snapshot of how each service and deployment model aligns with various business goals, making it easier to match the cloud solution to your specific needs.
Also Read: Game-Changing Cloud Technologies for 2025
While each model has unique features, they all share common benefits like cost savings, scalability, and enhanced collaboration. Let’s explore the advantages they bring to both businesses and individuals.
The Benefits of Cloud Computing Models for Businesses and Individuals
Cloud computing models offer numerous advantages, making them essential for both businesses and individuals looking to optimize their operations and improve efficiency.
1. Cost Savings
- No need for expensive hardware and infrastructure.
- Pay-as-you-go pricing ensures you only pay for what you use.
- Reduces maintenance and operational costs through provider-managed services.
2. Scalability and Flexibility
- Easy scaling of resources to match workload demands.
- Accommodates growth or seasonal spikes without costly infrastructure changes.
- On-demand access to computing power and storage.
3. Enhanced Collaboration
- Enables remote access to files and applications, improving productivity.
- Supports team collaboration through shared tools and platforms.
- Real-time updates and file sharing streamline workflows across geographies.
4. Security and Reliability
- Offers great security features, including encryption and regular updates.
- Data redundancy ensures availability even in case of failures.
- Reliable backup and disaster recovery options minimise downtime.
These benefits can lead to greater efficiency and reduced costs, allowing businesses to stay competitive in a rapidly evolving digital landscape.
Also Read: What is DES (Data Encryption Standard)? DES Algorithm Explained
Despite their benefits, cloud computing models also come with challenges like security concerns and compliance issues. Here’s how to address these limitations effectively.
Overcoming the Challenges and Limitations of Cloud Computing Models
While cloud computing models offer significant advantages, they also come with challenges that businesses and individuals must address effectively.
Here’s how to overcome some common limitations:
1. Security Concerns
- Use multi-factor authentication (MFA) and strong access controls to safeguard data.
- Encrypt important information both in transit and at rest.
- Choose cloud providers with robust security certifications (e.g., SOC 2, ISO 27001).
2. Compliance Issues
- Partner with providers offering compliance-specific solutions for regulations like GDPR or HIPAA.
- Regularly audit cloud practices to ensure alignment with legal requirements.
- Maintain clear documentation for data handling and retention policies.
3. Downtime Risks
- Leverage multi-region deployments and failover mechanisms for uninterrupted service.
- Monitor cloud services using uptime tracking tools to mitigate disruptions quickly.
- Choose providers with strong Service Level Agreements (SLAs) guaranteeing high availability.
By proactively addressing these challenges, businesses can harness the full potential of cloud computing models while minimising risks.
Overcoming challenges is just one step; selecting the right model tailored to your needs is key. Here’s how to evaluate and choose the best cloud computing model for your goals.
How to Choose the Right Cloud Computing Model?
Selecting the right cloud computing model depends on understanding your business requirements and matching them with the strengths of each model.
It’s wise to assess your business needs when choosing a model. Here are a few considerations:
- Budget: Determine your financial capacity for cloud services, considering both initial and ongoing costs.
- Control: Evaluate how much control and customization you need over infrastructure and applications.
- Scalability: Consider whether your workloads are static or likely to fluctuate, requiring scalable resources.
- Security: Identify the level of data protection and compliance your organisation requires.
Use Cases for Each Model
Different cloud computing models cater to specific needs. Whether you’re looking for scalable infrastructure, a platform for app development, or ready-to-use software, understanding these use cases ensures you choose the model that aligns with your business goals.
1. IaaS (Infrastructure as a Service)
- Best for startups and businesses with fluctuating or unpredictable demands.
- Suitable for hosting websites, running custom applications, or building testing environments.
2. PaaS (Platform as a Service)
- Ideal for developers focused on building, testing, and deploying applications.
- Perfect for collaborative projects requiring pre-configured development tools.
3. SaaS (Software as a Service)
- Best for businesses needing ready-to-use software with minimal setup.
- Commonly used for CRM, office productivity tools, and team collaboration platforms.
By assessing your needs and aligning them with these use cases, you can choose the cloud computing model that maximizes efficiency, reduces costs, and meets your business goals.
Also Read: Types of Cloud Service Models & Which One Should You Choose?
Choosing the right model is vital, but so is building the skills to implement and manage them effectively. Discover how upGrad’s programs can help you gain expertise and advance your career.
How upGrad Helps You Master Cloud Computing?
upGrad offers industry-relevant programs designed to equip you with the skills you need to excel in cloud computing.
upGrad offers hands-on training with real-world projects, expert mentorship, and 100+ free courses. Join over 1 million learners to build job-ready skills and tackle industry challenges.
Here are some relevant courses you can check out:
Course Title |
Description |
Professional Certificate Program in Cloud Computing | A comprehensive course designed for professionals aiming to build a strong foundation in cloud technologies. |
Cloud Engineer Bootcamp | Get a brief but critical introduction to Linux, Python, and Cloud Computing where you cover the fundamentals. |
Fundamentals of Cloud Computing | Learn key cloud computing basics: storage, databases, networking, virtualization, containers, and architecture. |
Introduction to Cryptocurrency | This course offers a foundational understanding of cryptocurrency, including basics, investment strategies, and career opportunities. |
Fundamentals of Cybersecurity | Learn cybersecurity essentials, its importance today, key terms, and challenges in this course. |
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Frequently Asked Questions
1. What industries benefit most from cloud computing models?
Industries like healthcare, finance, e-commerce, and gaming benefit due to scalability, security, and compliance features.
2. Can I combine multiple cloud service models?
Yes, businesses often use IaaS for hosting, PaaS for development, and SaaS for productivity tools simultaneously.
3. What are the environmental benefits of cloud computing?
It reduces energy consumption and carbon footprints by optimising shared data centre resources.
4. How does cloud computing impact disaster recovery?
Cloud solutions like DRaaS ensure faster data recovery and reduced downtime compared to traditional methods.
5. What’s the difference between Multi-Cloud and Hybrid Cloud?
Multi-Cloud uses multiple providers; Hybrid Cloud integrates private and public clouds.
6. Are there limitations on the types of data that can be stored in the cloud?
Sensitive data may require compliance protocols depending on industry regulations like HIPAA or GDPR.
7. How do cloud providers ensure data redundancy?
They replicate data across multiple servers and locations to safeguard against hardware failures.
8. What skills are necessary to manage cloud infrastructure?
Knowledge of platforms, security, and tools like Kubernetes or Terraform is essential.
9. How does cloud computing handle compliance with local data laws?
Providers allow users to choose data centres in regions that meet local regulations.
10. What is the role of APIs in cloud computing?
APIs enable integration, automation, and customization between cloud services and applications.
11. Can cloud computing support edge computing use cases?
Yes, it offers low-latency solutions for IoT devices, autonomous vehicles, and similar use cases.
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