Courses
Cloudwards Video Courses New

Cloudwards.net may earn a small commission from some purchases made through our site. However, any earnings do not affect how we review services. Learn more about our editorial integrity and research process.

Top Cloud Computing Examples Based on Service Types and Models in 2024

The first thing you should know about cloud computing is the different categories of solutions. If you aren’t an IT professional, then the only way you can sift through all the terminology and jargon is by looking at cloud computing examples from each category and examining their differences.

Aleksander HougenBrett Day

Written by Aleksander Hougen (Co-Chief Editor)

Reviewed by Brett Day (Writer, Editor)

Last Updated: 2024-07-11T10:30:04+00:00

All our content is written fully by humans; we do not publish AI writing. Learn more here.

In the most basic sense, cloud computing refers to any resource, application or software component delivered to a client via the cloud. However, there are many different types of cloud services that vary wildly in their functionality and purpose. If you’re just starting to learn the ins and outs of cloud computing, then looking at cloud computing examples is crucial to helping you understand the differences between them.

Keep reading for many examples of cloud computing based on cloud service types, cloud computing models and different industries.

Cloud Computing: A Brief Overview

Cloud computing products like Microsoft Azure, serve as IaaS providers, offering a range of infrastructure including storage, computing power, networking, and virtualization. While these providers enable customers to create and manage applications that communicate with the service’s API, the responsibility for the entire lifecycle of such apps remains with the clients. 

Most large IaaS providers, including the ‘big three’ of Amazon, Microsoft, and Google, extend their offerings to include PaaS, CaaS, and FaaS solutions, which can complicate distinctions among the service types.

Cloud Storage Courses

Check out our cloud storage courses and grab a limited-time offer.
Registration available now!

Enroll Now

Cloud-based PaaS solutions, such as Google App Engine, take things a step further by hosting the actual applications themselves instead of just offering resources for rent. This gives developers a framework to work on when developing their own custom applications so they don’t have to worry about deployment.

Beyond PaaS, we have Function as a Service (FaaS) and Container as a Service (CaaS). CaaS is similar to PaaS in that it provides software developers with a framework to use for developing apps but lacks a managed runtime environment. FaaS is the most managed type of solution, where the user is only responsible for providing short code snippets and trigger conditions.

cloud service models
FaaS and CaaS solutions fall between PaaS and SaaS conceptually.

Finally, cloud vendors classed as SaaS solutions target the end user directly, where every part of the software is hosted by the provider. SaaS is the broadest of the three types, with examples ranging from cloud storage (like Dropbox) to video conferencing (like Zoom) or cloud-based collaboration software (like Google Workspace).

Every industry in the world makes use of cloud computing applications in some capacity. Whether it’s healthcare, education, banking or any other sector, cloud computing solutions are used to store data, collaborate on projects, and manage communication and team members. Without further ado, let’s take a look at some of the most popular cloud computing examples.

Examples of Cloud Computing Based on Cloud Service Types

Cloud service types differentiate between services based on their use cases, with most big providers offering something in every category. 

Take Amazon Web Services as an example — the S3 and Elastic Compute Cloud components are examples of IaaS, as they provide users with access to remote storage, computing power, virtual machines and hosting. 

On the contrary, AWS Elastic Beanstalk is an example of PaaS, as it provides developers with a framework for creating and deploying applications. In between IaaS and PaaS, you have CaaS solutions like AWS Fargate or App Runner. This service packages and deploys applications as “containers” that can run on any environment, but falls short of providing an entire development platform.

On a smaller scale, you have FaaS solutions (also known as serverless cloud computing) like AWS Lambda. These ones are aimed at event-driven applications that run a small function (or piece of code) in response to an external trigger. 

Because they cover any service that is hosted and delivered through the internet (or the cloud), examples of SaaS solutions are the most varied, ranging from Dropbox to Discord or any other online service.

The Big Three: Amazon Web Services vs Microsoft Azure vs Google Cloud

big three cloud applications
Amazon, Microsoft and Google — otherwise known as the “big three” of cloud computing companies — all have enormous cloud computing platforms that cover every type of cloud computing solution.

With the exception of SaaS, all types of cloud computing are dominated by three different cloud providers: Amazon, Microsoft and Google. Amazon has Amazon Web Services (AWS for short), Microsoft has Microsoft Azure and Google has the Google Cloud Platform (GCP). 

These services cover the entire spectrum of cloud computing types and offer different products and services depending on your needs. Each solution has hundreds of features that provide infrastructure, development tools, web hosting, application deployment and so much more.

What Are Some Examples of Cloud Computing Infrastructure as a Service (IaaS)?

Infrastructure as a Service (IaaS) refers to solutions that provide resources and infrastructure, such as cloud data storage, computing power and networking. Consumers pay for the amount of resources they use and can access the service through a web interface or an API. 

Popular examples of IaaS include: 

  • Amazon S3 (part of AWS)
  • Amazon EC2 (part of AWS)
  • Microsoft Azure
  • IBM Cloud
  • Akamai
  • Google Compute Engine (part of Google Cloud)
Amazon S3 & Amazon Elastic Compute Cloud (Part of AWS)

Amazon S3 and Amazon Elastic Compute Cloud (known as EC2) are the storage and computing components of AWS, which is the largest cloud computing provider in the world. S3 provides users pay-as-you-go cloud storage, while EC2 offers virtual machines, instances and processing power.

  • History: Initially focused entirely on web hosting, AWS was founded in 2002. In 2006, the service added both Amazon S3 and EC2 to its list of products. This marked its entry into the cloud computing space and, in many ways, set the standard for what modern cloud computing looks like. 
  • Features:Amazon S3 offers data storage and backup, while EC2 allows users to set up custom virtual machines or instances and pay for processing power (also known as “compute”) as they need it.
  • Benefits:The largest benefit of using Amazon S3 or EC2 is undoubtedly their integration with the wider AWS ecosystem. With more than 200 different apps and products, AWS is the gold standard for cloud computing features. Because of its wide adoption, it’s also very easy to find documentation and experts to help solve issues.
  • Drawbacks:The drawbacks of Amazon S3 and EC2 (and the larger AWS ecosystem) are related to its benefits. Since AWS has so many products and services, there’s a steep learning curve. It’s also a bit pricier than its competitors, and the billing structure can be confusing. Lastly, AWS often struggles with performance on its East Coast data centers due to overload.
  • Pricing:AWS offers a 12-month free tier with 5GB of storage, 750 hours per month with one VM instance and other integrated services. If you want more storage or compute, or you’ve used your 12 free months, then AWS charges for its services on a pay-as-you-go basis that varies depending on the rented infrastructure’s performance.
Azure Virtual Machines & Blob Storage

Microsoft Azure is the second biggest cloud computing platform and provides IaaS in the form of virtual machine computing power and object storage. These services are branded as Azure Virtual Machines and Azure Blob Storage, respectively.

  • History: Although the Azure platform was announced in 2008, the virtual machine and object storage functionality was added in 2010 as part of Windows Azure before it was renamed to Microsoft Azure in 2014.
  • Features: Microsoft Azure offers storage and computing infrastructure that integrates with the rest of the cloud computing suite and other Microsoft products such as .NET, Visual Studio and Active Directory.
  • Benefits: The biggest benefit of Microsoft Azure is its integration with all other Microsoft products and solutions. If your company or organization is already invested in the Microsoft ecosystem, whether that’s through .NET development or the Windows operating system, then Azure will easily integrate with your existing systems.
  • Drawbacks: The most obvious drawback to Microsoft Azure is its pricing, as it generally charges about 1.5 times what AWS or GCP does. It also requires quite a bit of setup and thought from the systems developer to ensure a solid foundation.
  • Pricing: You pay per GB of storage or per minute of CPU usage; prices also vary depending on the performance required. Azure’s free tier splits into two categories: some services are available for 12 months (750 hours of Windows or Linux VMs and 5GB of free storage), while others stay free forever (SQL database, functions, app service, etc.)

Google Compute Engine (GCE) & Google Cloud Storage (Part of Google Cloud Platform)

Rounding out the “big three” of cloud computing, we have the Google Compute Engine and Google Cloud Storage, both part of the Google Cloud Platform.

  • History: Google Cloud launched in 2008 — the same year as Microsoft Azure — but it wasn’t until 2010 that it added Google Cloud Storage to the platform. GCE didn’t launch until 2012.
  • Features: Google Compute Engine and Google Cloud Storage offer scalable storage and computing infrastructure, as well as predefined and custom virtual machines. Both services integrate with the wider Google Cloud ecosystem.
  • Benefits: Despite not having the same number of services as AWS or Azure, it still has far more integrations to take advantage of compared to a smaller niche service (more on these below). Google Cloud is also generally easier to learn and use than AWS or Azure, with many of its services having a simplified workflow.
  • Drawbacks: Being newer, Google Cloud has fewer services and products than its two big competitors. Its main drawbacks are its limited selection of programming languages and its documentation being harder to find when compared to other big providers. It also has a smaller global network of centers, and creating nonstandard or niche VMs can be a little cumbersome.
  • Pricing: Google Cloud charges based on resources used, be that storage or computing power. The price also depends on the type of instance or virtual machine you run. The free tier comes with one low-performance VM instance, 30GB-months of persistent storage and 1GB of outbound data transfer, plus limited use of other services within the Google Cloud Platform.

IBM Cloud

Leaving the “big three” behind, we get to our first niche cloud computing service on this list. IBM Cloud offers many of the same basic IaaS solutions as the previous three providers, such as virtual machines, storage and computing power — though with nowhere near the same number of services. It’s notable for its bare-metal cloud servers and industry-specific solutions.

  • History: Originally founded in 2005 as SoftLayer, IBM acquired the service in 2013 and repackaged it as IBM Cloud in 2017.
  • Features: Although it doesn’t have anywhere near the amount of services and tools as the previous examples, IBM Cloud offers some niche features not found elsewhere. This includes integration with IBM Watson, a long-running, mature AI-powered platform that can analyze data, convert speech to text, create custom neural networks and AI models, and more.
  • Benefits: IBM Cloud is mostly known for its bare-metal servers. It also specializes in solutions for the banking, finance and healthcare industries, with a focus on large enterprise solutions. Rather than reinventing the wheel, IBM Cloud allows multicloud integration with AWS, Azure and Google Cloud to make up for some of its shortcomings. Since IBM owns Red Hat, it also offers a slightly higher guaranteed uptime for its Red Hat Cloud integration.
  • Drawbacks: The main drawback of IBM Cloud is that it offers far fewer services and features than the “big three” providers if you’re not an enterprise-level company in one of its targeted sectors (finance, banking and healthcare). The pricing structure also makes it difficult to manage cloud costs over time.
  • Pricing: IBM Cloud offers a free tier with access to more than 40 of its services, including 25GB of object storage and 100,000 vCPU seconds of compute per month. If you need more, you can opt for a standard pay-as-you-go model or a committed-use plan, which is cheaper but ties you down to a minimum amount of monthly resources.

What Are Examples of Cloud Computing Platform as a Service (Paas)?

Often part of a larger IaaS provider, PaaS solutions are used for software development. They provide a framework of prebuilt software components that developers can use to create custom applications while the PaaS provider handles things like platform compatibility and deployment.

Examples of cloud computing PaaS solutions are: 

  • Microsoft Azure App Service
  • AWS Elastic Beanstalk
  • Google App Engine 
  • Salesforce Lightning
AWS Elastic Beanstalk

Elastic Beanstalk is Amazon’s PaaS offering and integrates with the wider AWS ecosystem.

  • History: AWS Elastic Beanstalk was initially released in 2011 as a way to provide easier access and use of its various AWS components.
  • Features: Elastic Beanstalk allows for managed access to AWS’ IaaS components (S3, EC2, CloudWatch, etc.) without having to manually configure and maintain each resource. It supports a wide range of platforms and languages, and it lets developers create and deploy applications more easily using AWS infrastructure and components.
  • Benefits: As part of the AWS ecosystem, the sheer number of features and abilities that Elastic Beanstalk offers is unmatched by any other PaaS provider. It supports a wide range of platforms and programming languages, and it’s easy to find documentation and expert support. Finally, it has better automatic scaling and load balancing options than its competitors.
  • Drawbacks: Like the rest of AWS, Elastic Beanstalk has a steep learning curve due to its sheer scale. While you don’t technically pay for Elastic Beanstalk itself, AWS’ underlying cloud infrastructure is often more expensive than other providers.
  • Pricing: As mentioned, Elastic Beanstalk is technically free. It’s included as part of the AWS free tier, but you have to pay for IaaS resources if you exceed the free limits.
Azure App Service

Like Elastic Beanstalk, the Azure App Engine is a PaaS framework for developing and deploying web applications. 

  • History: The Azure App Service was originally added to the overarching Microsoft Azure ecosystem in 2013 under the name “Azure Web Apps,” but it was rebranded in 2015.
  • Features: Azure App Service supports web app development with frameworks for PHP, ASP.NET, Java, Node.js and Python. You can deploy applications to Windows and Linux systems, and they automatically scale based on need. Azure App Service integrates with a host of other Azure services for authentication, virtualization, automation and more.
  • Benefits: The biggest benefit to the Azure App Service is familiarity for developers who are accustomed to the .NET programming ecosystem, as well as the ability to use other Azure services for Windows and Linux deployment. Its dedicated deployments for both Visual Studio and popular Java IDEs allow developers to keep using their favorite tools.
  • Drawbacks: Like the rest of Microsoft Azure, the App Service has a steep learning curve for beginners, especially for those who aren’t familiar with .NET architecture. Like Azure’s other services, it’s also generally more expensive than its big competitors.
  • Pricing: Azure App Service has a free tier with 60 CPU-minutes per day, 1GB of RAM and 1GB of storage that can host 10 apps. From there, you pay as you go depending on the tier you choose, starting at $0.013 per CPU-hour for the basic paid tier.
Google App Engine

Coming back to the “big three,” we have Google’s PaaS solution: Google App Engine, also known as GAE. 

  • History: Google App Engine was the first big PaaS solution on the market, releasing in 2008 as part of the initial launch of the Google Cloud Platform.
  • Features: Google App Engine provides developers with a managed development and testing environment that automatically handles deployment and scaling. It offers deep integration and uses other Google Cloud Platform services.
  • Benefits: One of the main benefits of Google App Engine is that it’s easier to use than other big PaaS solutions. It has a less punishing learning curve and a more streamlined approach to both scalability and deployment.
  • Drawbacks: Out of the “big three,” Google App Engine is the most limited in terms of supported platforms and languages. It also has fewer features in total due to the lower number of services included in GCP compared to AWS or Azure.
  • Pricing: Google App Engine is priced per hour of use, but the cost varies depending on the type of instance you’re using — higher performing instances will increase the hourly price. You can also use the App Engine on Google Cloud’s free tier, but with a limited selection of instance classes and usage hours per day.

What Are Examples of Cloud Computing Container as a Service (CaaS)?

CaaS falls somewhere between IaaS and PaaS. CaaS solutions provide easy deployment of applications by packaging everything the software needs to run into a standard container that’s compatible with most environments. This makes them more managed than pure IaaS, but not quite as much as the full frameworks provided by PaaS solutions.

Examples of cloud computing CaaS solutions are: 

  • AWS Fargate
  • AWS App Runner
  • Azure Container Apps
  • Azure Container Instances 
  • Google Cloud Run
AWS Fargate & App Runner

AWS Fargate is AWS’ container service and provides an easier way to deploy applications using the Amazon ECS and EKS infrastructure. Fargate is serverless but still comprises containerized applications, so it straddles the line between FaaS and CaaS. AWS also offers a service called App Runner, an even simpler environment intended for users with no prior cloud computing experience.

  • History: Fargate was added to the AWS platform in 2017. Amazon later added AWS App Runner in 2021.
  • Features: Amazon Fargate simplifies the AWS development process by packaging different components into standardized containers that can be deployed anywhere. App Runner abstracts it even further, making it better for simple use cases and those who lack cloud computing experience.
  • Benefits: Fargate saves developers from worrying about provisioning infrastructure or ensuring compatibility when deploying their apps. It specifically integrates with Amazon’s wider AWS infrastructure, essentially automating tasks you’d normally do using IaaS solutions like Amazon’s elastic storage (S3) and computing (EC2).
  • Drawbacks: Compared to the underlying IaaS solutions, Fargate is expensive. Its conveniently managed systems also come with less control over infrastructure and resources, which is crucial for some use cases. It’s less flexible and customizable than working with the components directly, which is especially true for App Runner. The price structure is also confusing.
  • Pricing: Both Fargate and App Runner charge for the amount of resources your apps utilize, whether it’s processing power, storage or RAM. The price varies depending on what virtual configuration you use, and it’s calculated in GB-hours and CPU-hours. There’s no access to either service on the AWS free tier. 

Azure Container Apps & Azure Container Instances

Microsoft also offers two separate CaaS products, namely Azure Container Apps (ACA) and Azure Container Instances (ACI). ACA is more heavily abstracted with things like load balancing, certificates and scaling automatically included. By contrast, ACI operates at a lower level of abstraction, requiring the developer to take a more active role in provisioning resources.

  • History: Out of the two CaaS solutions, Azure Container Instances came first in 2017, building on the now defunct Azure Container Service. ACA was introduced much more recently in 2022 to provide a managed way to indirectly access Kubernetes APIs.
  • Features: Azure Container Apps is built on Kubernetes and lets developers create microservices and event-driven applications that rely on multiple different services and dependencies. On the other hand, Azure Container Instances focuses on serverless applications that don’t rely on other components or services to function. 
  • Benefits: Aside from simplifying things like provisioning resources and scaling, ACA and ACI’s containers have much faster start-up times than regular virtual machines, greatly increasing performance for small apps and services. Where most CaaS solutions only support Linux, ACI is the only major one that also works on Windows.
  • Drawbacks: Like other CaaS solutions, the main drawback of both ACA and ACI is decreased control and flexibility compared to interacting with the underlying components directly.
  • Pricing: For ACI, you pay as you go for both storage and vCPU time. The same is true for ACA, but here you also have the option of billing per million requests made by your app. There’s no free access to ACI, but ACA provides the user with 180,000 vCPU-seconds, 360,000 GiB-seconds and 2 million requests each month for free.
Google Cloud Run

Unlike Amazon and Microsoft, Google offers a unified CaaS solution that is significantly more managed than its counterparts. This can cut both ways, either leading you to feel that “it just works” or causing frustration with the lack of control and insight into the backend.

  • History: Beta access Cloud Run was added to the Google Cloud Platform in April 2019 before it moved on to general availability for all GCP customers later that year in November.
  • Features: Google Cloud Run uses HTTP containers (rather than the more common Docker implementation) to deploy applications and to automatically scale and provision resources. Like AWS Fargate, Google Cloud Run is serverless, meaning it combines some of the features of FaaS with more traditional CaaS features. 
  • Benefits: Google Cloud Run is far more managed than its counterparts, making it an easier solution to learn and master. Because it uses HTTP requests, it also supports a much wider range of programming languages than either AWS or Azure’s CaaS solutions.
  • Drawbacks: Like most of GCP’s services, Google Cloud Run doesn’t offer the same degree of flexibility and control that its counterparts from Microsoft or Amazon do. 
  • Pricing: Google Cloud Run’s Standard tier (or Tier 1) offers slower routing at a lower cost and only charges based on vCPU-seconds and GB-seconds. The Premium tier has more powerful servers, but it costs more and also charges per million requests made to your container. The free quota gives you 450,000 GB-seconds/240,000 vCPU-seconds on Tier 1 and 375,000 GB-seconds/200,000 vCPU-seconds on Tier 2, as well as 2 million requests.

What Are Examples of Cloud Computing Function as a Service (FaaS)?

FaaS is the most lightweight of the cloud computing types. Often described as serverless computing, FaaS solutions don’t allow for any kind of access to hardware or infrastructure — they simply take in code (aka the function) that is then set to run in response to a trigger or event.

Examples of cloud computing FaaS solutions are: 

  • AWS Lambda
  • Azure Functions 
  • Google Cloud Functions
AWS Lambda

AWS Lambda is Amazon’s FaaS solution and is the most mature service of its kind.

  • History: AWS Lambda was released in 2014 and is considered to be the first fully formed FaaS solution to enter the market.
  • Features: AWS Lambda allows developers to deploy code in Java, Go, PowerShell, Node.js, C#, Python or Ruby, which waits for an event to trigger. This code (or function) can then interact with over 200 of AWS’ other services.
  • Benefits: Some benefits of AWS Lambda are its fast start-up times and a high maximum timeout for requests (15 minutes), making it very suitable for small tasks and larger batch jobs. It’s also a highly flexible solution with lots of customizable options for developers to tweak.
  • Drawbacks: Because of its high degree of flexibility, AWS Lambda can have a steeper learning curve depending on your prior experience. It also doesn’t include HTTP integration by default (it’s billed as a separate service), which is one of the most common types of endpoints for FaaS solutions.
  • Pricing: Lambda is priced per request and per GB-second of compute time. The free tier includes 1 million requests and 400,000 GB-seconds per month. After those resources are used, it costs $0.20 per 1 million requests and $0.00001667 for every GB-second.

Azure Functions

Microsoft quickly followed Amazon’s lead by releasing Azure Functions.

  • History: The preview build for Azure Functions released in March 2016, followed by the full version later that year in November.
  • Features: Azure Functions offers the same functionality as Lambda — namely event-driven serverless compute service — but instead, it integrates with the overall Azure ecosystem, which is sizable but not as expansive as AWS. Azure supports C#, Python, Node.js, Java, Powershell, Go and Typescript, but notably lacks native support for Ruby.
  • Benefits: Azure Functions’ max timeout is even longer than Lambda’s (30 minutes), and it has much of the same flexibility and customization. It also has a better HTTP integration that streamlines the process of setting up web-based endpoints.
  • Drawbacks: Microsoft Azure has start-up times that are notably slower than both of its main competitors, which can greatly impact performance if you’re running a lot of small jobs.
  • Pricing: Azure Functions is billed in the same way as Lambda, calculating the cost based on requests and resource consumption. The similarities don’t stop there — the free tier offers an identical amount of requests and GB-seconds, and the prices per request and GB-second are the same once you exceed the free limit.
Google Cloud Functions

Once again, we’ll use Google to round out our list of examples with Google Cloud Functions.

  • History: Google Cloud Functions is the youngest of the three big FaaS solutions, launching as a beta in 2017 that was followed by a full release in 2018.
  • Features: Google Cloud Functions supports code written in Node.js, Python, Go, Java, C#, Ruby and PHP. While Azure has added support for Go (developed by Google), Cloud Functions doesn’t support Microsoft’s PowerShell.
  • Benefits: Ease of use has become a theme for Google’s solutions, and Google Cloud Functions is significantly more user-friendly and easy to learn than the two aforementioned services. It also has a very streamlined HTTP integration that makes it simple to set up endpoints.
  • Drawbacks: Perhaps due to its focus on ease of use, Google Cloud Functions doesn’t have the same amount of advanced features or customizability as Lambda or Azure. It also has a lower max memory (capping out at 8192MB) and a shorter max timeout (nine minutes).
  • Pricing: Google Cloud Functions’ free tier is more generous than AWS and Azure’s, with 2 million free requests per month (though the free compute limit is the same at 400,000 GB-seconds). Once past the free tier, Google Cloud Functions charges double for requisitions at $0.40 per 1 million, but compute time is cheaper at $0.0000025 per GB-second.

What Are Examples of Cloud Computing Software as a Service (SaaS)?

Of all the cloud computing types, SaaS solutions are by far the most ubiquitous. Salesforce CRM — launched in 1999 — is often considered the first “pure” SaaS solution. Since then, the market has grown exponentially, to the point where most new software operates at least partially on a SaaS model.

Some well-known examples of SaaS solutions are: 

  • Google Workspace
  • Zoom
  • Slack
  • Dropbox
  • Salesforce CRM
Salesforce CRM

Salesforce CRM is the original SaaS platform and provides businesses with a tool to manage customer interactions and relations.

  • History: Founded in 1999 by a former Oracle executive, Salesforce pioneered the SaaS space with its CRM solution. Salesforce acquired many other software companies over the years, including Heroku and Slack.
  • Features: Salesforce CRM offers a customizable cloud-based platform that enables users to communicate with customers, analyze data and manage relationships with other businesses, vendors and services.
  • Benefits: Salesforce is a mature and comprehensive CRM platform that comes with plenty of functionality covering most business scenarios. It’s much easier to scale compared to traditional software, and many repetitive tasks can be automated.
  • Drawbacks: Since it’s been around for a while, getting started with Salesforce can be difficult, as all its different components have a steep learning curve. Customer data is stored remotely and can be accessed only with an internet connection, so it might not be suitable for businesses that handle highly sensitive data or are based in places with poor connectivity.
  • Pricing: Salesforce offers a range of cloud-based software programs depending on use case, but the basic CRM suite starts at $25 per-user, per-month.
Zoom Video Conferencing

Zoom is a communication tool that specializes in video conferencing but also offers instant messaging and Voice over IP (VoIP).

  • History: Zoom originally launched in 2012, but it wasn’t until 2020 and the COVID-19 pandemic that it became a household name. In the first two months of 2020, the service gained more new users than it had in the entirety of 2019, quickly becoming almost synonymous with remote work.
  • Features: Zoom is a relatively simple cloud-based software platform. It mainly offers video conferencing with meetings capable of hosting up to 1,000 attendees and lasting 30 hours on the most expensive plan. Zoom also offers a mail and chat client, a notes app, cloud storage and an AI companion, among other integrated services.
  • Benefits: Zoom supports a larger number of participants for its video calls than most comparable providers. It’s also very easy to use and offers a wide range of supporting features like screen sharing, breakout rooms and polls.
  • Drawbacks: Privacy concerns have been raised about Zoom — in particular, it settled a lawsuit in 2021 over sharing user data with unauthorized third parties, and it changed its terms of service in 2023 to allow the use of customer’s video and audio to train AI.
  • Pricing: Zoom has a fairly limited free plan, restricting users to 40 minute meetings, which is short compared to alternatives. Paid plans start at $15.99 per user per month and can add up quickly.
Google Workspace

Google Workspace is one of the most widely used SaaS solutions in the world. If you’re on the internet, chances are you have an account in some form. This includes Gmail, Google Drive, Chrome, Google Docs and more. Google Workspace has gone through many changes and updates throughout the years, to the point where it’s unrecognizable from its beginnings.

  • History: Google Workspace dates back to the 2006 launch of “Google Apps for Your Domain” (shortened to “Google Apps”), which had Gmail and a few other apps like beta versions of Google Calendar and Google Docs. Google Drive added cloud storage in 2012, which was unified with Gmail’s storage in 2013. The service rebranded to GSuite in 2016 before rebranding again as Google Workspace in 2020.
  • Features: Because of its many apps, Google Workspace has a wide range of features including communication (Gmail, Google Chat and Google Contacts), cloud storage (Google Drive), document collaboration (Google Docs, Slides and Sheets), note-taking (Google Keep) and video calls (Google Meet).
  • Benefits: The two biggest benefits of Google Workspace are its widespread use and the fact that you can use it entirely for free unless you need more storage. The collaboration platform is easy to use and simplifies data sharing, communication and planning in several areas.
  • Drawbacks: Privacy is the greatest drawback to any Google product. The company is well known for using customer data to improve its algorithms and ad platform, which makes it unsuitable for any confidential or sensitive data or processes.
  • Pricing: Most Google Workspace services are free — examples include Gmail, Google Docs and Google Keep — but if you want more than 10GB of storage, you need to sign up for a paid plan starting at $1.99 per month.
Slack Virtual Workspace

Slack is another communication solution focused on businesses and teams. Whereas Zoom specializes in video, Slack is primarily about text-based communication.

  • History: Slack was first released in 2013 after IRC initially developed it to be the communication tool for an online game called Glitch. After the game was abandoned, the product was renamed Slack, an acronym for the phrase “Searchable Log of All Conversation and Knowledge.”
  • Features: Slack offers most basic communication features, including direct messages, multi-user channels, @mentions, custom user statuses, file-sharing, reactions and more. 
  • Benefits: A huge benefit of Slack is that it’s widely adopted, so many people already know how to use it, which makes it easier for teams to implement. All of its core features are available on the free version, so you can test it out and see if it’s the right choice before committing.
  • Drawbacks: The biggest drawback to Slack is its high price and the limitations imposed on free plans. It also has inconsistent video call quality and a disappointing privacy policy.
  • Pricing: As mentioned, Slack is expensive. There’s a free plan, but you’re limited to 90 days of conversation history, 10 external integrations, and 1:1 video or audio calls only. For those wanting to get around these limits, the cheapest paid plan starts at $8.75 per user per month, which can quickly balloon into a huge cost for large teams.

What Are Cloud Computing Examples Based on Cloud Deployment Model?

Another way to categorize cloud computing solutions is to look at their deployment model. This refers to how the solution is delivered to the user and who can access it. There are four types of deployment models: public, private, hybrid and community.

cloud deployment models graphic
Instead of categorizing cloud-based services based on use case,
you can look at how they’re deployed and accessed.

We can categorize the various examples of cloud computing based on deployment model as public, private, hybrid and community. These examples include: 

  • Public clouds, like Google Workspace or AWS
  • Private clouds, like Hewlett Packard Enterprise or VMware
  • Hybrid clouds, like Infinidat or Ensono
  • Community clouds, like Cisco or Cloud4C

What Are Examples of Public Cloud Computing?

Examples of public cloud computing are: 

  • Google Workspace
  • Amazon Web Services
  • Dropbox
  • Microsoft Azure 

Public cloud services are the most common, as they are premade environments that anyone who signs up can access. The resources of public clouds are all shared between its users and allocated as needed.

What Are Examples of Private Cloud Computing?

Examples of private cloud computing are solutions such as: 

  • Hewlett Packard Enterprise
  • Oracle Cloud Infrastructure
  • Dell Technologies Cloud
  • VMware Cloud 
  • IBM Cloud

Predictably, private cloud computing is the opposite of the public version. Private clouds are tailor-made for a specific company or organization and often come with significant support for maintenance and upgrades. Unlike public clouds, the resources on a private cloud can only be used by a single organization and aren’t shared with other users.

What Are Examples of Hybrid Cloud Computing?

Examples of hybrid cloud computing are: 

  • Infinidat
  • Ensono
  • Threat Stack 
  • DataCore Software

Hybrid clouds take the best of both worlds by combining public and private clouds into a single solution. This type is commonly used by users who don’t want to expose sensitive data and workflows to a public cloud, but still want to migrate less sensitive business processes and data off-premises. 

What Are Examples of Community Cloud Computing?

There aren’t any solutions dedicated entirely to community cloud computing, but not all private and hybrid clouds are capable of accommodating a community cloud. Examples of solutions that can offer community cloud computing are: 

  • Cisco
  • Cloud4C
  • Hewlett Packard Enterprise

Community clouds are essentially private clouds that are shared or pooled between multiple companies or organizations. This reduces the cost for each participant in the community cloud and also ensures that resources and infrastructure don’t “go to waste” by sitting idle when nobody is using them. 

What Are Examples of Cloud Computing in Different Industries?

Virtually every industry in existence uses cloud computing to a certain degree, though some use it more than others. Common examples of cloud computing in different industries include: 

  • E-learning and collaboration platforms in education
  • Big data analytics in banking and finance
  • Customer relationship management systems in retail
  • Telemedicine solutions in healthcare

Examples of Cloud Computing in Education

Cloud computing has become increasingly common in education. Examples include remote classrooms with Zoom or other video conferencing software, as well as online learning platforms like Google Classroom and Instructure, which provide a platform for students and teachers to submit and grade assignments. 

There are also sites like Kahoot! that host online educational games that allow many people to join and collaborate.

Examples of Cloud Computing in Healthcare

Examples of cloud computing in healthcare include telemedicine solutions like Mend.io and Doxy.me, as well as systems that manage electronic health records like Medsphere. Another example involves solutions that process data for more accurate diagnoses. Companies like Pfizer also use cloud computing to research and test new pharmaceuticals.

Examples of Cloud Computing in Retail

Cloud computing is widely used in retail for CRM systems, SAP deployment and data analytics. These examples comprise chains like Zalora and Petco, which employ data analytics solutions to personalize user experiences on their websites, or Morrisons moving its contact center to AWS Connect.

Examples of Cloud-Based Social Networking Websites

Unsurprisingly, all social networks operate on cloud computing infrastructure. Examples of social networks that use cloud computing include Facebook, Twitter, LinkedIn, Instagram and others.

Examples of Cloud Computing in Banking

Banks use cloud computing to run their financial services, analyze data and offer software solutions to customers. 

Here are some examples of cloud computing in banking: 

  • Wells Fargo operating on a mix of Azure and Google Cloud
  • The Bank of America partnering with IBM Cloud
  • The Commonwealth Bank running the largest VMWare Cloud in the world
  • DBS Bank partnering with Oracle to build a private cloud

The Future of Cloud Computing

Although it’s an old concept, modern cloud computing only really found its legs in the 2000s with the release of AWS and Amazon S3. This rapid growth makes it difficult to predict where the sector will go in the future, but we can make some educated guesses:

  • Artificial Intelligence & Machine Learning: Generative AI and machine learning have exploded into public consciousness recently. Although large cloud computing solutions have been using machine learning for a while, we foresee providers investing even more into this space going forward.
  • Multicloud Solutions: As the cloud computing space continues to mature, we expect to see more possibilities for integration between clouds as industry standards for the underlying infrastructure are solidified and further developed.
  • More Hybrid Clouds: Similar to the last prediction, we think hybrid cloud solutions will become more popular as more industries shift to a cloud-based approach, leaving pure on-premise solutions behind. As cloud adoption increases, the need for hybrid solutions will grow.
  • Low-Code & No-Code Solutions: As cloud computing solutions have matured, they’ve added tools that require less actual coding ability to use. CaaS and FaaS products already simplify the cloud computing process greatly, but we wouldn’t be surprised to see more tools approaching no-code software like Make.com, Zapier and IFTTT.

Final Thoughts

That concludes our list of examples of the different cloud computing solutions based on their type, deployment model and industry. If you’ve made it all the way down here, we hope you’ve gained a greater understanding of what the different terms mean and how they overlap.

What did you think of our cloud computing examples? Do you think we missed any big or important providers in any of our categories? Let us know in the comments below, and as always, thank you for reading.

FAQ: Examples of Cloud Computing 

  • There are five main types of cloud computing solutions: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Container as a Service (CaaS), Function as a Service (FaaS) and finally, Software as a Service (SaaS).

  • Yes, cloud computing is generally safe. In fact, cloud platforms sometimes offer enhanced security compared to on-premise solutions, depending on how things are managed.

  • Yes, everything on the cloud needs to be backed up by some sort of physical server based somewhere in the world. Usually these remote servers are located in enormous server farms in geographically suitable areas that provide cheap electricity for cooling.

  • Migrating from an on-premise solution to a cloud-based one can lead to cost savings, greater scalability and increased productivity. It also allows remote employees to gain easy access to tools and data that would otherwise require a VPN connection to a private network.

  • Some typical real-world examples of cloud databases are employee files, business records and lists of customer data and transactions.

↑ Top