A few years ago, “the cloud” sounded abstract. Today, cloud computing platforms are simply where your files live, your apps run, and your customers connect with you.
If you are a freelancer, IT beginner, or small business owner, understanding the latest cloud computing platforms helps you avoid overspending, improve reliability, and scale without stress. This guide walks you through the major options in plain language so you can pick a platform that fits the way you work.
You will see the term cloud computing platforms used a lot here. Think of a cloud platform as the operating system and hardware running in someone else’s data center, delivered to you over the internet with pay as you go pricing. It lets you skip buying servers and instead rent exactly what you need when you need it (Akamai).
Before you dive into specific providers, you may want a quick refresher on how cloud computing works behind the scenes and why it is different from traditional hosting.
1. Amazon Web Services (AWS)
If cloud computing platforms were cities, AWS would be the giant, always-busy capital. It is the most widely used cloud platform in the world, with more than 200 fully featured services and the largest global network of data centers (Varonis). In 2024 alone, AWS generated over US$100 billion in revenue, which shows how central it has become for businesses of all sizes (Technology Magazine).
What AWS is best at
AWS covers almost everything you can imagine in the cloud. A few core building blocks you will see mentioned often include:
- Amazon EC2 for virtual servers on demand
- Amazon S3 for durable, low cost cloud data storage
- AWS Lambda for serverless computing, where you only pay when your code runs
- Amazon RDS for managed databases
These services sit on top of a global infrastructure in more than 30 regions, so you can place your applications closer to your users, reduce latency, and deliver a faster experience worldwide (CloudOptimo).
AWS is especially strong if you care about:
- Very broad service choice
- Mature tooling and documentation
- Advanced security and compliance
Cloud providers like AWS reach massive economies of scale by serving hundreds of thousands of customers, which helps them keep per unit costs low and pass savings to you through pay as you go pricing models (AWS Whitepapers).
When AWS is a good fit for you
AWS can suit a one person startup or a fast growing company, but you will benefit most if you:
- Expect to scale quickly and want room to grow
- Need specific services like machine learning tools, data lakes, or content delivery
- Want fine grained control over your infrastructure
You can start simple with a single EC2 instance or a static site in S3, then layer on more services as you grow. The main tradeoff is that AWS has a learning curve, especially if you are new to cloud concepts.
2. Microsoft Azure
If your world already runs on Microsoft, such as Windows, Office, or SQL Server, Azure can feel like a natural extension of what you have. Azure is the second largest cloud computing platform after AWS, but it is growing faster, used by more than 95 percent of Fortune 500 companies (BMC).
Where Azure shines
Azure delivers a broad set of infrastructure and platform services, similar to AWS, such as:
- Azure Virtual Machines for compute
- Azure Blob Storage for object storage
- Azure Kubernetes Service for running containers
- Azure SQL Database for managed relational databases
Azure also integrates very closely with products like Microsoft 365 and Dynamics 365, which makes identity, access control, and collaboration smoother if your business already lives in that ecosystem (Technology Magazine).
A few reasons you might lean toward Azure:
- You use Windows Server and Active Directory and want tight integration
- You prefer hybrid setups, where some systems stay on premises and others move to the cloud
- You want potentially lower on demand prices, especially if you have Microsoft software licenses already
Research shows that Azure often has the lowest on demand pricing among the big three cloud providers, and existing Microsoft customers can unlock additional savings when migrating workloads to Azure (BMC).
Who Azure works well for
Choose Azure if you:
- Run a small business built around Microsoft tools
- Need to connect office based servers with new cloud apps
- Want to experiment with AI through offerings like Azure AI and Azure OpenAI Service
Azure can be slightly easier to adopt for teams that already speak “Microsoft” in their daily operations.
3. Google Cloud Platform (GCP)
Google Cloud Platform is the data nerd of cloud computing platforms. While it is smaller than AWS and Azure by market share, it is the fastest growing of the three and is well known for data analytics, machine learning, and high performance networking (BMC).
Why Google Cloud stands out
Under the hood, Google Cloud uses the same infrastructure that runs Search and YouTube. This backbone powers services like:
- Compute Engine for virtual machines
- BigQuery for lightning fast, serverless data warehousing
- Google Kubernetes Engine (GKE) for container orchestration
- Cloud Storage for object storage
Google played a major role in popularizing Kubernetes, and GKE is still considered a standard choice for modern container based apps (Technology Magazine).
You might prefer Google Cloud if you:
- Do a lot of data analytics or business intelligence
- Build AI or machine learning into your products
- Value clean networking design and global connectivity
Google Cloud operates in over 35 regions and 140 availability zones, which gives you good coverage for global users while focusing on performance and reliability (CloudOptimo).
Who should consider GCP
GCP is a strong option if you are:
- A startup building data heavy apps
- A freelancer offering analytics or AI services
- A small team comfortable with Google’s developer tools
If you like the way Google designs products, you will probably appreciate the developer experience on this platform.
4. CoreWeave and specialized GPU clouds
While AWS, Azure, and Google Cloud dominate the general cloud market, specialized players have emerged for specific needs. One standout is CoreWeave, which focuses on high performance GPU infrastructure for AI and machine learning workloads.
What makes CoreWeave different
CoreWeave has grown quickly during the generative AI boom by offering large scale access to the latest Nvidia GPUs and related hardware. Its main strengths are:
- Easy access to powerful GPUs that can be scarce on general clouds
- Infrastructure tuned for AI training and inference at scale
- Pricing models designed around GPU intensive workloads
In the 12 months to March 2025, CoreWeave generated US$2.71 billion in revenue, which shows how much demand exists for dedicated AI infrastructure (Technology Magazine).
When a niche GPU cloud makes sense
You may not need a provider like CoreWeave for everyday websites or simple web apps. However, it can be a strong fit if you:
- Train large machine learning models regularly
- Run image, video, or generative AI workloads
- Need more GPU availability than big providers can offer on demand
For many small businesses and freelancers, using a large general cloud plus a specialized GPU provider for AI workloads is becoming a practical multi cloud strategy.
5. Platform as a Service (PaaS) options
So far, you have seen mostly infrastructure as a service, where you manage virtual machines, storage, and networks yourself. If you want to skip server management and focus on code, a Platform as a Service (PaaS) might be easier.
A PaaS gives you a ready made environment to build, test, and run applications without touching the underlying servers, operating systems, or middleware (Akamai).
Google App Engine
Google App Engine (GAE) is one of the classic PaaS options. You write your web app in languages like Python, Java, or Go and deploy it to App Engine. Google automatically:
- Scales your app up or down based on traffic
- Handles load balancing and resource allocation
- Manages patching of the underlying infrastructure
This lets you focus almost entirely on application logic instead of capacity planning (GeeksforGeeks).
Force.com from Salesforce
Force.com, built by Salesforce, is another PaaS platform that targets business applications. It powers Salesforce.com, one of the leading software as a service CRM tools, and lets you:
- Build custom apps on top of Salesforce data
- Use visual tools and prebuilt components
- Create workflows, dashboards, and social style enterprise apps
For small businesses that already rely on Salesforce, Force.com can be a way to extend CRM data into custom tools without building everything from scratch (GeeksforGeeks).
When PaaS is a good fit
PaaS is ideal if you:
- Do not want to manage servers or operating systems
- Are building web or mobile backends and prefer a managed stack
- Value faster development cycles over low level control
Just keep in mind that you will trade some flexibility for convenience, and you may be more closely tied to one vendor’s ecosystem.
6. Serverless computing platforms
Serverless computing takes the PaaS idea a step further. Instead of running long living servers, you write small functions that run only when triggered, such as by an HTTP request or a queue message. The provider handles all scaling and you are billed only for actual execution time.
Serverless makes it easier to scale quickly and can be simpler to manage than PaaS, but you will have less control over the runtime environment (Akamai).
Examples you will encounter
Most cloud computing platforms offer some serverless option, for example:
- AWS Lambda as part of AWS
- Azure Functions on Microsoft Azure
- Cloud Functions on Google Cloud
Common uses include API backends, scheduled jobs, lightweight data processing, and event driven workflows. For small businesses, serverless can be attractive because you pay only for what you actually use, which fits nicely with variable traffic patterns.
When serverless is worth exploring
Consider serverless if you:
- Have workloads that are bursty or unpredictable
- Need to prototype quickly without thinking about capacity
- Want to minimize idle costs for low traffic services
If you already maintain a more traditional server based app, you can still adopt serverless gradually, for example by moving background jobs or specific features into functions.
7. Public vs private cloud platforms
So far, most of the platforms discussed are public clouds, where many customers share the same physical infrastructure but run isolated virtual machines or containers. Public cloud platforms offer almost unlimited scalability and are typically the most cost effective option, although you are sharing underlying hardware with others (Akamai).
In contrast, private cloud platforms provide a single tenant environment dedicated to one organization. This path offers higher control and potentially stronger security but involves more investment and less elasticity than public clouds (Akamai).
For freelancers and small companies, public cloud is usually the practical choice. Private cloud tends to make sense for larger organizations with strict regulatory requirements or very specific control needs.
8. Multi cloud and unified security
As cloud usage grows, many organizations spread workloads across multiple providers. In 2024, multi cloud adoption became a major trend as enterprises used AWS, Azure, and Google Cloud together to improve availability, avoid vendor lock in, and manage risk (CloudOptimo).
Why multi cloud is growing
Using more than one cloud provider can help you:
- Avoid depending on a single vendor
- Place workloads in the region or platform where they run best
- Use provider specific strengths, such as AI tools on one cloud and databases on another
However, a multi cloud setup can create fragmented visibility and inconsistent security policies if you rely only on each provider’s built in tools. To address this, more organizations use unified security platforms that sit across AWS, Azure, and Google Cloud to provide consistent controls and centralized monitoring (Varonis).
If you are just starting out, it makes sense to begin with a single primary cloud. As your needs mature, you can add a second provider for specific workloads and bring in multi cloud security and cost management tools.
9. How cloud platforms help your bottom line
You have seen individual platforms and features. It helps to zoom out and look at why cloud computing platforms are appealing financially and operationally.
Cloud computing lets you swap heavy upfront capital expenses for variable operating expenses. Instead of buying servers that may sit idle, you pay only for the computing resources you consume (AWS Whitepapers). This is particularly helpful if your workload changes with seasons, promotions, or client projects.
Because providers like AWS operate at massive scale, they can offer lower per unit costs than most companies can achieve on their own, while delivering pay as you go pricing that reflects actual usage (AWS Whitepapers).
Beyond cost, cloud computing platforms support:
- Scalability and flexibility. You can scale resources and storage up or down quickly, which avoids both overprovisioning and performance bottlenecks (Google Cloud).
- Faster time to market. Developers can spin up instances, deploy new versions, and experiment without long procurement cycles, which speeds up product development and experimentation (Google Cloud).
- Advanced security. Features like Zero Trust models, AI powered threat detection, and centralized management consoles can help strengthen your overall security posture if used correctly (Google Cloud).
Global cloud infrastructure services reached about US$330 billion in 2024, a jump of US$60 billion from the prior year, powered largely by generative AI technologies (Technology Magazine). That level of investment means the tools you use keep improving, often without extra effort from you.
To stay on top of your own spending, you will want basic cost management practices, such as tagging resources and reviewing usage reports regularly. Cloud pricing is flexible, but unmanaged usage can still lead to surprises (TechTarget).
10. Choosing the right platform for you
With so many cloud computing platforms available, it helps to narrow the choices based on what you actually need rather than every possible feature.
Use this quick guide as a starting point:
| Your situation | Cloud direction to explore |
|---|---|
| You want maximum flexibility and lots of services | Start with AWS |
| You are already deep in Microsoft tools | Consider Microsoft Azure |
| You care most about analytics and AI | Look closely at Google Cloud |
| You train large AI models or need many GPUs | Explore CoreWeave plus a general cloud |
| You want to focus on code, not servers | Try PaaS like Google App Engine or Force.com |
| You have spiky or unpredictable workloads | Add serverless options like AWS Lambda or Cloud Functions |
If you are unsure, pick one major provider, launch a small project, and learn by doing. Cloud platforms make it easy to start small, test ideas, and scale successful ones without committing to heavy upfront infrastructure.
As your experience grows, you can refine your mix of services, bring in additional clouds if needed, and build a stack that matches how you and your customers actually work.