If you have no reason to choose otherwise, start with AWS: it has the largest market share and the most learning material. Choose Azure if the employers you want run on Microsoft, and GCP if you are heading into data and ML work at companies that use it. The concepts transfer, so the first cloud matters less than learning it properly.
What people tell me
I want to learn cloud computing to improve my job chances, but I keep going back and forth between AWS, Azure and Google Cloud. Each has its own courses and certifications and I do not want to waste time learning the wrong one. People online give confident but opposite advice, and I do not know how to decide.
A composite of the messages behind this question, with personal details left out.
Key takeaways
- Most core ideas transfer: compute, storage, networking, identity, managed databases and billing.
- AWS is the safest default by market share and learning material.
- Let the job posts you actually want decide if they clearly favour one provider.
- Build and deploy something real before paying for any certification.
- Set a billing alert on day one.
The concepts matter more than the logo
Every major cloud offers the same building blocks under different names. Once you understand them on one platform, moving to another is mostly learning new names and a new console.
| Concept | AWS | Azure | Google Cloud |
|---|---|---|---|
| Virtual machines | EC2 | Virtual Machines | Compute Engine |
| Object storage | S3 | Blob Storage | Cloud Storage |
| Serverless functions | Lambda | Functions | Cloud Run functions |
| Managed containers | ECS, EKS | Container Apps, AKS | Cloud Run, GKE |
| Managed SQL | RDS | Azure SQL, Database for PostgreSQL | Cloud SQL |
| Identity and access | IAM | Entra ID and RBAC | IAM |
What you are really learning is networking, identity and permissions, storage choices, how to deploy and scale, and how billing works. Those are the parts people get wrong in production.
How to choose
Choose AWS if you have no strong reason otherwise. By most market estimates it has the largest share of the cloud infrastructure market, followed by Azure and then Google Cloud. It also has the most tutorials, community answers and job posts that mention it by name.
Choose Azure if your target employers run on Microsoft. Large enterprises, banks, government bodies and companies built around .NET and Microsoft 365 often use Azure. If you already work in a Microsoft shop, Azure is the obvious first step.
Choose Google Cloud if you are heading into data or ML. Its data warehouse and analytics services are popular with data teams, and some startups prefer it. If your target is data engineering or ML work at a company that uses it, start there.
Then check your own market. Search twenty job posts for the roles you want, in your region and for remote roles, and count which cloud appears. That count beats any general advice, including mine.
A practical first month
- Week 1: Create an account, set a billing alert and a budget, and learn the identity basics: users, roles and why you never use the root account day to day.
- Week 2: Deploy a small web app on a virtual machine, then again with a managed container or serverless service. Notice what you no longer have to manage.
- Week 3: Add a managed database and object storage. Put secrets in the provider's secret manager, not in code.
- Week 4: Tear it all down and recreate it with infrastructure as code. Terraform Tutorials are a good start, and Terraform works across all three clouds.
The Cloud Resume Challenge is a well-known project that ties these steps together. The DevOps and cloud roadmap and its cheat sheet put cloud inside the wider skill set: Linux, containers, CI/CD and monitoring.
Free learning material
- AWS: AWS Skill Builder and AWS Cloud Practitioner Essentials.
- Google Cloud: Google Skills, formerly Cloud Skills Boost.
- All three: the official architecture guidance, such as the AWS Well-Architected Framework and Cloud Design Patterns.
What about certifications?
A foundational or associate certification can help your CV get past filters, especially for cloud and DevOps roles. But build first. A certificate with nothing deployed behind it is easy to see through; a deployed project with infrastructure as code and a clear README is not. I cover this in more detail in Are certifications like AWS or Google Cloud worth it for getting a tech job?.
One warning
Free tiers have limits, and it is easy to leave something running. Set a billing alert before you create anything else, and delete resources at the end of each session. Plenty of learners have been caught out by one forgotten service.
If you are still stuck
If you are unsure whether cloud is even the right direction, read How do I move into AI engineering, data science or DevOps?. If you want help matching a cloud and a first project to the roles you are aiming for, join Sefism and, as a member, book a 1:1 session.
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