Choosing Your Cloud Platform

🔄 Quick Recall: In the previous lesson, you learned the three cloud service models — IaaS (rent infrastructure), PaaS (rent a development platform), and SaaS (use ready-made software). You now understand the shared responsibility model and how each model trades control for convenience. Now you’ll compare the three major platforms where these services actually run.

The Big Three

Three companies control approximately 67% of the global cloud infrastructure market:

The remaining 33% includes IBM Cloud, Oracle Cloud, Alibaba Cloud, and dozens of smaller providers.

AWS: The Market Leader

AWS launched in 2006 — years before Azure (2010) and Google Cloud (2008 public). That head start shows: AWS offers 200+ services, more than any competitor.

Where AWS excels:

• Broadest service catalog for any workload
• Largest global infrastructure (30+ regions)
• Most third-party integrations and community support
• Strongest certification ecosystem (most recognized by employers)

Best for: General-purpose cloud workloads, startups using the free tier, anyone targeting the widest job market.

Key services to know: EC2 (virtual machines), S3 (storage), Lambda (serverless), RDS (databases), IAM (identity management).

Azure: The Enterprise Standard

Azure’s killer advantage is Microsoft integration. If your organization uses Active Directory, Microsoft 365, Teams, or .NET — Azure is the natural extension.

Where Azure excels:

• Seamless integration with Microsoft tools (AD, Office 365, Teams)
• Strong hybrid cloud with Azure Arc and Azure Stack
• Enterprise compliance certifications (government, healthcare, finance)
• Best for organizations already invested in Microsoft

Best for: Microsoft-centric organizations, enterprise workloads, hybrid cloud strategies.

Key services to know: Azure VMs, Blob Storage, Azure Functions (serverless), Azure SQL, Azure AD.

Google Cloud: The AI Pioneer

Google Cloud may have the smallest market share of the three, but it leads in AI, data analytics, and Kubernetes — which Google originally created.

Where Google Cloud excels:

• AI and machine learning (Vertex AI, TensorFlow integration)
• Data analytics (BigQuery is the gold standard for data warehousing)
• Kubernetes management (GKE — built by the team that created Kubernetes)
• Often lower egress pricing than AWS/Azure

Best for: AI/ML workloads, data analytics, organizations prioritizing innovation.

Key services to know: Compute Engine, Cloud Storage, Cloud Functions, BigQuery, Vertex AI.

✅ Quick Check: If a company already runs on Microsoft 365, Active Directory, and .NET applications, which cloud platform likely offers the smoothest migration? Azure. Its native integration with the Microsoft ecosystem means existing identities, tools, and applications extend to the cloud with minimal friction. Platform choice should prioritize ecosystem fit, not just market share.

Using AI to Compare Platforms

AI assistants are excellent at translating your specific needs into platform recommendations:

Help me choose between AWS, Azure, and Google Cloud
for my situation.

My context:
- Role: [developer / manager / career changer / small business]
- Current tools: [list what your team/company uses]
- Primary goal: [learn for career / migrate existing apps /
  build new project / cost optimization]
- Budget: [free tier only / small budget / enterprise budget]
- Technical level: [beginner / some experience / experienced]
- Industry: [tech / healthcare / finance / retail / etc.]

For each platform, tell me:
1. How well it fits my specific situation (and why)
2. What would be easy about getting started
3. What would be challenging
4. Estimated monthly cost for my use case
5. The one service I should try first

Give me a clear recommendation with reasoning.

The Universal Concepts

Here’s the insight that makes cloud learning easier: the core concepts are identical across all three platforms. Only the names change.

Learning one platform means you understand 80% of any other platform. The hard part is learning cloud concepts — not learning a specific provider’s interface.

✅ Quick Check: Why is learning one cloud platform effectively learning 80% of any other? Because the core concepts (virtual machines, storage, networking, identity management, serverless) are universal. AWS EC2, Azure VMs, and Google Compute Engine all do the same thing — run virtual servers in the cloud. Learning the concept on one platform transfers directly to the others. Only the console interface and service names differ.

Key Takeaways

• AWS (~31% market share) has the broadest service catalog and largest job market — best general starting point for career builders
• Azure (~25%) excels in Microsoft ecosystem integration — the natural choice for organizations already using Microsoft tools
• Google Cloud (~11%) leads in AI, data analytics, and Kubernetes — best for AI/ML workloads and data-heavy projects
• Cloud concepts are universal across platforms — learning virtual machines, storage, and IAM on one provider transfers 80% to any other
• Choose your platform based on ecosystem fit (what you already use), career goals (where the jobs are), and specific workload needs — not just market share

Up Next: You’ll deploy your first cloud resource using free-tier accounts — with AI guiding you through each step so you get hands-on experience without spending a cent.