Welcome back to another edition of the Indispensable Azure Tools series, your guide for tools that help you work smarter, architect better, and stay ahead in the cloud game. Today’s Indispensable Azure Tool isn’t on a typical Azure-specific utility, but on something every cross-cloud strategist should have in their bookmarks: Cloud-Product-Mapping.
If you’re working in multi-cloud environments, planning migrations, or just need to understand how Azure stacks up against AWS and GCP, this open-source tool is very helpful. Here’s why this tool stands out and how it makes comparing cloud services across Azure, AWS, and GCP a whole lot easier.
What is Cloud-Product-Mapping?
Navigating services across Azure, AWS, and GCP can feel like decoding three different country maps, each with its own naming conventions and quirks. Cloud-Product-Mapping, a community-driven GitHub project from @milanm, solves this problem with clean, downloadable tables that map equivalent services side-by-side.
It’s vendor-neutral, so not one of those tools that nudges you toward a single ecosystem, also it lays out your options clearly and objectively. Whether you’re designing hybrid architectures, supporting cloud migrations, or preparing for a cross-cloud architecture discussion, having these comparisons in one place gives you a nice edge.
Oh, and did we mention it’s open-source? That means you can contribute to it, customize it, or just keep it bookmarked as a reliable go-to reference.
Cloud-Product-Mapping is maintained by Dr Milan Milanović, a cloud architect and community contributor passionate about simplifying cloud complexity. 💡 Want more insights like this? Subscribe to his newsletter, Tech World With Milan, for regular updates and deep dives!
A Peek Inside
This solution is actually very simple, it’s a practical resource focused on utility. You’ll get PDF and PNG visuals of categorized cloud services: compute, networking, storage, databases, AI/ML, identity, and more. Each Azure service is mapped to its AWS and GCP counterpart, often with a short description to explain what it does.
Need a quick comparison before a planning session? This is your cheat sheet. Whether you’re building architecture diagrams or attending a design workshop, having these mappings available makes your job a little bit easier.
Database comparison for Relational, Key-Value, In-memory, Document, Graph and Time Series databases between Azure, AWS, GCP and Cloud Agnostic solutions.
Let’s walk through a couple of service categories using some guidance from the Azure Architecture Center’s Azure for AWS Professionals.
Example 1: Compute – Azure VMs vs. AWS EC2 vs. GCP
Compute still is the heart of nearly every cloud solution. Choosing the right virtual machines is important for performance, scalability, and as always cost.
Here’s how Cloud-Product-Mapping lines up the big three Cloud providers:
- Azure Virtual Machines – Full control over Windows or Linux instances, great for general-purpose workloads and hybrid deployments.
- AWS EC2 – Highly customizable instances with a vast selection of types, optimized for everything from compute-heavy apps to burst workloads.
- GCP Compute Engine – Offers flexible VM sizing and per-second billing, useful for tight cost optimization.
According to the Azure Architecture Center, Azure VMs are best in class in hybrid scenarios thanks to Azure Hybrid Benefit, allowing you to reuse on-prem Windows licenses and reduce costs. AWS plays the scale game with its massive EC2 catalog, while GCP offers sustained-use discounts.
With Cloud-Product-Mapping, you can see these distinctions instantly and make informed decisions faster, without having to bounce between documentation sites.
Example 2: Object Storage – Blob Storage vs. S3 vs. Cloud Storage
When (or IF :-)) your application is generating tons of unstructured data, object storage is the backbone.
Here’s how it looks on the mapping chart:
- Azure Blob Storage – Tiered storage (hot, cool, archive) optimized for big data and analytics.
- AWS S3 – Industry-standard object storage with strong lifecycle management and archive options like Glacier.
- GCP Cloud Storage – Unified object storage with support for multi-region redundancy.
Azure Blob Storage integrates with Azure Data Lake, making it ideal for analytics-heavy use cases. S3 brings durability (a whopping 11 nines) and proven longevity. GCP’s offering focuses on simplicity.
With Cloud-Product-Mapping, you can quickly assess which features matter most for your scenario, analytics capability, long-term archiving, or global reach, and align your storage choices accordingly.
Multi-Cloud Strategy Meets Azure
Head over to the Cloud-Product-Mapping GitHub repo, grab the latest PDF or PNG version, and start exploring. It’s lightweight and helpful. For deeper Azure-centric comparisons, pair it with resources like Microsoft’s Azure for AWS Professionals guide to get a dual-layered view of service parity.
Now that you know what to compare across cloud providers, it’s equally important to understand the Service Level Agreement of your Azure service of choice.
Knowing the SLA ensures you’re aware of the reliability, availability, and support commitments for the services you’re using.
For a deeper dive into how the Azure SLA impacts your architecture and business, check out our detailed guide: The Azure SLA and What That Means for You.
Stay tuned as we roll out more indispensable tools to power up your Azure cloud journey!