In large organizations, it is common to have dedicated teams for various tasks. For instance, there might be a research team, an economic analysis team, and a solution architecture team. These teams collaborate to make informed decisions. In our case, we conducted a comprehensive comparative study involving Google Cloud, AWS, and Azure. We determined that Azure was the preferred solution for most of our requirements. However, when it came to demanding analytics workloads, particularly in the realm of AI and machine learning, we opted for AWS due to its robust capabilities in that domain.

In the past, I used AWS. Personally, I prefer Azure Stack because it offers scalability across availability zones, elastic computing, and a robust marketplace with options for bringing your own license. It's user-friendly and has readily available scripts and patterns. Everything is there for me.

Overall, Azure is better than Canonical and OpenShift. The overall portfolio is better. Canonical and OpenShift have limited product lines. I also need to use third-party products along with them. With Azure, everything can be installed from the dashboard, and Microsoft has a very rich product portfolio.

We use Microsoft products but did conduct a lightweight comparison. Because we rely very heavily on Microsoft on-premises, we immediately saw the benefits of using the solution instead of AWS or Google. 

The solution is developing very fast so new features are always being added. It is almost hard to keep up with everything the solution offers. 

We are thinking of moving from Azure to AWS because there are issues scaling the suite of products, support is not optimum, and the solution is more costly than AWS products. 

I have conducted cost analysis and simulations using AWS, Azure Stack, and Google Cloud. So I've performed several cost analyses based on customer requirements. But I haven't had extensive hands-on experience with those public clouds.

Based on the secondary data or information we got in our company based on the initial evaluation we did, I think the way the instances are spread and made available across the globe makes Azure Stack a relatively easier product compared to its competitors. Azure Stack becomes easier to adopt with the new GDPR and the country-level data privacy or security rules implemented.

We evaluated AWS and Google. It depends on the company and what the best fit is for the organization. If companies have similar requirements, they can follow us, or if they have a different requirement, I believe that Google or AWS might fit their needs as well.

I've looked into AWS, which is more user friendly, and is a solution I would prefer to move over to. Not only is it always easier for us too manage by another provision, it's a lot faster. Azure is slower. 

We are providing services based on Azure – infrastructure services, fast services, and all these kinds of things.

Azure Stack is very good technology. You can use other Microsoft products, such as Nutanix as the virtualization layer or VMware, and then install all the products that other complex vendors are using – Cloud Service or Amazon Service.

The only issue is some performance issues. And with this concern, if you have to do the right sizing.

I plan to test VMware vRealize, but I have not done it yet.

I have tested many different OCRs, including one from Google Cloud, and this is one of the best that I have ever seen.