Microsoft Azure Reviews

The most valuable feature is the interface.

The price could be improved as well as the interface speed, and technical support.

I have been using Microsoft Azure for four years.

This solution is stable.

Microsoft Azure is a scalable product.

We have more than ten users.

I am not satisfied with the support. It seems that they outsource to different companies with people who don't even know the basics. 

You get asked several questions but never get any resolutions.

The initial setup was easy and it only takes a few minutes to install.

The cost is a little high and can be more competitive.

Microsoft Azure is a good service and I recommend it.

I would rate this solution an eight out of ten.

Hybrid Cloud

The Canvas flow interface brings a very nice functionality that improves self-learning.

Selecting and applying a machine learning algorithm is not a click-and-run process. In this case, clustering our data has helped us to find patterns and trends that were not visible using conventional (internal) classification.

Stronger R integration in a circular fashion (Azure->R->Azure). Nowadays, it has an unidirectional bias.

I've used Machine Learning Studio for the last six months.

We've had no issues with the deployment.

By using a free account for cloud services can bring you "queued" status, but normally it runs smoothly. The quota defined for free account is enough for a variety of experiments and none of the features are blocked.

We've had no issues with the scalability.

Customer Service:

As a cloud service, online chat and email service are available, but the community forums are the best place to solve issues.

Technical Support:

We have a support maintenance agreement for Windows/Office.

There are a few competitors in place, and their number is increasing, but friendliness is the strong point of AzureML, comparing to Amazon AWS or BigML.

It does not involve any setup, just having an Outlook or Microsoft account.

Using a free account leads to offline projects. For online projects those issues must be evaluated according to client side company's environment.

Machine learning is just one part of the whole data science cycle. Big data (streaming, video, etc.) or deep learning needs must be addressed with additional tools. But for prediction/classification this is a fantastic tool.

Below is a PCA graph generated by K-means training model and its Qlik Sense panel. The idea is to segment unlabeled data based on numerical features in order to find common patterns that can be grouped, named clusters.

We are using Microsoft Azure for hosting our applications in a secure environment. We are using AI and machine learning models.

Microsoft Azure has been easy to use in my experience.

I have been using Microsoft Azure for approximately two years.

Microsoft Azure is stable.

We have approximately 50 people using the solution in my organization.

The local support is fair but it is sometimes limited, the service could be better.

The initial setup is straightforward.

I am able to do the implementation of the solution.

We have some system engineers and developers that manage the solution.

The price of the solution could be cheaper in general. We are on a monthly subscription to the solution.

I would recommend this solution to others.

I rate Microsoft Azurean eight out of ten.

Public Cloud

Microsoft Azure is easy to use.

I would prefer Microsoft Azure to increase the free trial, then developers can take advantage, and it could increase their sales.

I have been using Microsoft Azure for approximately three years.

Microsoft Azure is stable.

We have approximately six customers using this solution.

The technical support could be faster and the information should be more precise.

The installation is straightforward because there is no installation required.

The number of support staff that is required depends on the use case.

There is a monthly fee you need to pay for the use of Microsoft Azure.

I would recommend this solution to others.

I rate Microsoft Azure an eight out of ten.

Public Cloud

We have been using it to modernize customers' environments. We propose that the customers consider moving a number of things into the public cloud instead of building and maintaining everything on-premise. 

The organization can focus more on real business problems instead of IT problems. It can also reduce the time spent setting up the infrastructure. This then makes the organization more agile and, in a lot of cases, more reliable. With the public cloud, if your design is okay, the chance of running into a serious outage is, in most cases, lower than that when relying on your own on-premise IT infrastructure, particularly in the case of companies with 50 to 500 people that typically don't have very big IT budgets.

I think the most useful feature has been the remote desktop. It has been very helpful when customers have old applications that are not architected to run remotely.

In my opinion, what could be improved is making the actual costs more predictable. It is very difficult to estimate the cost or the budget you are going to need to run your environment in Azure Cloud. You have to be a specialist to understand how you will be charged, which constantly changes.

As for additional features, it would be great if the pricing could be cheaper for those trying to study and use the cloud. Having a discounted pricing scheme or even a free usage scheme, like a sandbox that is free to use on a continuous basis, for those who are studying would help them to actually generate more business later on. The more people learn to use the clouds, the more business they will actually attract.

They will start pushing solutions into the cloud, but if they have no time or opportunity to learn to use it, they will not be confident in proposing cloud solutions. So until they have been able to validate it in a test environment or a learning environment, they won't take the risk and propose a cloud solution.

I've been involved with this solution for one year.

I think Microsoft Azure is fairly stable. It also depends on how you set up your design.

As advertised, the scalability should never be an issue. The only thing that would stop you from scaling would be that your application has an architecture that is not scalable.

For public clouds, customer service/technical support is okay. In general, the documentation is very good.

For those who are familiar with Azure, the initial setup is not that complex. However, for those who are using Azure for the first time, it's probably a bit more involved because they may need to create their own virtual data centers in the cloud with the necessary security measures. I think that often this is a bit underestimated mostly because of a lack of knowledge on the part of the new customer.

Software licensing models can be expensive depending on what you need compared to open source solutions, for example. However, if you don't have the technical skills, you may be better off paying for a license and support instead of trying to use open source solutions.

I would rate Microsoft Azure at eight on a scale from one to ten. 

I would advice others to take the time to study it carefully because there's a lot to understand and a lot to know before putting a solution in the clouds. Don't underestimate the complexity.

Hybrid Cloud

We are a system integrator and Microsoft Azure is one of the products we implement for our clients. We offer a service for DR solutions with it.

The most valuable feature is the instant availability of resources.

The initial setup is quite complex because of the number of options that are available.

Azure is a very stable product.

This is a scalable solution. Our clients are small and medium-sized businesses.

The initial setup is complex because there are a lot of options used to configure it.

I can recommend this solution because of its capability and scalability. In terms of improvements, I cannot think of any specific requests for new features at this time.

I would rate this solution an eight out of ten.

Public Cloud

Microsoft Azure

High availability rate anywherem, anytime. Periodic workloads options let me pay only for the time I have used it. It is easy to backup database via BCP program or tools available on codeplex site. It supports multiple languages such as Java, .NET, Ruby and PHP.

Needs fast Internet connectivity. Fear of being data being hacked or captured.

We moved our accounting database from an in-house SQL Server to MS Azure cloud and saw a significant increase in performance. We can now connect to the database even while roaming and back it up anywhere, anytime. Data replication services make it highly reliable and always available.

We are using Microsoft Azure to access the Azure cloud database.

It's a flexible solution.

We need more customization and support for doing so.

I would like to see more customization on the DevOps side.

I have been using Microsoft Azure for approximately two years. The organization has been it for more than five years.

We are working with the current version.

It's a stable solution.

We plan to continue using it in the future.

Technical support is very good.

The installation is straightforward.

If you want to install it, it would have to be on a VMware virtual machine.

If you have some experience, it doesn't take much more than thirty minutes to an hour to complete the installation.

I completed the installation myself.

This is a good product and I recommend it to others who are interested in using it.

I would rate Microsoft Azure an eight out of ten.

Public Cloud