Microsoft Azure Reviews

We use it for various services and business applications. 

It is stable and scalable. It is useful for many applications and services, such as SharePoint, Microsoft Teams, and OneDrive.

They can add more documentation about the solution.

I have been using this solution for two years. 

It is stable.

It is scalable. We have around 100 people in the organization.

Their technical support is good. There are no problems.

It is easy to set up.

I would recommend this solution. It is a good solution.

I would rate Microsoft Azure a nine out of ten.

Implementation of Cloud Backup and Disaster Recovery solution, where we used Carbonite Availability as the primary tool and Microsoft Azure as secondary/target location.

Real-time replication configured from one point to another for business continuity and high availability. 

Altogether, there are eight servers in the local premise which are entirely replicated to the cloud. The kept cloud servers are idle until a disaster happens with the on-premise servers. The project setup was successful even with real-time testing. It was done with automatic failover and failback.  

It has improved our organization. 

It was very user-friendly when setting up the virtual machines and console. It was an easy task for my team to create virtual servers and start replications. 

We able to manage resources wisely with a third-party tool.  

It should have cost optimization tools. Customers are required to use third-party applications to avoid usage complications. Also, charging on downloads is not a good option, especially when it moves to a production server. 

Two years.

Achieving business continuity was a nightmare. Project was done for a supermarket chain where they kept one machine in every branch directly connected to remote data center. The connection was done using VDIs. Whenever there is glitch at the remote data center, the entire infrastructure was in trouble, which in turns affected the business a lot. Setting up a disaster recovery data center was an expensive plan and maintenance was too heavy. Connecting Carbonite Availability with Azure was an easy options, as it reduced overhead and maintenance.

Monthly billing convenience reduced cost overheads up to 70 percent.

We are a service provider and Azure is one of the products that I use to assist my clients.

I like the ExpressRoute because that makes it easy to configure connectivity to Azure-hosted services.

Azure could be made more user-friendly. For example, the configuration wizard should be more intuitive for the users.

I have been using Microsoft Azure for about 18 months.

This product is stable enough.

Scalability-wise, we have not had any problems.

We have been in touch with Microsoft technical support and I would say that they are average.

I am also working with AWS and I find that it is more user-friendly. I am a fan of AWS and although it depends on the use cases and requirements, we generally implement AWS more often than Azure.

The initial setup was fairly simple. If we did have any issues then we would consult with Microsoft Professional Services, or some of our cloud architects, just to figure out how to resolve them.

We follow the Microsoft update paths. There isn't any maintenance required because it's a managed service and the providers take care of it.

For the most part, Microsoft Azure works well. They are constantly upgrading their services. That said, I don't think that it's perfect.

I would rate this solution a seven out of ten.

The time to market is fast compared back to the traditional on-premise hosting. That is one of the better things I can say because there is no need to worry. The Pack services will enable it to start immediately. 

I think Azure is good. We're exploring the Cosmos DB for the dealer distribution, which is in a project phase. We are happy with their services. 

They should enable more other products to enable other commercial products as a Pack services, from the database side, more from the security perspective. Some of the databases don't have the features that Azure SQL has. Those parts have to enabled.

There were also a lot of constraints with the serverless parts. They are far behind compared to AWS.

I have been using Azure for the last three years. 

The technical support is a bit clumsy. Their time to respond is not that much great.

In terms of the UCs, they are very cumbersome. It's not very user friendly.

Each deployment takes around ten minutes. We do around 300 a day.

If you look at it from the cloud product perspective, AWS is first. There is no doubt about it, and Azure is in the second position, and Google is the third.

Serverless is something that Microsoft needs to focus on, it is not so mature. That would be a game-changer.

I would rate it a seven out of ten. Not a ten because they need to improve in terms of maturity, flexibility, and user experience. 

My current project is to carry out a comparison between Azure, AWS, and GCP, the three variants of cloud in order to analyze the best possible solution. In terms of costing and services I've been carrying out a comparison between all three. We are currently building the machine learning pipeline. We're partners with Microsoft and I'm a data architect. 

The data factory is a valuable feature. I come from a hardcore Microsoft background so I was able to relate to the data factory best among all the components as it's close to my existing system. 

I think the pricing model could be improved. I have that clarity with AWS but with Azure it's not that easy. If I am building a solution on Azure, the first question that stakeholders will ask me is about the cost. If I'm using multiple services of Azure, then how do I figure that out given that it's all on cloud.

Technically, I would say there could definitely be improvement on the AutoML part, which is the machine learning component of Azure. I made a comparison between AutoML versus DataRobot, another vendor that provides machine learning. DataRobot is definitely ahead of Azure AutoML. Of course that could be because I'm using the licensed version of DataRobot versus the free version of AutoML but there does seem to be a gap. 

I've been using this solution for about six months. 

I haven't had any issues with stability. I think it's more to do with the volume of data that I am playing with which for now is only 5GB of data. I don't expect any problems.

I don't see any issue with scalability. But here again, on the cloud platform, there won't be any issue with the scalability but you need to understand the pricing. Once you have that,  scaling will never be an issue. 

The complexity or otherwise of the initial setup depends on the person who will be using it. If you take the AutoAI services from other vendors, those are more graphical, more eye pleasing versus what Microsoft offers and less complicated to implement. With Azure ML, values have to be manually fed into the columns and that's clearly going to be more time consuming. 

There are multiple players in the market and this seems to be a good solution. It really depends on the use case and on the customer. I would personally choose AWS over Azure because that's where my experience is and I'm more familiar with AWS.

I would rate this solution a seven out of 10.

We primarily use Azure for our ERP system and DR usage. It is set up for multiple production workloads.

This solution requires minimal administrative effort.

The scalability is good.

The most valuable feature is Azure SQL.

Improvements need to be made with respect to the availability of third-party services.

I would like to see more advanced functionality in terms of information security.

We have been using Microsoft Azure for six years.

There is room for improvement in terms of stability.

Scalability is one of the best features. We have thousands of users.

I have been in contact with technical support and would rate them better than average. I find that it takes a long time to reach somebody who is a subject matter expert. This is because they first need to escalate requests from the level one or level two helpdesk. For the problems that we have experienced, we needed support directly from people with expertise.

The initial setup is straightforward and the deployment can be completed within short time. Now we can deploy most components/services within a day or two.

When we first implemented Azure, we engaged with a third-party system integrator. Now, however, we can do everything ourselves. We have approximately five people who do the maintenance of the cloud infrastructure.

The price of Microsoft Azure is pretty good. Among the top market players, it’s usually the cheapest or the one after. Our usage is more than $1,000,000 USD annually.

My advice for anybody who is considering this product is that it can be a good start for SME, up to MNC who needs to see their full environment, rather than just a particular system or area.

Overall, this is a good solution but there is room for improvement.

I would rate this solution an eight out of ten.

• Windows and Linux compatibility
• Great front-end management interface
• Pricing based on use time

One time I needed to build an environment, but it did not exist at the time to buy the hardware and all logistics inside it. To deploy it was essential, we got a great success on the project using MS Azure.

It could be a useful process to make the marketing of MS Publisher a little area of improvement for IT professionals learn about this tool.

Two years.

No. We did not have any problem deploying it.

No. We do not have problems with stability.

No. We do not have problems with scalability.

I do not use customer service.

We have had great experiences using their technical support. They were very useful.

No, just on-premise and testing Amazon.

No, it is easy to configure and use.

It was implemented in-house, using our own team. Some of the professionals had already worked with Azure.

It was not calculate

The whole pricing list is published, so it is clear. When you choose the configuration, you can see the price.

Yes. On-Premise and other solutions inside the company.

We are faster to market with greater integration of the development and infrastructure teams.

Develop solutions quickly using the normal toolset be it either as developer, IT, DevOps or BI. Expand into new world via AI and Machine Learning.

Update two years later.... Microsoft Azure continue to expand its Platform as a Service value and has set itself apart from other cloud providers that are focused on the IaaS world. If you are a Microsoft house e.g. Visual Studio, .Net, Xamarin, O365, Windows Server or Windows Users this is a clear winner. It is easy to expand you in-house, in-data center knowledge into the cloud and Microsoft's enablement of hybrid/spanning on-premise with Cloud makes transitions easy.

In general, the entire suite of PaaS is valuable. It enables a true breakdown of IT siloes and allows an organization to embrace DevOps. It speeds up micro-service architectures and provides interesting and new opportunities to staff, generating morale boosts.

Two years later..... This has been resolved by Microsoft. There is now starting to be the challenge of figuring out which service you want to use and it is no always clear which PaaS is best for the job. This is Microsoft achilles heal across its services.

Predictability and quality need improvement. Make sure things work predictably, as expected, and are documented.

As my organization learned the new tooling that Azure provides we encountered topics where the behavior of the PaaS Resource was behaving slightly different than expected and outlined in the documentation. We usually would open a service request on the topic and be told that it is supposed to work as we expected but there is a problem and Microsoft provided a work around. An example of such a topic was IAM where a contributor on a resource group who were creating a Storage resource were told they were not authorized. The main reason was around the registration of the resource that had to be done by an administrator and manually as a one-time task. Talking to Microsoft they admitted this was an error. This was for us predominant for Storage Accounts but it did occur for some other resources as well.

The second topic we encountered were related to VM’s that would suddenly and without warning would go offline. Response from Microsoft support request was that as long as the SLA is below 99.95% they cannot do anything. Obviously you can expand the resource and the cost using a availability set, fault domains etc. but my expectations was that VM’s would only be taken down for maintenance with prior notification. This one is less critical as I agree that you need to design your VM’s using the high availability features.

I have not seen any stability issues. High availability and reliability is good if you follow Microsoft development practices.

Provides fast scalability, based on demand.

Technical support is outstanding. They provide fast and high quality support, even with lower support contracts.

I used traditional data center solutions.

The setup was complex. There is a lot of training that needs to occur with both development teams and infrastructure teams. It is a different approach. In some ways, it is more structured.

Keep to PaaS to gain the optimal benefits from an OPEX finance and resource perspective.

I also use AWS. While AWS is ahead in the IaaS technology, for a Microsoft shop, Azure is more aligned to skills.

Learn and spend up-front time on training the organization.