Microsoft Azure Reviews

We deploy all of our projects in Microsoft Azure. We are a startup company. We have been since the beginning deploying our code in Azure cloud. We are actively using the full capabilities of two cloud services.

The application services are the most valuable in Microsoft Azure. I'm not using them directly but I am using the function and the web applications. I don't need to pay a lot for the maintenance. I do not need to have a DevOps employee. 

I am familiar with Google, and everything I was doing was in Google. I had to control my back proxies and do my own configuration files. With Microsoft Azure, it is all easy.

The documentation can be outdated and is not as clear in Microsoft Azure as it is in AWS or Google.

I have been using Microsoft Azure for approximately four years.

The solution is stable. 

It's easy to monitor, there's no problem with the code in their development. We had some stability issues, it was not the fault of Microsoft Azure, but it was the mistakes of the developers. It was easy to monitor it in Azure.

Microsoft Azure is highly scalable.

On only one web application I created with one service plan I can connect 10  projects. Imagine one machine can run 10 projects at the same time because whatever the project has more requests or demands, it will scale its machines and auto-scale down. This is why it makes it affordable. I can control which project is demanding more computing power or storage power.

We have approximately 50 people using this solution in my organization. It is mainly back and front developers.

We are drastically increasing our usage because last year we were running 13 projects, and now 19 projects. In 2022 we are trying to double our team.

The support could improve. For example, Python is needed for Microsoft Azure,  and the lack of documentation for the community is a problem. If you are a Python developer Microsoft Azure released an update to Python at the end of May 2021. Theoretically, I can use it with Python, but if I have a problem I need to call a Microsoft engineer to solve it. It takes some time. However, I did receive very good support from the Microsoft engineers to make my system production-ready, but language support for Python and other languages is coming late.

I have used other solutions, such as Google and AWS.

When comparing these solutions to Microsoft Azure, AWS has better documentation, Google's cognitive services, and predictions give better results, and Microsoft Azure has the best UI. If you want to reach the database of Google, there is no such SQL manager UI. Microsoft Azure UI is easy to use and has great tools.

The deployment's easy and the pipelines are easy from the Azure DevOps, everything is integrated and it has good security. The overall setup is extremely easy.

We have a team in London that is maintaining the solution. We have 450 backend developers at this site and approximately five people are looking after all the maintenance and admin roles. We have database and developers administrators that are giving access to the people for the production maintenance. 

I am very happy with the solution.

Thanks to the training I have received from Microsoft Azure, which cost £60,000, I'm up-skilling all my team for the certification, databases, and machine learning tool. Every month I'm receiving approximately £1,000 from the training credit for the up-skilling.

It is simple to start with Microsoft Azure if you know the application life cycle. You can try so many things without any cost because of the serverless system. You will not be charged for any request at the beginning. For example, you are creating a function application in Azure the first 10,000 requests are free. It is great because you can anyone a developer to test anything.

They're not using very heavy machine learning systems, the system is generally cheap. For example, they are giving a free month trial and a developer can't finish it personally if they do not use a large computing machine.

At the moment they are adding new features faster than I expected. For example, they have Python support but five years ago there wasn't any Python support. They were slow at the beginning but now it updates very quickly. For example, the community services for the low code, no code power platforms, and the power platforms.

I spoke to my developers, machine learning engineer, data engineer, and data scientists and told them please use the auto ML or the community services better. As a London business user site team, we can create all the virtual agents and AI builders with the no code platform for the machine learning models for the power applications. The auto ML is very powerful and you don't need to be an expert in machine learning.

I rate Microsoft Azure a nine out of ten.

Our current client is in the securities business, so we deal with a lot of trading data, like securities, holdings, etc. We evaluate the data quality of the daily file that comes from the current providers and transform that data using PowerPlay and Dashworks.

We're building cloud-based data warehouses by adapting on-premises data warehouses in MySQL Server. Initially, we migrated everything to the Azure SQL Data Warehouse to take advantage of all the MPP technology and stuff. In the process, we realized it was expensive for us, and we didn't need all that capacity, so we migrated that code to a simple Azure SQL database. We made it work from that point.

In our current project, we're using Power BI with Azure. We directly import data from that SQL database into Power BI using PowerPlay and ask the client architect to do some data engineering so we have serverless capacity in Azure. Right now, we are migrating to Azure Synapse, and we are actually in the process of doing a couple of PLCs with serverless capacity. Maybe we'll also use Databricks. 

Azure Data Lake is useful. We are in the process of populating the data lake for our current project. Also, we are directly importing for Power BI to using PowerPlay.

There is room for improvement on a couple of Azure services. One that comes to mind is Data Factory. Microsoft has improved a lot of Data Factory's capabilities, so maybe it's now possible to make a green custom database within Azure and Data Factory. 

I think it would be good to keep making progress on giving users the ability to do action calls on Data Factory. Right now, it's mostly local. Perhaps Microsoft could add the ability to put some calls in the workflow. Airflow is a good example. You might say, "Why not just use Airflow?" And maybe you could use that, but I think it would be better if all these things were possible with Data Factory. 

We've been working with Azure for a couple of years. I work for a tech consultancy, so we're not tied to just one project. We work with one client for a year or so, and then we work with another client the next year. Mostly we build data warehouses with SQL using Microsoft Synapse. We also do some things with Power BI and PowerPlay.

Azure is stable. We've never had any problems. 

When you work on the cloud, it's a straightforward process. You start on a PLC and start adding more components like maybe some security with a private network and so on. It's effortless for us to scale by adding additional components. Scalability depends on the service you're going to use. For example, if you are going to change from a SQL database to another database or another inter-processing ending, it's not going to be that easy. It happens with all providers. 

It is easy to set up Azure. For deployment and maintenance, we have a team of five or six people consisting of one tech leader, three developers, and one QA.

Azure's pricing could be more competitive. Some clients mentioned that they are considering switching to AWS because of the price. And AWS can provide you with the instant capacity called SpotLink. 

I rate Microsoft Azure eight out of 10. It's okay for all the use cases we've had so far. If you are going to do it on your own, make sure you read the documentation. All the information is there. Microsoft documentation is good. But if you don't want to take on that burden of reading documentation and so on, you can contact support. They'll know better than you. This is crucial because of the cost. If you choose the wrong services, you could waste a lot of money. 

We have our data lake on it. In terms of deployment, I believe we have a hybrid deployment.

We can temporarily build out an environment for different scenarios, such as testing, and when testing is done, we can shut that environment down. So, we do not have an overhead in our own data center.

The ability to scale down is a big thing.

It can be improved in terms of ease of billing or monitoring of the billing. That gets to be a little difficult.

I have been using this solution for four years.

It is absolutely stable. Microsoft doesn't want to sell something that isn't.

Its scalability is excellent. You just turn something on, and it is there. We have not made any reservations on it. We can scale up and scale down as needed. There is nothing that we have that is a commitment.

We probably have about 500 users, and they are administrators, developers, BI folks who actually manipulate it and create reports, and then we have end-users for the data. They are the people that use those reports.

In terms of the plans to increase its usage, right now, we're going through a merger, which will impact the data a little bit. So, we are in a holding pattern in terms of scaling up anything until that merger gets completed.

We go through a third party for that, and their support is really good.

We were fully on-premise with some SaaS platforms, and we then moved to Azure for a part of that.

It was complex, and that was mostly because of the security needs. We had to understand how things fit together.

The original deployment, just for testing, took about half a day, but to really get it going and to be able to allow access to people, other than the administrators, took more time. We're a financial institution, so we had to have everything monitored and secure. It probably took about four months to get it functional on the production side.

We used a consultant. They were excellent. They knew exactly what they were talking about. They were able to give us not only what was needed presently for our deployment but also the things to think about as we let the environment grow in the future.

For its deployment and maintenance, I've got security folks who watch what's going on. They make sure that only the right people are getting the right data, and it is not being allowed to folks who shouldn't have access. I have nothing public-facing on it. I've got administrators. I've probably got three people in security and five people in the administration. We're a 24/7 business, so it is split across all of that time.

Originally, when we implemented it, it was basically in a like-for-like way, which is not the way the platform is designed. So, once we were able to really get in there and figure things out, we figured out that we could use a much smaller footprint. That helped us out quite a bit in terms of a return on investment. We are seeing probably about 75% of the regular data center cost in Azure, so there were 25% savings, but we could see that go down as testing was being eliminated over different platforms.

Currently, we do not have anything reserved. There are no reservations that we have built into the Azure environment, so all of our licensing is on a consumption basis. As things spin up, those licenses spin up.

In terms of the additional costs incurred beyond the standard licensing fee, such as for operations, it's kind of tough for me to judge because I already had a fully-staffed operations team in a fully on-premise platform environment. So, we didn't spin up anybody extra for that. It just changed what they were doing.

We evaluated other options. We decided to go with Azure because we understood the licensing and VMs and how all of that worked together. Prior to the merger, we were looking at bringing the platform onto AWS. It wasn't that we were necessarily exclusive; we just felt that this was our best first step.

I would advise understanding what data you're going to be putting out there, and what your security requirements are for that. You should be ready to have a workshop so that everyone involved knows what's going on. Get a good understanding from the accounts payable team about how the payments are coming in and how to monitor them.

I love the product. From a procurement standpoint, I don't have a lot of control over it. Unless we've got some contracting of what we plan on doing, I don't have a lot of control over licenses, etc. An administrator can just go out, do it, and put the licensing in place, and then it is like you've got to pay for it. It doesn't function well in a P2P type of environment.

I would rate it an eight out of 10.

We use the solution to manage and secure my users' email for the Active Directory.

The solution’s initial setup is a bit complex.

I have been using Microsoft Azure for seven months.

I rate the solution’s stability an eight out of ten.

Only two users are currently using the solution.

I rate the solution’s scalability an eight out of ten.

We pay a monthly licensing fee for the solution, which could be cheaper.

We are currently evaluating how to maximize the use of services to back up our database. Microsoft Azure is a cloud-based solution. I would recommend Microsoft Azure to other users because it has many services that will benefit companies.

Overall, I rate the solution a seven out of ten.

We have deployed the NMS network monitoring system in Azure. We can monitor the network through it. There is no need to deploy an NOC (Network Operations Center) in my country. If we use Audiovi and Airspace there and install the NMS network element and Microsoft, everything is configured in Azure. Configuration is done remotely from anywhere. By entering Azure, we monitor the NMS network.

The stability could be improved.

I rate the solution’s stability an eight out of ten.

The solution’s scalability is good. 

I rate the solution’s scalability an eight out of ten.

The initial setup is straightforward and user-friendly. 

Azure offers a trial version, which you can use for free before proceeding to payment.

We are using the free version.

I recommend the solution to use it. This solution is cost-effective, with high uptime and zero downtime.

We use Microsoft Azure for hosting websites. It provides comprehensive control over our infrastructure and services.

Azure is easy to use and visualize.

It should improve database performance and make the platform more user-friendly. Additionally, providing more tools for seamless migration from AWS to Azure would be beneficial. Performance testing should ensure that systems remain reliable and transactions do not drop unexpectedly.

It should be thoroughly testet before release. Additionally, in Kubernetes, detailed documentation should be included, especially for STO.

I have been using Microsoft Azure for five years.

The solution is stable.

Microsoft Azure is highly scalable. It enhance the application's performance by managing increased demand efficiently. For instance, if around one thousand requests per second are coming in, Azure can handle this load seamlessly. Its scalability ensures consistent performance even under heavy traffic.

If you have an issue with Microsoft Azure, they will help me resolve it.

Positive

We use Terraform to deploy and configure our infrastructure on Microsoft Azure, following a hub-and-spoke model for networking.

It is a continuous process. Mostly, it takes about one and a half months for approval and around one month for deployment. Based on customer requirements or new needs, we continuously update the resources within the Azure infrastructure.

If I create a Terraform script, it significantly reduces the need for support. Typically, just two or three people are needed to manage it.

Azure is a strong competitor to AWS. AWS has a competitive pricing strategy, but Azure offers unique benefits. Azure provides credits, which can reduce costs for a certain period. For example, you might receive yearly credits, resulting in zero infrastructure investment for that year. 

In comparison to AWS, Azure is user-friendly and has lower cost. Azure also provides good performance over time.

In Kubernetes, what we are using offers different features, which is good. We are enabling more drivers and integrations, which is beneficial. Regarding virtual machines, they also perform very well.

We are using cognitive services include the Face API.

We have built a comprehensive AI search feature, specifically Cognitive Search, and implemented it in our application.

If a product is supposed to include certain features, it performs as expected. The support team ensures it is a reliable product, without parts that don't work. Products are thoroughly tested to ensure quality. However, in Azure, maintaining new products can be challenging and requires significant work. AWS fixes these issues more efficiently. 

Some startups choose Azure because they may not have much funding. These startups find Azure services beneficial and cost-effective.

Overall, I rate the solution an eight out of ten.

We use the solution as part of the scrum agile methodology. 

We use Azure DevOps' full hierarchy to manage our data workloads. From product management to development and QA stages, Azure DevOps provides tools. Additionally, we're implementing automation testing and integrating it with our CI/CD pipelines using Azure DevOps. This platform helps us manage all our processes. 

The main advantage of using it is that it supports a smooth workflow from development to QA, following the Scrum Agile methodology. It manages the sequence of tasks and sprints. The tool's integration capabilities are good. 

Microsoft Azure needs to improve its customization capabilities. Each organization has unique tasks and fields that it wants to use. Additionally, the search functionality could be more flexible. 

I have been working with the product for five years. 

I rate the product's stability an eight out of ten. 

I rate the solution's scalability a seven out of ten. 

I haven't contacted technical support yet. 

I rate Microsoft Azure's deployment ease as five out of ten. It takes around a month and a half to complete, while our sprints take two weeks. Moreover, we conduct three rounds of testing and development. 

The product is expensive. 

I rate the overall solution an eight out of ten. 

We use the solution to set up access to process queuing, configure virtual instances, obtain a domain name, acquire the necessary certificates, and deploy the web server to the internet.

Microsoft Azure has proven to be beneficial for our organization due to its quick deployment capabilities. Setting up virtual machines or any required infrastructure is fast. 

The tool needs to improve its navigation. 

I have been using the product for two to three years. 

Microsoft Azure's stability depends on the resources allocated. If you provision sufficient resources, it tends to be stable. However, choosing lower resources, like two gigs of RAM and CPUs, might lead to less stability.

The product is scalable. My company has five users. 

I haven't contacted the technical team yet. 

Microsoft Azure's deployment is straightforward for me, given my experience and understanding of the Azure system. It is not difficult for me to handle.

The tool's deployment was done in-house. 

I rate the product an eight out of ten. 

Our people are familiar with Microsoft Azure, and we use it for our day-to-day operations.

We use Microsoft Azure for operations, email, and office applications.

The solution’s learning curve could be improved.

I have been using Microsoft Azure for two to three years.

Microsoft Azure is a stable solution.

Around nine people use the solution in our organization.

We contact our local partners so that they can help us with our issues. For some difficulties, we try forums and open support. We don't contact enterprise support because we don't have it.

The solution’s initial setup is very straightforward.

We implemented Microsoft Azure through an in-house team consisting of two to three people. The solution’s deployment takes a few weeks.

Microsoft Azure is deployed on the cloud in our organization.

Overall, I rate the solution a seven or eight out of ten.

We use the email accounts and SharePoint. We want to use the AI and OCR services, but we do not have many use cases.

I get all the features under one roof.

The subscriptions are complicated. The process is not user-friendly.

I have been using the solution for almost one year.

The tool’s stability is good.

The tool is scalable. Around 30 people use the solution in our organization. We are trying to get projects from Europe and North America. Once we get more projects, we will be scaling up.

The initial setup is straightforward. It took me around one week to set up the product. I did the deployment myself since I am into IT.

The return on investment is good because everything is in the cloud. We save a lot on infrastructure costs and server costs.

I pay a yearly subscription fee for the solution. The pricing is normal compared to other service providers. I can increase or decrease my subscription based on my organization's needs.

We are into data management. We do a lot of data consumption and data validation. We need a lot of virtual solutions and storage solutions to process data. I would recommend the solution to others. Overall, I rate the tool a nine out of ten.