Microsoft Azure Reviews

We have various dashboards built for different subject areas using Microsoft Power BI. These are built to meet specific user requirements for dashboards, reporting, and analytics, including predictive analytics. The data is populated in the cloud using Microsoft integration services and Data Factory.

Microsoft Azure provides a valuable Data Factory, particularly for analytics. The product is powerful for integration and data loading. Power BI, another feature of Azure, is extremely elegant and has robust features that support forecasting using R and Python. Azure's ecosystem promotes integration across various products, making it a comprehensive solution for data and analytics.

Many features are specific to Azure cloud, creating a vendor lock-in. Moving solutions back on-premises may not be possible. Some features available on Azure cloud are not present on-premises, which can limit hybrid deployments. Recent outages and security issues are also a concern, causing a decrease in confidence, especially when partnering with third-party companies.

I have been using Microsoft Azure for less than three years.

I find the setup to be very simple and easy to use.

Microsoft Azure is quite stable, but recent outages and security issues have slightly decreased my confidence. I have not personally faced any major issues, but the security part needs more focus.

Scalability with Microsoft Azure is amazing, which is a primary reason for using cloud solutions.

The setup is very simple and user-friendly.

Pricing varies on a case-to-case basis. Microsoft solutions might be cheaper than some services like AWS, but some solutions may be more expensive depending on the services compared.

I evaluated Cloudera as well. While Microsoft Azure offers easier and faster rollout of solutions, Cloudera provides a flexible hybrid environment with no vendor lock-ins, which can be an advantage.

I rate Microsoft Azure a nine out of ten overall. It is a very well-done and elegant platform, but the security issues slightly lower my rating.

Public Cloud

Microsoft Azure

My experience primarily revolves around modernization, IT transformation, and infrastructure as a service in the cloud, along with managed services, cloud service provider strategies, designing cloud services, and monetization strategies.

So, I'm mainly focused on consulting for customers. However, I also use it personally. 

My customers integrate Microsoft Azure into their existing IT infrastructure. They adopt a hybrid approach, and they tend to move as much as possible to the cloud. It's a transition to fully cloud-based solutions, dealing with legacy systems through temporary hybrid solutions until everything can be migrated.

Projects often leverage Azure for data handling, using Microsoft's data platform, Power BI, and Azure Synapse Analytics. Innovations with Azure are increasingly driven by integrations with OpenAI and tools like ChatGPT, enabling rapid project initiation and delivering substantial results in artificial intelligence applications.

It's very exhaustive and very comprehensive. Regarding the security features, the security stack of Microsoft has made a lot of improvements in the last two years. We really appreciate the offerings, particularly what they have done with Microsoft Sentinel, a platform that helps manage what is happening within your organization, which is very good. 

An improvement could be a version that is more adapted for small companies. Microsoft Sentinel is great for large companies but less so for smaller ones. I also appreciate what they have done with Microsoft Purview. The cybersecurity stack of Microsoft is very good.

Microsoft Azure promotes clear, logical structures preventing impractical configurations. So, compared to the older platform I know, the advantage of Microsoft Azure is it's very coherent. You can't really build something totally stupid. 

With other platforms, it's possible to build something technically possible but practically very stupid. So, it's very coherent on the Microsoft platform, and it's also consistent with what Microsoft has done on-premise. 

If we have a customer with a strong Microsoft footprint, it's pretty obvious that we should move to Microsoft Azure. On the opposite side, if we have a customer that's super Linux-oriented, they have a lot of Linux services and stuff like that for those types of customers. It's easier, maybe, to move to AWS.

Another area of improvement is Microsoft Sentinel. It is great for large companies but less so for smaller ones. An improvement could be a version that is more adapted for small companies.

The only thing is regarding the management of multi-cloud environments. That's not really possible. 

So basically, it's wonderful if you manage Microsoft clearly and if you manage Microsoft Azure, but if you need to consume external services and have a global overview of all your consumption, it's not the case. 

Google, for instance, has tools that help you manage multiple environments, which makes sense because Google is really the cloud provider. So that's why they need to be compliant with the others. 

But for sure, Microsoft's approach is different, and it's wonderful when you're one hundred percent on Azure. But if you'd like to have something more of a multi-cloud strategy, that's a bit of a gap where they could improve.

I have been using this solution for more than ten years now. 

It is a very stable solution. I would rate the stability a ten, but I never give it ten, so I would rate it a nine out of ten. 

I would rate the scalability a nine out of ten because no one is perfect. Azure's scalability features are fundamental. They allow our applications to grow with our customers. 

For instance, when a customer enters new markets, it's easy to deploy an environment in a new data center or provide a CDN for closer distribution. We encourage customers to adopt modern applications based on microservices, which are natively scalable and elastic, allowing the IT infrastructure to grow with their market demands and expectations.

In Switzerland, where I'm based, the majority of people use Azure. AWS entered the market a bit later. The problem is they're working more with Microsoft products like Microsoft 365 than with Azure as an infrastructure platform, which is still pretty new here. We're at an early stage in Switzerland for full cloud adoption.

Our customers are medium enterprises mostly because they are the most prominent customers we see in my business. Large customers already use Azure extensively, like the top 50 big companies, including Zalando, Nestle, Kraya, and Philip Morris for PMI. They're using Azure a lot, but not always AWS. If you're very big, you'll have at least two cloud providers. 

The medium market is more Microsoft-oriented than AWS. Small companies, however, don't know much about the cloud or are not interested in it; they are interested in solutions that may be hosted in the cloud, but that's not their focus.

The customer service and support are very good. When we have an issue in an Azure environment, it's usually our fault, not Microsoft's. Maybe it is an issue with the design we made.

However, when we raise a ticket, we quickly get feedback or someone assigned to help us identify the problem, which, 90% of the time, was on our end. I'm very happy with the support they provide.

Positive

I've worked with many solutions as I'm involved in cloud strategy, focusing on cloud technology.

I have substantial knowledge of the AWS platform and Microsoft Azure, particularly in infrastructure as a service, management, cloud platforms, FinOps, containers, and microservices. 

I have a good overview of the offerings from AWS, Microsoft, and Google, and they're very close. They observe each other and are very similar. For me, Microsoft Azure is a very good platform with a lot of utility. 

AWS is probably the most exhaustive platform, allowing for a wide range of technologies. However, this means you can create monster systems that don't make sense, though it might be useful for a very niche market. 

Google tries to think out of the box, offering alternatives that can comply with other platforms, and having a more data-driven approach. But AWS and Microsoft are very close.

I would rate my experience with the initial setup a five out of ten, with ten being easy to set up. 

It's not difficult because you are well-guided, but it requires an understanding of the philosophy and knowledge. It's definitely easier than AWS, which is more complex and designed by engineers for engineers. Managing AWS is definitely a bit more complex than Azure.

The time it takes to deploy Microsoft Azure varies. You can create an environment in five minutes, but setting up a whole organization can take longer. It depends on what you mean by "deploy." 

In Azure, the environment size matters; whether you have one server or three thousand, it's not the same thing, and it also includes factors like replication. Now, everything is scripted, so the deployment time also depends on your maturity and experience. It's faster to deploy a cloud environment than a physical one.

First, we identify what needs to be achieved and make the architecture. Then we deploy in a test environment, perform integration and acceptance tests, move to a pre-production environment for real-life assessment with limited users, and based on success, move to production. 

There's a sandbox or dev environment, a test environment for testing, a pre-prod for limited user testing, and then production for a dedicated market or group if successful.

I would rate the pricing a seven out of ten, where one is cheap and ten is expensive.

It's not about licensing but subscription. For an SME, spending roughly 5,000 euros per month becomes interesting, indicating a significant infrastructure setup in the cloud. 

For those just starting their cloud journey or using only Office 365 and similar services, it's much cheaper, about 1,000 to 2,000 euros per month.

Customers pay Microsoft to get the environment up and running, but they may also need to pay external providers or suppliers for managed services. This is where we see an opportunity to provide an integrated offer that includes both the Microsoft suite and management on top. 

It's crucial, especially for companies that may not know how to fully leverage the product, to have this guidance and support. 

This is where Microsoft partners come in, adding value on top of Microsoft's offerings. 

For an SME, depending on their IT infrastructure, having managed services is important, as they may not have a large IT department. The cost of managing the environment might be similar to the expense for Microsoft services, potentially around 5,000 euros a month to manage the environment.

I would advise that migrating to the cloud is an amazing opportunity. However, it's crucial to understand the drivers of the cloud, what changes it brings, and to reconsider the organization and skills within the organization. 

If you expect to move to the cloud without changing the structure, processes, personnel, or without providing training, it won't work. You might end up disappointed, wanting a direct copy of what you had in a cloud environment in the past, which could be more expensive.

Moving to Azure requires training your IT teams, but also providing basic cloud training for everyone, including the CFO, CIO, and even the CEO. Everyone needs to understand the concept of the cloud and what can be achieved with it.

Creating a cloud center of excellence is also critical to reshaping the company with cloud capabilities. This can lead to significant changes and transformation, increasing elasticity, reactivity, and potentially huge savings.

Overall, I would rate the solution a nine out of ten. 

Hybrid Cloud

We host all of our production workloads in Azure, including all environments like UAT, development, and production. 

All our mission-critical workloads run in Azure, and that includes Azure Kubernetes Service (AKS), Azure API Management (APIM), Application Gateway, Load Balancer, and a full suite of security products, including Azure Sentinel, virtual machines, Azure Monitor, and ExpressRoute for private network connectivity.

Additionally, we've recently begun using Azure Synapse for data warehousing, and our SaaS solutions include Office 365 and Dynamics 365.

We use so many services, and it's constantly evolving, so there are many features I like. 

For example, Azure DevOps is good for deployment.

Additionally, different Azure products integrate well to create unified security solutions.

I really like the security features in Azure. Defender integrates everything, so I can handle all security posture management tasks within a unified solution. It outperforms SIEM, CIEM, and even Security Access Broker solutions. It's a complete package with unified support within Azure.

For compliance, we follow specific industry standards and government regulations. Azure provides a strong baseline, making compliance maintenance easier.

We use most Azure services. However, there are limitations with a few services, like the Standard Load Balancer. It lacks features like utilization visibility compared to traditional load balancers.

Some older services need better log visibility. Additionally, limitations can be restrictive. For example, the Standard Load Balancer currently lacks the ability to proactively monitor its own health.

Additionally, through the Cloud Solution Provider (CSP) model, Microsoft support isn't ideal. We often need to escalate to outsourced technical support, who rely on documentation. I often need to remind them that we follow the documentation and educate them on the issue. I rarely reach the actual Microsoft back-end engineers. Despite this, the service uptime and monitoring are good.

I have been working with it for seven years. I have been using it since 2017. 

It's stable. However, we had a major incident in Singapore last year, even though we don't have any resources in Australia (where another major incident occurred). 

Aside from that, we consider it reliable. One issue is that Microsoft sometimes upgrades released instances without notifying us (the last notification was in August). This happened with an automated upgrade I'm still working on resolving with support.

It's very scalable. We can scale up to 80-85% without issues. The only limitation is for scaling down below 10-15% due to CSP quotas and limitations, but that only affects a small portion (less than 10%).

We always forecast scalability needs, such as sizes, so it wasn't a bottleneck for deployments or production issues. Instead, it has only enhanced our environment.

Honestly, and without disrespect to Microsoft, I'd rate it a two out of ten.

It bothers me. I don't understand why we spend so much time and money on Azure when Microsoft relies on third-party companies for support in the CSP model. I don't know how the support model works within Microsoft, but giving it to poor-performing third-party companies is not ideal. 

Negative

My company primarily works on Azure now. However, in my previous organization, I used Oracle and AWS Cloud.

Navigation and some features are better in AWS. But the documentation can be complex compared to Azure. 

For example, the AWS documentation for creating a virtual machine end-to-end is very clear, even for someone unfamiliar with the cloud. 

Azure documentation, while good, can be overwhelming, requiring more experience to understand.

The initial deployment is easy now, after five years of using it. It might have been a nightmare a few years ago, but it's very good now.

We primarily deploy using PaaS (Platform as a Service) solutions. We avoid managing virtual machines whenever possible. Approximately 90% of our mission-critical application workloads are microservices run in Azure Kubernetes Service (AKS). We use virtual machines for the remaining 10%. We also use Azure SQL Database. We deploy resources using Azure DevOps pipelines.

Azure's documentation assists with our deployments. I like the recommendation feature, although we sometimes need to create exceptions, as is typical with any baseline. But overall, it's helpful. 

Not just the recommendations, but the entire added value is a great feature and provides valuable insights. The architectural framework pillars are also very useful to use as a whole, not just the individual recommendations.

I wasn't on the deployment team, but I support most architecture decisions. We use Azure DevOps pipelines to deploy to AKS clusters in production. 

We use YAML pipelines for infrastructure as code (IaC) deployments and Azure DevOps for application deployments. 

However, we face some integration challenges, but that's okay. It's not unique to Azure; every other tool has its own challenges.

For PaaS (Platform as a service) offerings, we have no issues with maintenance. However, with IaaS (Infrastructure as a service) services like Azure SQL, choosing maintenance slots is limited. 

For example, with business-critical Azure SQL instances, there are only three available maintenance slots to choose from. This makes it difficult even though the downtime is less than a minute. We cannot create custom maintenance windows for Azure SQL instances. 

We'd like Microsoft to offer more maintenance slots because the current options, like 10 PM to 6 AM Monday to Thursday, are not suitable for mission-critical workloads. It's not always feasible to ask stakeholders for downtime outside those windows. So, I would definitely recommend requesting more maintenance time slots as feedback.

 

It's a mixed bag. Some services are okay, while others are expensive. Different features within the same service, like Defender, have separate charges. This, combined with the skill shortage in FinOps strategy and management, makes it difficult to control costs. 

Cloud-native development makes it hard to predict future load capacity, so some services need the flexibility to scale up later, while others require full configuration during initial deployment.

Overall, I would rate the pricing on a seven out of ten, with ten being the most expensive.

I would recommend Azure based on specific business needs. However, I would recommend using this solution. 

Overall, I would rate the solution an eight out of ten because of the customer support issues. 

Public Cloud

Microsoft Azure

Microsoft Azure provides many critical features, such as business continuity and disaster recovery, which come embedded out of the box. From my point of view, managing the whole infrastructure, these features have been very beneficial. The support is also amazing, with someone allocated to assist within a few minutes.

At the moment, we've found Azure Container Apps to be most beneficial for scalability. Previously, our resources were hosted on dedicated servers, which were tricky to scale automatically. With Azure Container Apps, which work like Kubernetes with additional features, scalability is built-in. This allows us to scale to almost zero when not in use, saving costs. Additionally, consumption-based features ensure we only pay when there's demand, and it auto-scales accordingly.

However, we've had issues with Databricks auto-scaling, where it sometimes spun up more clusters than needed, incurring extra costs. Azure has resolved these issues based on our feedback. As we often adopt new technologies early, we encounter some immaturity in features, but overall, for our application needs, we're quite satisfied. I haven't used AWS or other cloud providers, so I can't compare costs.

Support is very responsive, especially for production issues. Within a few minutes, I get a phone call, and within half an hour, they gather the experts based on the resource type to address the issue.

Positive

Our budget for the Microsoft Azure infrastructure is over a million a year.

I am very satisfied with Microsoft Azure. Their resources, such as Databricks, can be expensive, but Microsoft is working on addressing that with discounts. I am happy because I use many of Azure's features, from development tools (Azure DevOps) to infrastructure.

I would recommend Microsoft Azure to others. Our developers are familiar with the Microsoft stack, which makes Azure a natural fit for us. Additionally, Microsoft offers substantial discounts for partners like us. Azure supports many open-source tools and integrates well with Azure DevOps extensions.

Recently, we've implemented Advanced Security through Microsoft Defender, which scans for vulnerabilities and integrates with our existing stack. This addition has been crucial in addressing previous gaps in security, particularly in identifying and resolving vulnerabilities early in the development process. 

I rate the overall product a nine out of ten. 

Microsoft Azure is a ticketing system that provides support services to Microsoft partners based on their partnership tier. Partners can raise support tickets, particularly for production-related issues. When we had issues with our Cosmos DB instance in production, we would submit a support ticket with screenshots detailing the error. We usually receive a call from a support engineer the same day.

Once a support engineer was assigned, the process was well-organized. Each engineer worked shifts of about eight to nine hours, and before their shift ended, they would email us to let us know who would be taking over, for example, "John Doe." They would also provide a summary of the issue, progress made, and next steps, ensuring a smooth handover without the need to re-explain the problem to the next engineer. It was a very efficient process.

Microsoft Fabric is a new service that integrates various functionalities into one platform, such as data engineering, data science, and data visualization. While promising, some complexities and limitations become apparent only after you use the service.

Fabric is a comprehensive and expensive service with tier-based pricing. For someone new to the platform, like those coming from Snowflake or Databricks, it can be difficult to grasp the cost implications and potential limitations without extensive exploration. The documentation outlines these limitations.

Pricing is very expensive.

I have been using Microsoft Azure for five years.

Cosmos DB offered better scalability. In Azure SQL, we had to carefully manage the storage tier, switching back and forth based on needs. But when we first implemented Cosmos DB, we had a good understanding of the required data volume over the past three months. This helped us select the appropriate tier because we had those figures.

If we had done it the other way around, it would have been much harder to estimate the data accurately. While you can get a rough idea, whether it works out in practice is more of a hit-and-miss approach, which we have already experienced with Cosmos DB. We applied the knowledge gained from that exercise to build a similar solution over Azure SQL.

On the DevOps side, our team consisted of five members, ranging from senior to junior roles. We would raise requests for specific services needed in the development environment. The process typically takes three to five business days, including all necessary approvals, from submitting the request to receiving the resources and verifying access.

Sometimes, even with the documentation available, understanding how it applies to our specific issues requires contacting a system engineer and creating a support ticket. The support engineer often provided additional details that were not included in the official documentation. This highlights the gap between the provided information and practical, real-world use cases.

Positive

Deployment was relatively straightforward. We didn’t encounter any issues whether we were using the GUI mode or working with our DevOps team, who utilized Terraform to provision resources as needed.

Most people use Azure Synapse for data onboarding and integration. Synapse is a big data analytics platform where data engineers and scientists can collaborate on a unified platform. Another service called API Management serves data outside Azure to downstream consumers or third parties. This is useful for cases where third parties can't be onboarded onto your system due to compliance or regulatory issues or need a specific slice of your data in near real-time. When we used Cosmos DB, we hosted near real-time data with a latency of about 15 minutes and served it via API M. With API M, authentication tokens were shared with the end users, allowing us to know precisely who was consuming data outside of our Azure environment. This setup was unique because it required providing near real-time information with minimal latency, even as the number of concurrent users increased. Cosmos DB worked well in this scenario due to its horizontal scalability. We also hosted similar data on Azure SQL, as Cosmos DB can be more expensive for cases where a smaller amount of data needed to be served, such as just the last one to three months of data. Azure SQL was a good alternative. The same API M interface was used to serve data from Cosmos DB and Azure SQL. Under the hood, one API would fetch data from Cosmos DB, and another would pull from Azure SQL. This architecture was tested and worked well for our client.

It was easy to maintain. Overall, I rate the solution an eight out of ten,

People use it for various reasons in my organization. Data engineers use it to target databases for data ingestion. 

As a data scientist, I primarily use it for modeling and analytics purposes. 

Databricks is extensively used for these purposes and also for deploying models into production. It's used across the entire pipeline in my division.

Azure offers broad compatibility with both structured and unstructured data. For example, we use PostgreSQL for storing Azure's official data and manage various types of data, including tabular and image data, accommodating the storage of all data types we handle. So, in many ways, Azure simplified the data storage and management needs.

However, we don't use  Azure for all our web hosting requirements. For example, for production and web hosting, we use a combination of Azure and other native languages and hosting services. So, it's not entirely dependent on Azure.

Being involved in building models, I appreciate the integrated version control, which obviates the need to manage different versions of my models manually.

I don't have to do a lot of experimenting; the version control is built-in. 

Azure also offers additional features in the AI space, which are beneficial, making it convenient to have all tools in one place without the overhead of using different tools for different purposes.

Integration with Microsoft products is seamless, facilitating connections to tools like Tableau and enabling easy API creation. 

One thing I find is that there are updates happening all the time, but they don't always roll out information about the changes. For example, the way to connect to Git repositories six months ago was different from how it is now. 

It would be good if the platform incorporated some kind of announcement system, like "This process has changed, here's the revised method." That would be really helpful. So, update announcements should be there. 

I have been using it for two and a half years. 

I would rate the stability an eight out of ten. It's quite stable, although there have been occasional downtimes affecting entire regions, but these issues are resolved quickly without causing significant business interruptions.

Azure's scalability, particularly in terms of cores and threads, significantly enhances our work. 

The ability to easily adjust capacity is crucial, especially when working with large geospatial datasets and running transformations or models requiring substantial computational resources.

In my department, there are around 40 end users using this solution. 

I would rate the scalability an eight out of ten. 

The platform's scalability meets our needs well.

We haven't actually needed to contact Azure support very often. However, the Databricks team, specifically our Service Account Manager, has been very helpful. They've reached out a couple of times to understand the types of projects we're working on and suggest additional functionalities that might be beneficial.

There was also some communication with the GenAI team about potential use cases that could be integrated into our platform or future products. 

I've never had to directly contact an Azure support representative. 

The online documentation is very comprehensive, and there's a large, active community that we can leverage for troubleshooting. 

Basically, all the documentation we need is readily available to resolve any queries.

We also use Cloud Foundry, alongside Azure, for various tasks within our operations.

Deployment is generally stable. But there are specific scenarios, especially in Asia Pacific, where there are limitations.

Microsoft hasn't fully rolled out services in all regions yet. This can cause problems when we try to deploy certain models in those specific regions where services are unavailable.

In contrast, if you have a self-deployed API, something you created in a native language and deployed on your own server, it would be more readily available across regions. 

So, the lack of Microsoft services in certain regions can become a blocker.

Troubleshooting and maintenance for Microsoft Azure products are handled by our internal IT team.

We have around 40 to 50 people, encompassing a mix of roles including administrators, engineers, and developers.

I would recommend using this solution. Internally, we've always preferred it over Cloud Foundry. Here's why: Microsoft Azure has been a much more seamless experience. For example, Cloud Foundry isn't very scalable. It can't handle parallel computation well, and it frequently hangs. Plus, it's not very user-friendly as a platform.

So, for all those reasons, I would recommend Azure. It's highly scalable, supports parallel computation, and offers all the steps needed for a product lifecycle within one platform. That eliminates the need for separate storage, deployment, and production environments – everything's available from the start. Those are the key reasons for my recommendation.

Overall, I would rate the solution as eight out of ten because there are still areas for improvement, like integration with cross-platform. 

We use the product to move data from sources to warehouses in on-premise environments. It also helps us move the data to the cloud or data lake.

The product's initial setup process and stability need improvement. 

We have been using Microsoft Azure for the last two years.

In terms of the product stability, we have encountered occasional issues. Sometimes, we encounter delays or wait times, especially when utilizing newly introduced services still in the preview phase. These services may initially experience glitches or bugs as they undergo testing and refinement. However, many of these issues are addressed over time, and the stability improves as the products mature. Azure continues to evolve rapidly, with new features being introduced frequently, which may contribute to occasional instability.

The platform's salability feature has supported our growth demands, allowing us to manage our resources and control costs efficiently. While it offers ease of escalation for additional resources when needed, we must exercise caution to ensure it aligns with our budgetary considerations. With a workforce of around 400 individuals spread across the globe, serving UN entities and other international organizations, our IT services are critical for their operations.

We have had an excellent experience with customer service and support from Microsoft. A dedicated team works, and we have regular monthly meetings with them.

Positive

Azure is more user-friendly and easier to use than Amazon Web Services (AWS). AWS, on the other hand, is geared more towards IT professionals and smart coding. At the same time, Azure provides a simpler and more understandable interface for building and learning. AWS may seem more complex but offers a wider range of services and possibilities. Both platforms are similar in some respects, and users may find equivalent services with different names.

The initial setup is complicated, particularly when implementing CI/CD and automatic deployment processes. It requires a strong background in coding and administration, especially when working with containers. Maintenance is simple and falls within the realm of administration.

Microsoft provides more affordable pricing than Amazon. We have a good discount for our entities. It is not an expensive product and is adaptable to various requirements. It offers a free tier for small-scale usage and the ability to scale up as needed when requirements grow.

The features enabling workflow efficiency include working with small databases locally and adapting the license pricing depending on the need. If we require more space, we can easily scale it up, and the price adjusts accordingly, making management simple. Azure allows access from anywhere worldwide to develop and manage data warehouses, facilitating remote work, especially during events like COVID-19. Previously, accessing systems remotely was more cumbersome when most data was on-premises. It provides discounted access and enables the creation of secure systems with appropriate networking for enhanced security control.

The platform's security and compliance offerings align well with our organization's needs. It is fully compliant, although it also depends on our customers' specific requirements, which may require more stringent regulations. Internally, we prioritize compliance, ensuring that we meet the necessary standards. Additionally, we appreciate its focus on performance improvements, as faster execution of services enhances our workflow efficiency. We have observed improvements in features like service flow definition within Azure Data Factory, further enhancing our capabilities. However, we encounter compatibility challenges, particularly when transitioning between different versions of Azure services, such as storage accounts from generation one to generation two, which may require manual review and adjustments.

It is seamlessly integrated with our existing IT ecosystem, allowing us to operate in a multi-cloud environment. We can easily access and integrate data sources from other platforms, such as AWS, and incorporate them into our Azure environment. For instance, we utilize Power BI within Azure to analyze unstructured data from AWS. While connectors facilitate integration, we also leverage APIs for more customized connections when specific connectors are not available. I rate Azure's integration capabilities as eight out of ten, acknowledging areas for further improvement and development.

Overall, I rate it an eight out of ten.

I am using Microsoft Azure primarily for application development purposes. Additionally, I am utilizing it for machine learning and Internet of Things.

Microsoft Azure has made it easier for me to use and format my applications effectively.

The most valuable feature is the broad range of services offered by Microsoft Azure, such as computing, networking, and Azure Arc, along with security and compliance. 

Additionally, it has made my applications easier to use and has improved the development process.

There is room for improvement in the pricing structure, user interface design (UI/UX), clear navigation, and documentation support of Microsoft Azure.

I have been using Microsoft Azure for about three years.

I would rate the stability of Microsoft Azure at eight out of ten.

I would rate the scalability of Microsoft Azure at eight out of ten.

I am very satisfied with the technical support and would rate it ten out of ten.

Positive

I did not use a different solution before Microsoft Azure.

The initial setup was a bit complex yet became easier as I learned more about it.

I would rate the pricing of Microsoft Azure at eight out of ten, which makes it on the pricier side for me.

I have already recommended Microsoft Azure to my colleagues, and they are finding it useful. 

Overall, I would rate Microsoft Azure an eight out of ten.

Public Cloud

Microsoft Azure