Microsoft Azure Reviews

We primarily use Microsoft Azure for data storage on the server. Additionally, we leverage Power Automate for process automation tasks. Some of our processes benefit from AI and ML capabilities, such as image processing and recognition. Specifically, we utilize the product for its Translation APIs, including language translation functionality.

We validate customer videos and speech in real-time by utilizing language translation services and image processing. This involves converting speech to text and vice versa in real-time. Customers record videos where they speak predefined text. We capture the image and speech, convert it to text, and compare it with the standardized text. Automating this process makes validation much easier compared to manual methods. On the Azure side, we primarily utilize its data storage and processing capabilities. Additionally, we leverage its AI/ML features, along with its automation capabilities.

Improving transparency in billing is crucial for us. Understanding how billing works only becomes clear once we start using the services. A more accurate billing calculator would help us anticipate costs associated with using specific services.

I have been using the product for two years. 

I rate the tool's stability a nine out of ten. 

Scalability is a key factor, so we opt for Microsoft Azure. Being a Microsoft product, we trust its scalability. Thus far, we haven't encountered any issues related to transaction processing or other scalability concerns. I rate it a seven out of ten since we are not running enterprise workloads. My company has 50 users. The usage of these use cases will increase as our business grows because they are directly related to serving the end consumer. Therefore, we anticipate a significant rise in usage over time.

Improvement is needed in the support process, especially for smaller and medium-sized customers who may not have existing support plans with Microsoft. Accessing support for these customers can be cumbersome, requiring additional payments before assistance is available. It is not clear when you buy the product. You will learn about additional support payments when you start using it. 

The tools' support is in multiple places, which can be complex for customers. It needs to be in one place. 

Neutral

I rate the tool's deployment an eight out of ten. It can be deployed in two to three hours. 

Microsoft Azure's pricing is reasonable. We pay around 5000 dollars per annum. 

We evaluated Google Cloud, IBM Cloud, and AWS. 

We don't face many challenges with compliance and security. We rely on Azure Stack and adhere to the security standards they implement. Compared to AWS, we find it much simpler and easier to achieve interoperability and integration when using Microsoft Azure. You must ensure you have the right competency before using the product. It can become complicated if you don't have the right person to manage it. I rate it an eight out of ten. 

Compared to other cloud platforms, I find the Azure portal very user-friendly. It's more intuitive and clearer than some, but it depends on your specific needs because Azure offers many services. 

For instance, working with Synapse, a complex technology with diverse processing engines, requires deep knowledge. In our experience with clients, using Databricks, a third-party service, on top of Azure can be helpful.

There's an ongoing development, particularly concerning the Data Fabric offering launched a few months ago.

Data Fabric is an additional offering which is Software as a service "as a service" application, unlike the core Azure platform initially focused on "platform as a service." It sits on top of Azure. 

We thought Azure could be more flexible and cost-effective, but our experience suggests this separation might simplify things for some customers. It's worth exploring as a potential improvement for specific needs.

I have been using it for several years. We have used it, or we have architectures. We consult about Azure. 

We do a lot here in this area because it's also a big topic for us. But it's a more general consulting topic for me. I have some experience with it, but I do not implement it. Internally, we use some Azure services. 

We have all kinds of typically, ranging more towards larger size customers, midsized customers, and a lot in the financial area. 

For example, with a Synapse environment, we might need to switch to Databricks for better scalability. But overall, the platform itself scales very well. Based on my experience, I'd give it an eight out of ten.

Azure is the best in Germany compared to AWS or Google. It has the best German footprint, so the support is better locally.

But globally, it's good, not always the best. Some users have very good experiences with Google's support as well.  

Neutral

From the consulting perspective, we consult on every technology on the market. For example, Snowflake is a big topic on our side.  

I have a lot of history in SAP. With current or former SAP solutions.  

In our company, we are more Microsoft-based and Microsoft CRM.

The technical part of setting up such a platform is typically the smaller part. And for an experienced consultant, it's okay. It's nothing special. It's more about the processes and organization, which is important to consider here.

So, I would rate my experience with the initial setup an eight out of ten, with ten being easy. 

Typically, in Germany, we see that setting up is very complex; enterprises work well with Azure setups if users are already experienced at different points with Azure. But it's a little bit more easy compared to Google or Amazon. But it depends a little bit on the service and the environment you need.

From a technical perspective, it can set up something in a day or in some hours. That's not a problem. 

The thing is more the organizational level here, what is allowed, who can do it, where the costs are going, and so on. The process is typically much more about the deployment or, depending on whether you have already built a platform and just have to automate the deployment process. 

For example, it works very well, typically, but the initial setup of a platform is more for organizational things, but this is not what I do. 

Overall, I would rate the solution an eight 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,

We utilize various Azure services such as Azure SQL, Azure Cosmos DB, Azure Data Factory, Azure Storage, and Azure Key Vault to build our data platform.

One of the features that I really like about Azure is its comprehensive environment for implementing a data platform. The solution provides multiple well integrated services which happen to work together seamlessly and provides flexibility and scale ability for use cases all around the industry.

There are some minor aspects which require improvement but they are very technical for an explanation. For example, the cost calculation for the services can be an unclear aspect which makes it difficult to estimate the expenses incurred accurately. Therefore, it will be beneficial to have it more transparent and apply your user-friendly cost estimation process to help users plan their budgets in a more efficient manner.

I have been using Microsoft Azure for the past 5 to 6 years.

I would rate it 9 out of 10 since it is stable but can get better.

I would rate the scalability 8 out of 10. The number of users on a platform is high but we do not have active engagement from all the users all the time. We have over 100 users but not all of them interact with the platform regularly. Keeping it aside, our main focus still remains on building data platforms which cater to different needs.

I have mixed feelings about Microsoft's technical support. While they do try to assist most of the time, I believe there's room for improvement. 

Neutral

As a data engineer, I mainly use these services rather than being involved in their implementation.

I would recommend Azure since it offers a variety of features and services which work together. This is quite rare in other platforms because they are not scalable. These features have helped us to promote our growth without any major challenges. The wide range of services make it a valuable option for implementing a data platform. However it is really difficult to quantify its value numerically. Different companies can Paradise different factors such as scalability, cost, or support which makes it different for each company.

It is important to keep in mind that there are also challenges such as the complex nature of estimating costs and no realistic expectations of savings due to the presence of hidden costs. Azure is an efficient solution but it requires improvement in terms of stability, support and pricing.

Microsoft Azure has enabled the organization to set up efficient cloud infrastructure at cost-friendly rates. 

It has a DR backup system that keeps data under safe storage for future recovery in case of any disaster. The Azure virtual machine has been the game changer in the implementation of reliable cloud computing services. 

It allows quick connection and can successfully integrate with cloud applications to enhance better workflows. It integrates Web Application Firewall which has firm security features for monitoring data flow and can easily prevent SQL injection in web apps. 

The URL-based routing system enhances precise routing protocol based on authorized ERL paths.

The platform has stabilized the enterprise backend servers with session affinities that enhance reliable feedback to client requests. 

The dynamic data management system has prevented various ransomware attacks that could lead to data loss. Azure keeps our data programs under 24/7 surveillance to ensure no critical errors can affect the entire workflow. 

The seamless integrations enhance excellent services from Microsoft Azure. We have fully complied with international data policies from the set of data models that are authorized by Zure.

Azure storage has exceptional scalability that gives the organization expandable space for storing data under secure cloud servers. The user-friendly interface enhances quick setup procedures and efficient task management, saving time and resources. 

The robust encryption services increase the confidence of tech users. The drag-and-drop features save time from the low code environment. 

Azure SQL Database has a serverless database that can integrate easily with APIs. Azure disk storage has multiple user cases that enable each team to select size and performance based on user requirements.

The pricing criteria can be improved with broken-down terms that can be understood easily. 

There are rare cases of time-consuming technical issues. The Azure team can devise efficient and streamlined procedures for dealing with critical technicalities that can affect workflows. 

Integrating the system with third-party platforms not connected to the Microsoft system is not easy. 

Maintenance is sometimes hectic due to poor cloud and on-premise server integrations. 

The overall performance has been excellent, and I can recommend Microsoft Azure to other enterprises.

I've used the solution for two years.

It is highly scalable.

I am impressed by the storage services and security configurations.

The support team offers reliable services.

Positive

I have not used any alternative product.

The setup was straightforward.

Implementation took place through the vendor team.

We've witnessed an ROI of 55%.

The setup procedure was simple and the cost is relatively friendly.

I have not evaluated any other platforms.

I am impressed by the performance.

We use Microsoft Azure for task management. 

The product is a cloud solution. 

Microsoft Azure needs to improve its user interface. New developers and teams have difficulty understanding its lifecycle. 

I have been working with the product for 12 years. 

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

Microsoft Azure is very scalable, and I rate it a ten out of ten. My company has 15 users. 

Microsoft's tech support is awful. 

I used Jira before Microsoft Azure. 

I rate the product's deployment an eight out of ten. It can be completed in a few hours. 

Our DevOps engineers manage the installation. 

It's a positive experience for every development team to use Microsoft Azure, especially when working with Microsoft products. However, if working with open-source solutions like PHP or Google programming languages, opting for other cloud solutions such as Google Cloud or AWS is recommended. These platforms are considered more suitable for open-source solutions compared to Microsoft Azure. I rate the product an eight out of ten. 

We use it for virtual machines, database services, load balancers, and firewall services.

The platform as a service for MySQL and PostgreSQL have significantly improved our operational efficiency. The performance is very good, and it has improved our business performance a lot.

Azure Security and Compliance features:

Azure offers built-in security called Microsoft Defender. This is a paid version that provides posture management for the servers. If there is any setting that needs to be changed or any problem with any network setting that could lead to a disaster, it shows us on the platform that the posture is not correct, and we fix it accordingly. It provides proactive overall management and monitors the entire infrastructure.

AI initiatives:

AI initiatives have been introduced, but we haven't tested it, so we cannot comment on that.

Everything is in the same control panel, and the management is very easy. If there's a new feature, it takes less time to understand the working procedure on the platform. So, it's user-friendly.

I would like to see improvement in the technical support. Sometimes it takes a long time. Only sometimes, not every time. It gets delayed. The response time should be faster.

I have been using it for six years. 

It is a very stable product. We haven't faced any issues with it, and it's been about five or six years.

I find it scalable. Whenever there is a large requirement to increase resources, we can increase them on the fly and decrease them when it's not necessary. It's very easy, and it takes very little time to scale up deployments.

Sometimes there are some problems that need to be taken care of by the Microsoft technical support team. We raise tickets for these cases, which are not solvable by email support. They call us back and resolve the problem.

Neutral

Previously, we used in-house servers. We moved to Azure. As for other solutions, no. There was no other solution. Everything was in-house. We had physical servers, and then we moved to cloud services.

I did not have any challenges or complexities with the initial setup process.

There's a vast knowledge base available. So, there were no challenges. If there's a new deployment, the tutorial is already there. You just have to follow it.

It took a couple of days to complete the migrations.

Maintenance happens at the machine level, not the platform level. There's no maintenance requirement at the platform level.

The initial deployment consisted of about twenty-five virtual machines and five to six services.

We did it in-house.

It has impacted cost savings or business productivity overall. We can easily scale up and scale down the services as per the requirement. 

During some months, the requirement is high. During that time, we scale up the service and scale it down when not necessary. So, it saves a lot of cost for us. The resource cost is not fixed here, and we can scale up and scale down as per the requirement. When we scale it down, the cost gets reduced by a lot.

The pricing is fine. Whenever you deploy a new service or virtual machine, they provide a calculator service that can upfront calculate the tentative cost for the service or resource, monthly or annually. On top of that, the third party through which we have taken the services adds some more discounts.

The recommendation would be to first go through the tutorials, or you have to know the requirement first. As for that, you need to go through the tutorials provided by Microsoft, and then you are good to go.

Overall, I would rate it an eight out of ten because there's always room for improvement.

I integrate our technologies into Azure. I just deploy, do some tests and POC for Azure. A recent project leveraged Azure's analytics services, it was related to Security Hub and Azure B1.

I support customers with their Azure implementations to better understand Azure architecture and how to integrate our technologies.

I like the ease of implementation and development and how quickly everything is ready.

Azure's security and compliance tools are not enough, and that's why other technologies like Fortinet would be much more recommended than the native ones.

Security, for sure, is an area of improvement. 

I have been working with it for three years now. 

I would rate the scalability a ten out of ten. Our customers are medium and enterprise businesses. 

I would rate my experience with the initial setup a ten out of ten, where one is difficult, and ten is easy.

It's cloud-based, both public and private.

The deployment can take a few days. I deploy it in the customer's premises, in their private or public cloud account.

I would rate the pricing a six out of ten,  where one is cheap, and ten is expensive. It's in line with other public cloud providers.

I would recommend it because it's easy to implement. But it always depends on the customer's needs. If their specific needs match with going towards the public cloud, then Azure would be one of my main recommendations.

Overall, I would rate it a nine out of ten.