Microsoft Azure Reviews

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.

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.

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,

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. 

Azure is a cloud provider. We use Azure services for various purposes, including PowerApps for app development and Azure DevOps for software development and operations.

We find Azure particularly beneficial when working with clients who are heavily invested in Microsoft solutions. It necessitates that we also leverage Azure for our solutions and services.

Azure offers a variety of services rather than features per se. 

The platform is quite self-service and adaptable.

It is secure. 

It can be cheaper, which might simplify things a bit.

We've started using Azure for the past year, although we are primarily an AWS shop.

It is a stable product. I would rate the stability a ten out of ten. 

Since it is on the cloud, it is a scalable solution. 

We have a lot of end users using this solution. We use it on a daily basis. 

Since all our solutions are hosted on Azure, usage will naturally increase as our operations expand and we onboard more users.

We were using AWS and had a requirement that led us to start using Azure. We utilize all of them based on specific needs.

We use all three (Azure, Google Cloud Platform (GCP), and AWS). It's about the use case and the requirements that dictate which one we choose.

I didn't handle the setup directly. Our IT team manages the provisioning of Azure services for us.

From what I understand, it was not particularly complex.

The implementation was handled by our IT team. We have a dedicated cloud team that provisions the services we request.

The return on investment largely depends on how and where you're using it.

We've seen significant savings in infrastructure costs. That's a primary advantage of using the cloud – it's fully managed, and you pay as you go, which is highly beneficial.

Overall, I would rate it an eight out of ten. 

I would recommend Azure. When implementing cloud services, it's essential to consider the top three cloud providers today: Azure, Google Cloud Platform (GCP), and AWS. 

Azure is stable and should be considered alongside these, depending on the use case.

We use the solution for business analytics, data warehouse, data sharing, and data governance. I am a data engineer. I work on cloud data warehouses and data lakes.

I use Power BI and Azure Synapse Analytics for my analytic needs.

The solution is useful for handling large amounts of data. It is useful for big data. Our analytical needs are taken care of by Azure Synapse Analytics. The scalability is valuable. The data is increasing daily in structured, semi-structured, and unstructured areas. Accommodating multiple data types with a cloud data warehouse and cloud data lake is easy. Azure's security and compliance tools are nice. We get a lot of customers who want to handle data in large volumes.

The third-party data-sharing features must be improved. It will be useful for users who use other cloud providers.

I have been using the solution for more than five years.

The tool is stable most of the time. Sometimes, when there is an issue, it takes a long time to resolve. I rate the stability a seven out of ten. The stability must be improved.

When the demand increases during occasions like Black Friday, we have to scale up to meet the customer requirements. Later, we can scale down. I rate the tool’s scalability an eight to nine out of ten. Our clients are mostly enterprise businesses. We normally deal with manufacturing and banking customers.

The customer support is fine. We work with a partner.

Positive

I rate the ease of setup a nine or ten out of ten. We don't require many skill sets to provision it. The time taken for deployment depends upon the environment and the data. Generally, it can be done within hours.

I rate the pricing an eight or nine out of ten. If a customer has Microsoft Stack, they choose Microsoft's products.

Many customers compare Azure Synapse with Snowflake. Snowflake has good capabilities in data-sharing and the marketplace.

We are partners. We pitch Microsoft products to our clients whenever there is a need. I will recommend the product to others. Overall, I rate the product a nine out of ten.

In any general use case, if we want to run any application on our own virtual machines, that's Infrastructure as a Service (IaaS). If we want to use a readily available managed service in Azure, like Azure Storage, Azure Security Center, or Logic Apps, those are Platform as a Service (PaaS) offerings.

This is because they're provided on the platform, and they manage them. We can run our data and applications on them. If we're using a complete application as a service provided by vendors, like Office 365 (including the email service), that's considered Function as a Service (FaaS) because we're not configuring anything on our end – we're just using it.

I'm involved in all kinds of services, whether it's IaaS, PaaS, or SaaS. It depends on the specific customer requirement.

We implemented Azure for our infrastructure needs. Our core components include virtual machines, virtual networks, network security groups (NSGs), load balancers, public IPs, and private IPs. For private endpoints, those are more specific to Platform as a Service (PaaS) offerings.

Additionally, we utilize a hub network with a firewall, DNS server, and Active Directory server (AD). This aligns with the enterprise landing zone concept, where a connectivity subscription with a hub network that includes a firewall, DNS, AD, Azure Monitor, etc., would be implemented.

These shared services reside in the hub network if we have on-premises servers or other large assets running in Azure.

For management purposes, we have a separate subscription – the management subscription – which includes Log Analytics workspace and other data monitoring tools. Finally, the landing zone itself would house our workloads and applications.

We rely on many security features to manage our Azure cloud environment. It's a kind of framework we follow. First, there's posture management with compliance by following specific regulations. Then, for specific services, mainly Azure Defender and Azure Sentinel are important. They use the latest threat intelligence to identify threats and vulnerabilities. 

On top of that, there are policies to ensure your security posture is maintained, followed by firewalls, Azure Defender, and Azure Sentinel for threat intelligence and response.

All these services are managed services and they are auto-scalable.

In Azure, there are so many things. Especially when dealing with different regions. Suppose we are far from a region and using it over the internet, then probably more Edge Zones in nearby cities would help. This would give easier access with no delay or latency.

Right now, the problem in many remote areas is they may have low-bandwidth internet connections. This can make it difficult to access large services that require more bandwidth to download data and such. So, if the service were closer, it would be faster to access. At least they could access it easily.

Again, there are many other suggestions from a technical perspective on different services. But this is just from a user's perspective, and user demographics can create challenges. Other users with very good access might not have latency or other issues, but they might have operational challenges.

For example, let's say ExpressRoute. It's very expensive and mainly available for enterprise customers. Suppose individual users want that kind of dedicated connectivity over a service provider like Airtel or Vodafone and have an ExpressRoute from their phone, but is there any availability for a lower-cost option?

Because it's very expensive as well, if there were any such services available at a lower cost, then that would really help customers, especially SMBs, to have more consistent and reliable applications.

The main improvement I expect is capacity improvement. For example, live streaming applications require a lot of backend computing power. During events like football matches, millions of requests can occur per second. Existing services might not be sufficient to handle this. 

We need to know the maximum scalability based on data center capacity limitations. In some cases, we have to deny customer requests due to insufficient capacity. So, improved scalability is a key area for development, and I'm sure other cloud providers face similar challenges.

There are a lot of services already in Azure, but from a regular user's perspective, improvements can be made to specific services and features. For example, in Kubernetes, initially, it was limited. You could only create a Kubernetes cluster in one subnet. 

If all the IPs in that subnet were used, you couldn't expand that subscription. That was an issue, but it's been addressed. Now, you can increase the number of nodes by creating a new node pool in the same cluster with additional subnets. Improvements like this feature-based approach can be applied to many services. 

Another key area for improvement is the Azure load balancer. Currently, it only supports virtual machines (VMs) running in the same virtual network (vNet) on the backend. 

They should definitely support machines or IPs running on-premises (prem) or in other Azure VNets. GCP and AWS already support that. So, Azure Load Balancer should support that as well because being able to provide support is a very basic requirement or a valid request from any customer. These kinds of feature requests can be improved from a cloud service provider's perspective.

I have been using Azure storage for five to six years. 

It is a stable solution because it depends on the workload you expect. Based on that data, you can configure how many users it can handle.

Managed services are definitely more efficient than IaaS and offer a performance-centric approach.

It is a scalable solution because it depends on how the user manages it. But any services we choose in Azure are inherently scalable.

The initial setup is straightforward. Nothing is truly complex unless your solution or requirement itself is complex.

The deployment time depends on my requirements. Suppose a customer needs a very small environment, like two or three cluster machines with a standard load balancer on top, running their application on those VMs. It would hardly take 30 to 45 minutes to create the virtual machines (VMs), create a load balancer, allocate a public IP address, and set up a virtual network (vNet). 

At the very beginning, we had to create a subscription. Within the subscription, you'll create a resource group. And within the resource group, we'll be creating a virtual network. Inside the virtual network, we'll deploy the VMs, a load balancer, a public IP, and a network security group (NSG).

Additionally, if I want to make it more secure, I can create a firewall as well. So, all of these together should be deployable within an hour.

The number of people like developers required for the deployment depends on your environment. For instance, if you use an IaaS solution, you'll need more resources on your end to manage it. 

But with a PaaS service, you'll need fewer people because the cloud service provider manages half of it. With a SaaS solution, you don't need anyone to manage it – the cloud service provider handles the entire application. You just use it. 

So, it depends on the solution type. Therefore, more complex solutions require more resources to manage.

When we decide to increase capacity, we always consider the ROI and look at the projections for the next three to five years. Big investment decisions are only made based on that. 

Similarly, any customer considering adopting a service in Azure, like Azure SQL Database or Logic Apps, will first look at the return on investment. They'll consider how much they're investing in these services, how many users will be using them, and how much money they'll make from them. 

If it's not profitable based on their expectations or KPIs, they obviously won't add those services. So, it depends on the customer's specific requirements and expectations. We recommend the best possible services for their needs.

Azure licensing costs. We always compare licensing to the ROI.  Azure costing can be multi-layered. Increased capacity depends on your requirements and any contracts you have. On top of that, there's a separate cost for the licenses of the applications and operating systems you install in that capacity. 

So, as long as you're using the existing capacity, you won't be charged extra for that. However, if you increase capacity, you'll only be charged for the services you use on that additional capacity, not for the capacity itself. 

This depends on specific guarantees made in contracts that can last from two to eight years. These guarantees ensure investment has a return on investment. So, in that case, you wouldn't be charged for the additional capacity, just the services used on it.

Capacity increases based on customer requests are very rare, typically only for extremely high-volume scenarios. For example, millions of requests per second would require a service capacity increase beyond standard rates. Otherwise, we usually have enough capacity in different data centers across various regions.

Generally, most services and their licensing – it's that straightforward.

I would rate Azure an eight out of ten for managed services and IaaS a seven out of ten.

While I can advise, many factors influence decision-making. For example, if we invest in a ten-million-dollar data center capacity improvement, we need to see the return on investment within a one to three-year timeframe. If not profitable, such a large investment wouldn't be justifiable. 

Alternatively, customers could sign a five-year contract guaranteeing capacity usage and payment if we invest in the upgrade. These are the parameters that define decision-making in such situations.

We use Microsoft Teams for collaboration with different teams and parties, creating channels for both internal and external communication. In addition, we leverage Power Apps within Microsoft Office to develop workflows and automation tools.

Azure has enhanced our organization's ability to scale applications on demand by providing flexible scalability options tailored to each application's needs. Depending on the application hosted in Azure, we can scale up resources to handle increased requests or scale down during periods of lower demand.

One feature I like in Microsoft Azure is its ability to host and run applications on virtual machines. It is a basic yet crucial capability for our team. 

One area where Microsoft Azure could improve is in offering a broader range of pre-built plugins and tools compared to AWS. While Azure excels in certain capabilities like text-to-voice and voice-to-text, it may lack robust support for handling diverse languages effectively, such as local dialects or combinations of languages like Chinese and English. Enhancing flexibility and language support could make Azure more competitive in diverse global markets like Singapore and the Philippines. Additionally, a feature I would like to see added to Azure in the future is support for a native graph database technology. While AWS offers Neptune for graph databases, Azure currently lacks a similar offering.

I have been working with Microsoft Azure for almost two years.

We have not faced any stability issues with Microsoft Azure.

Microsoft Azure is highly scalable, which makes it easy to adjust resources based on demand. It is mature in terms of scalability and offers seamless scalability features. We have over 200 users utilizing the solution across various teams and departments.

Microsoft's technical support is a bit costly, but it is worth it for the quality assistance they provide. I would rate the support as an eight out of ten.

Positive

Generally, the time it takes to deploy and configure a solution in Azure can vary depending on the specific requirements and complexity of the deployment. It could range from a few hours to a few days, but it ultimately depends on factors like the size of the application, the number of resources being deployed, and any custom configurations needed.

We utilize Azure for disaster recovery and business continuity, particularly for our graph database application. While our primary system is hosted on AWS, we have implemented a backup and disaster recovery strategy using Azure. In the event of any disruptions or failures, Azure serves as a reliable fallback, ensuring minimal downtime and data loss.

While we don't create workflows directly in Azure, we benefit from its auto-scaling feature, which adjusts resources based on demand. Plus, Azure integrates well with tools like Control M for workflow automation, making our processes more efficient.

Integrating Azure with other Microsoft solutions like Active Directory and Office 365 is seamless and straightforward, enhancing our business processes. However, we also need to integrate Azure with external systems like Jira and GitLab. While Azure excels in Microsoft product integration, we are exploring ways to streamline integration with non-Microsoft products, which is an area where Microsoft can improve.

For those considering Azure, it is crucial to understand that Microsoft offers a comprehensive ecosystem of products and services. Azure is a top choice for cloud computing needs, especially when already using Microsoft products. It seamlessly integrates with other Microsoft solutions, providing a cohesive experience. So, if you are already invested in the Microsoft ecosystem, Azure is worth considering for your cloud computing needs.

Overall, I would rate Microsoft Azure as a seven out of ten.