Azure Stream Analytics Reviews

We have different kinds of IoT devices placed in different countries including the UK, US, and others. They are configured with our IoT hub and we get the logs from them accordingly.  We have these logs connected with the Stream Analytics suites and Microsoft Power BI. Whatever updates and other activity is happening on the devices are streamed into Azure and Power BI so that we can see them.

If we find any error messages then we have to check the health of the corresponding IoT devices, databases, and configuration.

This gives us a real-time monitoring system that we can use to analyze the health of our IoT devices. Previously, when something was not working properly then we would receive messages in our email using the TeamWork application. Now, instead of checking email, we receive an alert ping that we can hear, which allows us to evaluate how well the machine is doing. We can check the performance and other relevant metrics.

In general, it gives us more visibility in terms of what is going on. We used to receive between 10,000 and 20,000 emails per week, which was hectic for us to calculate and keep track of. Since implementing Azure, we have been able to monitor things very easily. Not only does it create an interval for the logs but it reduces the number of duplicates.

We have not eliminated the messages that come in as email, as high-priority messages are still delivered in that manner. For example, if there is a power shut-down then we will be notified via email. This is set up in case we miss these types of messages in the BI platform.

The most valuable features are the IoT hub and the Blob storage. All of the logs and other data that we are getting can be stored in Blobs.

The interface is user-friendly.

There may be some issues when connecting with Microsoft Power BI because we are providing the input and output commands, and there's a chance of it being delayed while connecting.

I have been using Azure System Analytics for just more than one year.

This product is stable but if our VM goes down then we are not able to get a proper instance update. When this happens, we need to kill these instances. Situations like this only happen rarely.

The scalability is based on the requirements. If the requirements are high then highly-scalable machines are needed. If it is more manageable then it is cheaper. I think that scaling is really about the cost.

We have a development team and an operations team that is working with Azure Steam Analytics. There are seven or eight people in the operations team. The customer also has access to the platform if they require it.

If you raise a ticket with technical support then they will contact you within 24 hours. However, we have not faced many issues, so we haven't had much involvement with them.

There is a diagnostic tool available in Azure and you can check to see if you have any issues on your end. If there are problems then you can contact support for assistance.

Overall, I think that the support is very helpful.

Since transitioning from our email-only solution, we have been able to set the interval that we use to retrieve logs from the devices.

We did not use a similar product before this one for the same purpose. The company has been using Azure since before I joined, although they had used AWS for other tasks. At this company, I have not had the opportunity to work on AWS.

I have not completed a deployment for production purposes. Rather, I have performed a setup for training with Azure and an IoT simulator. In this case, we just check the logs during my practice session. My role in the operation was to lead the management team.

The training deployment that I completed was user-friendly and anyone can easily do it. Even as part of the operations team, I was able to capture the details and complete the deployment really quickly.

The only difficulty that I faced was connecting with the different machines in the outside layer, such as BI or Kibana. Depending on the application I was connecting with, there were issues with it.

The deployment was done by our development team, and they are responsible for the maintenance as well. Because it is a platform as a service, Azure takes care of almost everything.

I am not familiar with the details of the investment. This is something that is handled completely by the product owner. This would be my manager or the Delivery Manager.

The cost of this solution is less than competitors such as Amazon or Google Cloud. If we only use one hour then we are only charged for one hour. It is very easy and some products are more expensive.

Azure Stream Analytics is something that we were able to easily learn. It doesn't take much programming sill, so I feel that it is easy to start using.

Other than the problem with delays in connecting to Microsoft BI, Kibana, or other monitoring tools, I don't have any other issues with this product.

I would rate this solution a nine out of ten.

We use the solution to analyze application logs. It helps review incidents and production issues.

The solution's most valuable feature is its ability to create a query using SQ.

The solution's interface could be simpler to understand for non-technical people. Also, the chart feature could be more user-friendly. Presenting or elaborating on an incident to management or executives from other non-technical departments becomes challenging. We have to create another graph and include it in the presentation slides.

We have been using the solution for two years.

The solution is stable.

The solution is scalable. We have around more than 100 developers using it.

We follow virtual documentation in case of technical errors for the solution.

If you have Azure DevOps or are using the Azure ecosystem, you must go for the solution. I rate it an eight out of ten.

When it comes to doing partitioning for the data, if you are working with both ModiB and MongoDB, it's very powerful in Microsoft Azure - the clustering platform. If it's Spark Apache, Spark will be very powerful due to the fact that you have the option to have the Delta factory, which makes all that things available within the platform. 

It allows you to take a proactive decision for any abnormal functionality. For IoT, it will give you the facility to make quick decisions on any kind of metrics or output, et cetera.

The solution has a lot of functionality that can be pushed out to companies. There's a lot of analytics to take advantage of. What they have available on the market now is more than enough for companies to work with.

You can install the solution quite quickly and start using it right away.

While it depends on the business scenario, in some cases AWS offers better features. It's hard to speak to missing features at it really depends on the business case. However, in general, it has all the features a typical company might need.

The solution needs to be marketed better. Developers should be pushed or enticed to use the solution more to get it more well-known on the market. It needs more of a presence.

The solution offers a free trial, however, it is too short. You can't really properly test it before you have to start paying. They need to give companies a longer period of time to try it out risk-free. Also, the functionality is very limited. If you want to do a POC, you need the solution to offer more flexibility. Right now, you get a 14-day window, and that's not enough for a proper test.

I've used the solution in the past 12 months.

The solution is very secure. Occasionally we might get a bug or to, however, this typically happens outside of the solution. If you are within the scope of Azure, it functions very well and there is good support from Microsoft if you run into issues. Basically, there are no major bugs or glitches to contend with, unless you have a design flaw. It works quite well.

Scaling is okay, so long as the cluster isn't overloaded.

Microsoft offers excellent technical support. They are very helpful and supportive. We are quite satisfied with the level of service they provide.

The initial setup is very fast. You can set it up and just start using it. In that sense, it's great. A company shouldn't have any issues with getting it up and running.

The product does have a free trial offer, however, it is much too short. It's only 14 days and that's not enough time to run a proper POC.

Overall, we've been quite happy with the product. I would rate it at a nine out of ten.

Our primary use case is mainly to ingest real time data streams into permanent storage places like databases, block storage, etc.

The biggest improvement for us has been that it now takes much less time for us to receive valuable information. Basically, as soon as it appears in our real time data source, in a matter of seconds, it is already in our database.

The value of this solution is the deep integration it provides with other Azure resources which we use a lot. Our whole infrastructure is pretty much based on Azure so ease of integration is a valuable feature. Secondly, the simplicity of the solution is great. You don't need to set up much, you just make a selection, select a destination, and you're off. 

There are some improvements that could be made, first of all in pricing, because right now the pricing is a bit unclear. It's hard to estimate how much of that is a local issue but you can't figure out how prices are calculated or the proprietary part of the cost. Another area that could be improved is that if something does go wrong, it's very hard to investigate what caused it and why. The logging is available but it lacks detail and doesn't provide much information.

I've been using this solution for two years. 

The solution has an acceptable level of stability although, as mentioned, if it does fail, it's pretty difficult to find out the cause. 

It's very easy to scale this solution. We probably have a couple of hundred users and we have developers who deal with maintenance. This is our main tool for real time data streaming. 

The initial setup is quite straightforward. Because of the good integration, you select your real time data, store the destination where you want to write it and you probably don't even need to transform with data. You basically create a mapping descent source. We had a proof of concept in place, so I would say deployment took two working days without having a deployment plan. 

We have a good ROI because we are able to deliver solutions very quickly and customers are happy with that. 

We evaluated and carried out a comparison with Oracle. The results were pretty much the same for both in terms of real time data streams, but were very much tied to their own cloud solutions. If you work with Oracle i'ts probably best to go with Amazon.

My simple advice would be to not scale up initially. Also, if you have questions don't just rely on the official documentation, but use other resources such as a blog by a developer, because sometimes that can be more helpful than documentation provided by the company.

The best advice I can offer would be that if there is a simple solution available, do not try to complicate things. 

I would rate this solution an eight out of 10. 

This solution is connected with our Microsoft license. We use the E3 license, which also includes the software and analytics. We bought it and we are trying to get the best we can from the software. For now, we have some analytics, what's happening, and one of our guys looks at it and prepares reports or maybe requests some additional interventions.

It is mostly for analysis so that when something happens we can analyze it and do something about it.

Our biggest pain point is our housekeeping. We have lot of systems, we must do a lot of configurations and, because of the number of systems is not a simple part of the job, we may forget something. This solution is something which reminds us of what should we do, what stuff is most critical, what we should work on.

We would like to have something that includes the desktops, and perhaps the main system, so we can protect our systems before a threat happens.

My experience with it is that it is stable. The stability is okay and we are satisfied with it.

Our system has approximately 700 servers and a lot of other components and we are satisfied with it at this level.

We went with it because we had it. We had the opportunity to use it and started to do so. Before that, we had several areas where we wanted to improve our status. This is a tool we can check with from Microsoft and, for now, it is good for us.

The most important criteria when selecting a vendor is that the product is user-friendly. A lot of tools that are rated highly in industry reviews have complicated configurations. We would like something which is friendly enough for its administrator to use, to configure. Another criterion is price. We look for solutions we can afford. We read a lot of free white papers and try to find partners that have favorable write-ups. We use the software and do a phone conference where we can discuss further questions which are important to us.

Our firm works in the former Yugoslavia: Croatia, Bosnia, and Serbia, Macedonia, and Montenegro. The prices are different in these markets. Of course, we always want to have the lowest price but that doesn't mean price is the main factor when buying something. It is one of them, for sure. Maybe we cannot afford the most sophisticated tool there is, so price is important, but not the most important thing when we buy something.

We use Microsoft Analytics in the security department to try to raise the level of security analysis and security in general. We have implemented a lot of tools. We also have Nexpose for threat analytics, among others. Microsoft Analytics is just one of them and we implemented it because we already had it.

We tried to buy something for the desktop level. We also have systems like anti-virus, anti-malware, but these are all systems which only partly cover the threats which are now mainstream. So we would like to have a tool we can use that is faster, maybe with predictive analytics.

We have a mixed system. We also use IBM AIX in addition to the Microsoft platform. That means that ATP works successfully with Microsoft for us. If you want to implement it, the benefits are greater if you have a Microsoft in the surrounding systems.

Implementation is always easy. The hard part is then when you must have to use it, when you must work with it. An important part is education, this shouldn't be neglected.

I would rate Azure Analytics at eight out of 10. It gives us what we need, we are satisfied with the results.