So, you’ve heard about Azure Functions? Possibly read about them somewhere? Why all the fuss? What exactly are Azure Functions? Well, you’ve stopped at the right place. In this post and the next couple of posts, I’m going to talk about Azure Functions, along with their history, use cases and some tutorials. So, let’s get started.
I’ve recently had a lot of interaction with customers who have asked about Microsoft’s partnership with Citrix. More specifically, different people have asked how Citrix Cloud can be coupled with Azure in order to deploy a Citrix XenDesktop environment into Azure IaaS.
In this video, I don’t necessarily show the setup process. But, I do demonstrate a Raspberry PI 3 VDI client connecting to Citrix Cloud hosted Storefront and running XenDesktop/XenApp from a Windows Server 2016 machine in Azure. One interesting thing is seeing how responsive a YouTube video is while running on a Raspberry PI. Instead of the typical constraints imposed by the PI (e.g. processor, RAM, etc.), I’m leveraging the full resources of Windows Server while letting the VDI client simply render changes in the video to the user. The performance, I believe, is quite good – especially, when considering the possible deployment of such a device within the enterprise.
All in all, this makes for a very secure, economical VDI client.
First demonstrated at Microsoft’s 2016 Ignite Conference in Atlanta, GA, the IoT Asset Management Starter Kit is a boiler plate project comprised of Node.js and Angular 2 that facilitates the quick development of an IoT project for Asset Management. The project brings all the necessary components – Azure IoT Hub, Stream Analytics, Heroku, MongoDB and Raspberry Pi 3 – together to build a working end-to-end IoT solution.
A couple of weeks ago, I had the privilege of doing a live broadcast on Microsoft’s Channel 9 Developer Network. In the broadcast, I discussed various uses for the Internet of Things (IoT) across different industries. In particular, I followed an original story line from the previous couple of broadcasts that involved using BI for retail establishments to gather sales and marketing insights for driving revenue.
I’ve taken that story to the next level in examining some ways we can use IoT for predicting sales and being more proactive in marketing initiatives by monitoring human behavior. If you’re interested, check out the video.
It seems that when Microsoft deployed their latest versions of Office, they forgot to adjust the DPI (dots per inch) settings for PowerPoint rendering the menus on second monitors extremely large. With the menu and its fonts so large, the design space on a secondary monitor is very limited, if not useless altogether.
Last week Microsoft just released Azure VNet peering – a highly-requested and long-awaited internetworking feature – into public preview. VNet peering provides the ability to join two VNet’s, or virtual networks, in the same region using Microsoft’s Azure backbone network. Because of this functionality, all resources appear to be on the same network as compared to being on two separate networks that are simply connected. VNet peering is just another giant step in making Microsoft Azure a game-changer for hybrid networks.
The scatter diagram, or scatter plot, is a type of mathematical diagram of XY coordinates used to display values for a set of data. Typically, one value is under control while the other varies based on our control. For a quality assurance example, our control may be the number of features, while the variable is the number of bugs. The data for a scatter diagram is based over time or experience.
A Pareto Chart allows you to quickly identify the problem areas of your application by reporting those areas that have the greatest number of issues. The philosophy of the Pareto Chart is based on the 80/20 rule – by identifying and fixing the larger areas first, the application can be stabilized a lot quicker. Or, more specifically, correcting 20% of the currently known bugs will stabilize 80% of the application.
A histogram is a very simple diagram and doesn’t take much time to create. It illustrates a data point in history in order to calculate the probability of something happening in the future. In general, if we notice a trend of a event or action happening in a specific period, we can plan for the same event or action in the future, given the same circumstances.
Control charts are used for statistical analysis to determine if a process is in a stable state of control. Control charts are very similar to run charts, except that control charts have additional lines for upper and lower control limits. Control charts help us to determine the effectiveness of our quality control over time and view irregularities in order to improve our control quality.