Getting Your IoT Projects Off The Ground By Building On Azure

/ 02 May, 2022

With the popularity of the Internet of Things, new proof of concepts and prototypes are starting everywhere. If you’re contemplating getting started with IoT or need a nudge in the right direction, this article will highlight some great options to get you started. Now, some projects go nowhere, with others end up being very successful. But even in the latter case, a new IoT platform will still fail if the wrong choices were made in the technology selection, right at the project’s inception.

An IoT solution will have a couple of key components, even for a prototype. There needs to be a robust messaging system in place. This allows you to have bidirectional communication with your devices. You also need to store a collection of devices you can trust and their configuration to run correctly. These devices live at “the edge”, a collective term for anywhere from a factory, train tracks, or someone’s home. These devices could range from tiny microcontrollers to more powerful computers running artificial intelligence workloads. Both will send messages to the platform, and when these messages are received, they are transformed, analyzed, and visualized to extract insights from the data. The information is then stored, preferably in different ways for long-term storage vs. storage that needs to be readily available. With so many moving parts, choosing the right technology becomes critical because it will impact your project’s future.

One example of a project I’ve seen came to a grinding halt through the weight of its own complexity. A small IoT prototype was a success and became part of the company’s core business. But it simply wouldn’t scale any further than a couple of devices. The technologies used to develop this project seemed “fine” at the time. Surely you can come back to fix this, right? But a couple of years later, they’re running a custom message broker and a handful of databases and spreadsheets to tie everything together. IT doesn’t want to host their platform, and it’s now running in your “private cloud” in the attic.

The software described above is not an exaggeration, and I’m sure there are many more platforms out there like it. And who can blame the authors of these projects? They might have been trying something new, using the skills they had at that moment. When the prototype became a success, it was put into production instead of turning it into a scalable solution first. So how can you avoid making the same mistake?

Build for success with Azure

Instead of building and designing everything from scratch, you can get a head start by using Azure platform as a service (PaaS) components. These are the same components used for global-scale IoT platforms, managing millions of devices. While at first, this might sound like an excessive measure for a prototype with just a few devices, the PaaS components in Azure scale remarkably well. The best place to start for most platforms is Azure IoT Hub. You can get started with a fully-featured IoT Hub for about 20 Euros per month, and with 400.000 IoT messages per day, it will be a long time before you have to scale it up. So even for a proof of concept, you can spin up your own IoT Hub and save yourself the trouble of having to host hosting custom message broker, identity management, and message routing solutions.

When using IoT Hub, you have many options to transform and analyse the data you’re receiving. A typical scenario with new projects is starting with Azure Functions to transform and bring data from one place to another. Moving to Azure Stream Analytics can be a great choice when the requirements become more complex or need to consider time windows. It allows you to run analytics over data streams and extract the most critical insights. It also has built-in anomaly detection, a complex feature to build from scratch.

Another great place to start is Azure IoT Central. This software as a service (SaaS) product builds on top of IoT Hub and other Azure components to offer a highly scalable product. You can be the proud owner of an IoT Central instance in minutes for a few cents per month, so pricing shouldn’t be a limiting factor. It has dashboarding, device registration, a ruling engine, and even some new multi-tenancy features built-in. This means you can start to impress your organization with a complete IoT platform without reinventing the wheel. And if there are features you need that aren’t in Azure IoT Central, you can stream the device data to your own software. Your IoT prototype became so successful that the organization wants to include the data into their CRM platform? No problem, stream the data to Service Bus or Event Hub for further processing or send it directly to an HTTP endpoint of your choice.

In both cases, you get a huge jump-start in functionality and can get started with something much more important: building the features only you can create. You know your business better than anyone else, so build on these world-class components and focus on what you do best. Building an IoT platform shouldn’t be about making all the plumbing, time and again. It’s about realizing value.

Cloud logic, at the edge

Following the advice above, you will have a great start in the cloud, but IoT also involves devices. Your project could use off-the-shelf hardware, but you might need a device that doesn’t exist yet. Creating IoT devices is usually done by professional device builders. Combining electronics and writing code for microcontrollers is not a skill every developer has. But that doesn’t mean you can’t build simple prototypes. You can get started by building devices with Arduino or .NET nanoframework. The latter gives you a subset of the .NET CLR to write software for microcontrollers in C#. Getting started with nanoFramework is blazingly fast, and the different applications you can write with it deserve their own article. The most important thing is both Arduino and nanoFramework have many libraries available to do the heavy lifting, so even on the edge, you’re able to get started quickly.

But you might need more robust hardware. If you’re running AI at the edge or need to go beyond the constraints of a microcontroller, Azure IoT Edge will accelerate your device solution. It allows you to write device software in a language that you probably already use in your day job. If you know .NET, Python, Node.js, Java or C, and have some experience creating Docker containers, you have what it takes to be an Azure IoT Edge developer. Another benefit of Azure IoT Edge is you can use CI/CD to deploy updates to your device, so the development process should be familiar.

Microsoft also supplies standard IoT Edge modules for Azure Functions, SQL databases, Stream Analytics and more. Hence, like in the cloud, build on these existing modules to avoid reinventing the wheel.


Getting a new IoT project off the ground can be tricky. Starting with small prototypes and proof of concepts is an excellent way of testing the waters. Chances are, you already have what it takes to get started on the edge. There have never been more options for software developers to get involved without much-embedded development experience, be it microcontrollers or edge computing devices. And when you start by building on the same secure, reliable, and high-performing cloud components that support millions of devices worldwide, you can focus on what makes your project unique. And when the time comes to scale up your platform, you won’t ever have to run your platform from your attic.

Why it’s so important to choose the right tools for the job

One of the essential values of Xpirit is “Quality Without Compromise”. This value bleeds into every decision we make, so when we decide on the right tools to start an IoT prototype or proof of concept, we go for the same cloud components we would use for large-scale projects. Because these components scale very well for performance and pricing, there is no reason not to choose the best tools available. Remove the risk of starting from scratch when you want to bring your proof of concept to production by not reinventing the wheel.