Azure Stream Analytics is often the centerpiece of our IoT solutions.
It acts like a rule engine where data streams from multiple sources can be combined together, even enriched with static reference data.
Azure Stream Analytics does not come cheap if you only want to do some simple aggregations. For that, probably Azure Functions can help you out.
But, when it comes to more elaborate rules using multiple inputs, multiple outputs, time windowing, custom functions, and Machine learning integration, Azure Stream Analytics (and many more capabilities) should be your first choice:

Normally, I demonstrate Azure Stream Analytics using the Azure Portal.
There, it offers me a convenient browser experience where I can show how inputs, outputs, and user-defined functions are created. I can also copy/paste a (basic) query and demonstrate how it can be tested and run in a simple manner:

For people new to Azure Stream Analytics, this is a perfect starting point.
Still, this is for demonstration purposes only!
The Azure portal lacks (professional) abilities like source control/versioning, superior user-defined functions, and diagnostics.
If you plan to use Azure Stream Analytics in your projects, please consider starting using the VS Code project template.
In this blog, we will see how to start with the Visual Studio Code project for Stream Analytics.
Doorgaan met het lezen van “Creating an Azure Stream Analytics job using VS Code”