Persisting incoming telemetry in a local database is useful for multiple purposes. One of them is creating a custom dashboard eg. written in Blazor.
In this blog, we explore how to deploy the popular InfluxDB. This open-source time-series database is specialized in Internet of Things usage. And on top of that, let’s explore how Grafana can be deployed on the edge too. Grafana is an open source analytics and interactive visualization web application.
We see how it can be connected to the Influx database:
As you see here, we need a custom Azure IoT Edge module (called ‘writer’) that is capable of writing incoming telemetry to the Influx database. There, the telemetry is picked up and displayed by Grafana.
If you have built an IoT Device yourself and are finally able to send telemetry to the cloud, you should be familiar with the scenario where you have to repeat the hard work of describing the messages all again on ingestion.
IoT Devices expose D2C telemetry and it can also support C2D communication. This interface is most of the time unique for that device. To be able to get insights from a device you have to be able to react to its interface.
Wouldn’t it be nice if a device was able to provide metadata about its interface once it connects to the cloud? This way, the incoming D2C telemetry could automatically result in e.g. a full user interface. And all C2D output could be represented by pre-configured input controls.
IoT Plug and Play enables solution builders to integrate smart devices with their solutions without any manual configuration. At the core of IoT Plug and Play, is a device model that a device uses to advertise its capabilities to an IoT Plug and Play-enabled application