Azure Data Explorer connector for IoT Hub with real-time ingest

Azure Data Explorer (ADX) is a fully managed, high-performance, big data analytics platform that makes it easy to analyze high volumes of data in near real-time. The Azure Data Explorer toolbox gives you an end-to-end solution for data ingestion, query, visualization (including third-party dashboards), and management.

ADX can ingest data both from (persisted) storage and data provided as a stream:

Ingested data is managed and optimized by the underlying cluster so it can be queried and made available in (third-party) platforms as a view (like Power BI, Grafana, etc.) based on a powerful query language.

Data can also be ingested directly from Azure IoT Hub, as a stream for real-time analysis.

Let’s check out how this works.

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Deploy Prometheus container with Azure IoT Edge

Once you have set up your Azure IoT edge device and runtime, you want to make sure it keeps running as expected. So you need to start measuring how your device, your modules, and runtime are doing.

Microsoft provides built-in metrics for Azure IoT using endpoints on the EdgeHub and EdgeAgent exposing messages in the Prometheus format.

In a previous blog post, I showed how to access these endpoints and not to send messages containing this information to the cloud using a custom Azure IoT Edge metrics module.

Azure IoT Edge can deploy whatever Docker container you have. So, we can also use the original Prometheus service as a Docker container:

This way you can build a local dashboard using well-known tooling on the edge.

Let’s check out how this works.

Using Influx database and Grafana on the Azure IoT Edge

Over the last couple of years, in this blog, multiple databases are demonstrated which can be deployed on the Azure IoT Edge:

• SQL Server
• MySql
• CrateDB
• SQLite

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.

Let’s see how this works.