Deploying a secure MQTT test server on Azure with IPv6

MQTT (originally Message Queuing Telemetry Transport) is an important protocol for IoT that has been widely adopted. Devices deployed to the field may be connecting to existing MQTT endpoints, however you may also want to deploy your own MQTT server for testing purposes.

This article shows you how to deploy an Eclipse Mosquitto MQTT server onto Azure, configured for secure connections (MQTTS, which is MQTT over TLS), accessible over the internet, and including support for both IPv6 and legacy IPv4.

First we will configure a network in Azure, then deploy the server, and then test the deployment.

The instructions below show the individual commands, but if you want a quick start then full scripts, with automatic parameters, are available on Github

To deploy the network and then server components via the scripts:

az login
az account set --subscription <subscription id>
$VerbosePreference = 'Continue'
./azure-mosquitto/infrastructure/deploy-mosquitto.ps1 YourSecretPassword

Read on for the full details.

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LoRaWAN to Azure IoT — Unboxing the Dragino LDDS75

LoRaWAN devices are a popular solution for IoT, with many benefits, but they cannot connect directly to Azure IoT.

LoRaWAN devices communicate using LoRa to a local LoRaWAN gateway, which then communicates using standard protocols to a LoRaWAN network server. Only then can it be converted to a suitable IP-based protocol to connect to Azure IoT.

Even if they did share a common network, LoRaWAN IoT devices are often small, low-power, battery operated devices that operate in short bursts of minimal communication, and not the verbose communication expected by Azure IoT, so you would want to use a gateway anyway.

To test out connecting field-ready LoRaWAN devices to Azure IoT, I ordered a Dragino LDDS75 LoRaWAN Distance Detection Sensor, used to measure the distance between the sensor and a flat object. It can be used for both horizontal and vertical distance measuring, such as liquid level measurement or object detection (e.g. parking space).

Unboxing the Dragino LDDS75 Distance Detection Sensor

The Dragino platform uses open source hardware, with Dragino schematics and details fully available on github, although you are probably better off purchasing one than trying to build it yourself.

I set up the device up using The Things Network, a community network suitable for small scale testing, connected to Azure IoT.

Dragino, The Things Nework (LoRaWAN Gateway and LoRaWAN Network Server), and Azure IoT architecture overview

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Code First Azure Digital Twins — a first look

Telstra has a large Internet of Things portfolio, with Digital Twins one of the focus areas for Telstra Purple professional services. All major providers are supported, including Azure Digital Twins.

The team recently took some core bits out of project they are working on with code first Azure Digital Twins and have released it as an open source library, so I thought I would share an initial look at the project.

Why code first? Using a code first approach can make accessing Digital Twins easier for developers. They can use their native programming language and tools to develop their models, without having to learn the intricacies of DTDL (Digital Twins Definition Language) or the REST APIs for interacting with Azure Digital Twins.

The library can be found at

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Azure CLI vs PowerShell vs ARM vs Bicep

A key component of DevSecOps is infrastructure-as-code, and if you are using Azure there are multiple ways to specify what you want.

Microsoft provides Azure PowerShell, the Azure CLI, as well as both Azure Resource Manager (ARM) and the newer Bicep templates. There are also third party (and cross-cloud) solutions such as Terraform and Pulumi.

In the past I have been leaning towards Azure CLI, as I found ARM templates a bit cumbersome, plus my previous experience with migrations vs desired state for database deployments. With Bicep being promoted as a lighter weight alternative I thought I would compare the Microsoft alternatives.

Having now revisited the options, I still prefer scripting, but think I will switch more to PowerShell, particularly as it makes it easier to follow to the tagging, and naming, guidelines.

My recommendations:

  • For incremental development or changing environments, use Azure PowerShell scripts. They allow easy manipulation of parameters, and a migration/scripted approach can handle changes that a desired state/template approach can not.
    • If you are already heavily invested in an alternative scripting system, e.g. Bash, then Azure CLI would be easier to use.
  • If you have relatively stable infrastructure, such as a preset development environment or sample/demo code, that you want to repeatedly tear down and then recreate the same, then Bicep offers a nicer syntax than raw ARM templates. The deployments are viewable in the Azure portal, but templates do have some limitations compared to scripting.
  • In either case, follow the Azure Cloud Adoption Framework naming guidelines, allowing for unique global resources, as well as the associated tagging guidelines.

Example code is available on Github at

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IPv6 virtual networks on Azure

IPv6 support for Azure VNets is currently available in preview (

Most of it is available via the Azure Portal, but I found allocating an IP config to a network card had to be done via the shell.

Here are the steps I did to test:

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