I’ve been working on a few Azure IoT Edge projects in the last 2 years. During that period, I always felt that the IoT Edge module projects that are scaffolded by the standard project template are very simplistic.

When you want to use a Named Value in Azure API Management that contains a JSON string in an APIM policy expression, you might run into some problems. In this blogpost, I’m going to cover how I worked around them and finally fixed them.

In 2021, Microsoft released a feature of Azure Container Registry called ‘connected registry’ in public preview. A connected registry allows you to install a container registry on-prem which synchronizes or mirrors with an Azure Container Registry in the cloud. This allows you to have your container images nearby, which is beneficial in scenario’s where you have an occasional or limited connection with the cloud. At the moment that you want to pull a container image, the image doesn’t need to be pulled from Azure, but is already present closer to where you need it.

In this blogpost, I mentionned that it was not possible to execute a SqlAzureDacpacDeployment@1 task. As mentionned here, using Azure AD authentication is not supported on hosted agents, you need to create a private DevOps agent. But, it is possible to execute SQL commands against an Azure SQL Server using Azure AD authentication, albeit not via DacPac.

Querying data in an Azure Data Lake is quite easy with Azure Synapse as explained here. However, when the data that is stored in your Data Lake is not publicly available to everybody (in most cases, you don’t want to have your data exposed to anonymous users), there are some things that you need to consider. In this blog, I’ll try to go over those specificalities.

Creating users in Azure SQL based on Managed Identity or AzureAD accounts is very simple yet very powerfull. However, there are some issues when you want to create those kind of users in your Azure SQL database via Azure DevOps. This post explains how to work around them.

When we want to collect and analyze device-telemetry information, we typically look at solutions like Azure Timeseries Insights, Azure Data Explorer, InfluxDb, … But, what if you actually do not need all the functionality that those services provide ? What if you just want to be able to query the telemetry data and visualize that data in a PowerBI report ? Aren’t there any cheaper alternatives to achieve this ? It turns out, Azure Synapse make this possible using serverless SQL pools.

Azure Data Explorer is a great and powerful platform for when you are working with timeseries data such as sensor measurements and logs. Yet it is not designed to store relational data or act as an OLTP database. However, there can be situations where you want to combine relational data with the timeseries data that is stored in Azure Data Explorer. This post briefly explains how this can be done.

I’ve been blogging on software development in the past on another platform, but that blog didn’t receive any attention anymore from me in the past decade.