In part 2 of the series about Change Data Capture (CDC) in Azure Data Explorer, we look at another approach on how to handle data when only changes from the device to the cloud are sent.
Change Data Capture (CDC) is a design pattern to only track the changes in data. There are several ways this could be implemented. In IoT solutions, the Change Data Capture (CDC) pattern is used, to only send changes from the device to the cloud. But how to deal with this data in Azure Data Explorer for further analysis?
What if you have an Azure IoT solution and recently added Azure Data Explorer (ADX), and you also want to ingest your historical data. Then LightIngest might be the solution, a lightweight tool for importing data into Azure Data Explore.
Automatically deploy (layered) deployments to Azure IoT hub using Infrastructure as code (IaC). Because it makes your IoT hub deployments repeatable and more consistent.
How to create an Azure IoT hub with Bicep. But what is Bicep anyway and why should we use it. In this article, I will explain about Bicep and we will create a simple Bicep example to deploy an IoT hub.
At some point in your IoT project, you will need to create or update the modules of the IoT edge devices. When more and more devices are added, it becomes impossible to deploy the configurations by hand. In this article I explain the different possibilities for automatic deployments and I will walk you through the steps.
Unexpected Azure Storage Account transactions caused by Azure Function BlobTrigger, how to identify the problem and how to solve it.
How to save costs with azure automation account runbooks. In this showcase we added an Azure Automation Runbook to remove the Bastion Service every night. This will reduce the costs up to almost 140 euro per month.
High quality data is necessary to create reliable business insights, but how do you evaluate this for Azure Stream Analytics? In my latest article, I will explain how this can be done by creating test cases for Stream Analytics.