MQTT vs HTTP for IoT: why MQTT and AMQP are the preferred protocols for IoT devices over HTTP, and what makes them better suited for unreliable network conditions.
A clear explanation of the three-path IoT data architecture: cold, warm, and hot. What each path is for, how they differ, and which Azure services handle each one.
Azure IoT Hub explained: what it is, what it actually does, and why it sits at the center of every Azure IoT solution.
IoT explained: what the Internet of Things is, why you’d use it, and which industries are actually putting it to work.
Wrapping up the LUIS DevOps series by deploying the language model to QA and Production: provisioning LUIS resources, importing and training the model, and publishing it automatically from the pipeline.
A detailed look at the Pull Request and Build stages of a LUIS DevOps pipeline: importing, training, testing, and comparing a language model’s performance against its previous version.
The Azure resources, solution files, and test types (unit, performance, regression) behind a LUIS DevOps pipeline, plus a primer on Azure DevOps YAML pipeline structure.
Kicking off a DevOps for LUIS series by looking at the author workflow: how a language model is built in the LUIS portal and exported for developers to bring into source control.
Part 2: reacting to sensor-triggered Azure Digital Twins events with Event Grid, Azure Functions and SignalR Service to restyle a room on the floor plan in near real-time.
Part 1: creating a floor plan as an SVG in Inkscape, linking a room to its Azure Digital Twins space Id, and displaying it inline on an ASP.NET Core page with a custom Tag Helper.
Sending IoT device data to the browser in near real-time using an IoT Hub trigger in Azure Functions, an output binding to Azure SignalR Service, and a static website hosted on Azure Storage.
Part 2: building an ARM template for a Bot Framework v4 bot’s Azure resources and creating an Azure DevOps release pipeline that provisions, deploys, and configures the bot automatically.
Part 1 of setting up Continuous Deployment for a Bot Framework v4 bot: configuring LUIS and Application Insights on a sample bot project and creating a CI build pipeline in Azure DevOps.
How to add Application Insights to a Bot Framework v4 bot by configuring the service in the .bot file and wiring up a TelemetryClient to log exceptions during conversations.
Using Azure Logic Apps to collect World Cup tweets, Cognitive Services to translate them and extract key phrases, and Power BI to reconstruct the timeline of goals scored during a match.
Provisioning a SonarQube server on Windows and SQL in Azure with a ready-made ARM template, then upgrading it through the required version path to the latest release.