Power BI makes it really easy to import data, create reports with rich visuals, and then gain insights to make decisions. However one of the tricky things that I found when learning Power BI was that most of the example datasets were for sales and marketing data.
When should you use a bar chart? A donut chart? A funnel chart? Existing tutorials answer these questions fine– but what if you have telemetry or metrics for software projects?
In this post I share some Power BI chart and data model examples that are bit more relevant for software engineers. This makes it easier to build the best possible dashboards for your software or production systems telemetry.
Linting tools provide a way for us to automatically analyze source code to find bugs and style problems. Adding these tools to your project will help enforce coding best practices and maintain them as the project grows. In this post we demonstrate how to configure linting for PowerShell code projects in the Visual Studio Code editor using the PSScriptAnalyzer toolset.
I wrote an MSDN blog post a few years back (here) that demonstrated how to run PowerShell scripts by hosting the PowerShell runtime inside a C# / .NET application. A few things have changed since that post; including the introduction of .NET Core and PowerShell Core, better async support, and a few new best practices.
In this article we will jump forward to take a look at runspace execution for PowerShell Core and .NET Core applications. Including topics like project setup, runspace usage examples, stream handling, shared app domain use cases, and some helpful troubleshooting tips.
This is the third and final post in a series I’m writing on Azure’s Application Insights (AI) service. In the previous post we looked at how to create monitoring dashboards in Azure.
Here in this post we run through some examples for how to configure monitoring alerts with built-in Azure resource metrics and custom instrumented events and metrics.