GitHub

Almost a year ago, I wrote a blog post on how you could use GitHub Models with Semantic Kernel applications for dev and test purposes. Now that the Microsoft Agent Framework is available, I thought I’d create an updated article on how you can use GitHub Models with the new framework, so that you don’t have to provision Azure Foundry and pay for using LLM usage to build agents. What is the Microsoft Agent Framework? It’s an open-source kit for building AI Agents and agentic workflows in Python and C#. The Agent Framework is an extension of both Semantic Kernel and AutoGen projects, and it provides a unified approach for building agents. Both the Semantic Kernel and AutoGen teams are working together to build the Microsoft Agent Framework. ...

For one of my side projects, I use GitHub Actions to build and deploy my various microservices to Azure. In my workflows, I’ll often retrieve a value (such as getting the name of a container registry), and use the set-output command within my pipeline so that I can use the value of that output further down my pipeline. This is an example of what using the set-output command would look like in your GitHub Action workflow: ...

In my job, I build a lot of samples that I share with customers to show them how things work. A lot of my customers are interested in Azure Container Apps, so I want to be able to provide them with samples with pre-built container images, without having to share the entire application source code as well (especially if I’ve got a bunch of basic microservices, that don’t really need to be included in the sample). ...

Microsoft Defender for DevOps is a new capability in Defender for Cloud that provides visibility across multiple DevOps environments that you can use to centrally manage DevOps security, strengthen your infrastructure as code and help you prioritize critical issues in code across your pipeline and multiple cloud environments. This feature is currently in preview, and supports GitHub and AzureDevOps (with support for more platforms coming soon). As part of my job at Microsoft, I spend a lot of time helping engineers to use infrastructure as code to provision their resources to Azure, and help them to build pipelines that automates their deployments. In previous roles, I’ve used static code analysis within build pipelines to scan for vulnerabilities in my application code, so naturally I was keen to give this feature a try and apply it to my Bicep code. ...