This presentation explores a Terraform-based approach to Infrastructure as code. Infrastructure is becoming more and more important for us as developers to understand and develop; it’s no longer only in the hands of the operations team. Terraform is a great tool for infrastructure management.
In this post, l explain how we used Visual Studio Code’s Development Container feature as a stepping stone in our long-term effort to achieve Collaborative Infrastructure as Code. This one step in the process gave a versioned, repeatable working environment and allowed us time to determine the next steps in the effort to achieve IaC.
On my last two projects, I decided to give Azure Data Studio a try to see how it measured up to SSMS. Azure Data Studio gives you a more modern editor experience. It’s comparable to Visual Studio Code with IntelliSense, source control with GIT, and an integrated terminal for Powershell or SQLMD commands.
Azure Data Studio was built with a data platform user in mind, and its easy editing and export options, built-in charting of query results, and customizable dashboards make it an incredibly valuable tool.
In this post, I’ll go over some of the basics of how to use Azure Data Studio.
GitOps provides a declarative approach for improving the management of application delivery.
In this 50-minute video, Keyhole Principal Consultant Jaime Niswonger discusses basic GitOps fundamentals and various implementations in a Kubernetes environment. He covers GitOps best practices that unify deployment, management, and monitoring for containerized clusters and applications. Then he introduces ArgoCD and shows its capabilities in an OpenShift/Kubernetes environment. Jaime includes his own experiences and what he has seen working with companies across various industries.
Infrastructure as Code (or IaC) is the process of using code and versioning in the same way you do your source code to manage your networks, VMS, and Azure resources. IaC generates the same environment every time it is applied, and it’s an important DevOps practice to use alongside continuous delivery.
The release pipeline executes this model to configure target environments. If you need to make any changes, you edit the source, not the target environment. This allows you to create reliable and stable environments on-demand that can be validated, tested, and repeated.
In this blog, we’ll look at how we can use Azure CLI and Azure DevOps Release Pipelines to make this happen. I’ll walk you through all the steps you need to take to get set up.