![]() The example goes through the process of installing the Bot Framework samples, specifically the Echo Bot template, to generate a simple C# chatbot that's designed to work in the Microsoft Teams channel. The underlying capability templates could be defined as standards for an organization, and reused in multiple solutions.The underlying capability templates can be evaluated and deployed individually.Some of benefits of following this approach are listed below: An end-to-end solution or orchestrator template brings those underlying capabilities together. Typically it will consist of creating Capability templates, similar to units or modules that implement specific pieces of functionality. In such a case, you might want to consider using multiple linked ARM templates to deploy the solution. If you want your chatbot to use Azure Application Insights or Cognitive Services, such as LUIS and QnA Maker, be sure to add them in the template as well. In this example, the generated ARM templates deploy the following resources: The example scenario in GitHub provides the instructions to create the bot application, infrastructure, and the pipeline code. You can store unit test and build pipeline code in the same source control repository. With infrastructure as code, you can define and deploy your underlying infrastructure using ARM templates or open-source alternatives, and also maintain those templates in source control. Source control lets development teams track software code changes and inspect older code versions. The following sections provide more information about the components in the preceding architecture diagram. You can colocate the software and infrastructure code in the same source control repository, and deploy both through your pipelines. Infrastructure as code uses Azure Resource Manager templates ( ARM templates) or open-source alternatives to define and deploy an app's underlying infrastructure. Azure Pipelines can help you accelerate your software delivery and focus on your code, rather than the supporting infrastructure and operations. Azure Pipelines uses modern CI/CD processes to manage software builds, deployments, testing, and monitoring. This solution uses a DevOps approach to set up a CI/CD pipeline that deploys a chatbot app and its infrastructure as code.ĭevOps is a common development strategy for building custom applications like bots. ![]() Application Insights is an extension of Azure Monitor that provides application performance monitoring.įor more information about how these components are used in this solution, see the next section.Azure App Service is an HTTP-based service for hosting web applications, REST APIs, and mobile back ends.It combines continuous integration, continuous delivery, and continuous testing to build, test, and deliver code to any destination. Azure Pipelines automatically builds and tests code projects.Azure DevOps brings PM, design, and engineering together with integrated, collaborative processes to plan work, develop code, and deliver applications.Bot Service is an integrated development environment for building bots.It provides a management layer that you can use to create, update, and delete resources in your Azure account. Azure Resource Manager is the deployment and management service for Azure.Git is a free open-source distributed version control system.Once it gets successfully installed, users can start interacting with the chatbot from its chat window. A Microsoft Teams app package is created, validated, and ultimately published by uploading it as a custom app.Azure Bot Service channels messages from the Microsoft Teams chat to the Azure Web App, where the chatbot logic is running.It is the automated deployment of the chatbot application into the Azure infrastructure that was just provisioned. Continuous deployment is materialized at the second stage in the multi-stage YAML pipeline.It then builds the chatbot application, archives it, and publishes a new drop for the build as a new artifact, which enables continuous integration. A GitHub webhook notifies Azure Pipelines on top of changes in the repository, which triggers the first stage.As a second step in day-0, they will provision the initial required infrastructure in Azure using the generated ARM templates.Developers create a new chatbot, ARM templates for infrastructure, and code the multi-stage YAML pipeline, all hosted from a GitHub repository.Architectureĭownload a Visio file of this architecture. This article presents a DevOps approach to setting up a continuous integration and continuous deployment (CI/CD) pipeline that deploys a chatbot app and its infrastructure as code.
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