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Git Workflow and Pipelines

This section presents a practical Git workflow example that illustrates how branches and releases can trigger automation pipelines. Based on the popular Git flow model, it helps manage multiple environments—dev, qa, and prod—but can be adapted to fit your project's needs.

Overview

The diagram below illustrates our workflow for delivering a new feature (here “Feature X”) as part of release 1.0.0. Each automated pipeline plays a role in the process—some ensure code quality or run AI-assisted evaluations, while others handle deployment to the appropriate environment.

Git Workflow

Steps

  1. Create a Feature Branch Create a new branch off of develop for your work on Feature X:

    Do all your development in feature/feature_x.

  2. Open a PR to develop When your changes are ready, push the branch and open a PR against develop. This fires the PR Evaluation Pipeline (linting, unit tests, AI-driven checks):

  3. Merge into develop & Deploy to dev Once approved, merge the PR into develop. That triggers:

    • CI Pipeline: Builds the flow and runs full AI-assisted tests.
    • CD Pipeline: Deploys the updated flow to the dev environment.

  4. Create a Release Branch Creating this branchtriggers the CD Pipeline to deploy to qa for UAT and red-teaming.

  5. Open a PR to main from the Release Branch When the new Release passes QA, open a PR targeting main

  6. Create Final Release & Deploy to prod Tag the final version on main and publish a GitHub Release:

    This final tag triggers the CD Pipeline to deploy v1.0.0 to the prod environment.

CI/CD Pipelines

The CI/CD (Continuous Integration/Continuous Deployment) pipelines automate integration, evaluation, and deployment processes, ensuring efficient delivery of high-quality applications.

Pipelines

The Pull Request Evaluation Pipeline begins with unit tests, followed by a code review to validate code changes before integration.

In the Continuous Integration Pipeline, the process starts with unit tests and code reviews, followed by GenAI-assisted flow evaluation to identify potential issues. The application is then built, and the flow image is registered for deployment.

The Continuous Deployment Pipeline operates across three environments: dev, qa, and prod. Provisioning of resources is performed when necessary, and the deployment of the application is executed in the respective environment.

  • In the dev environment, the latest code is pulled, and the application is deployed for the development team's testing.

  • In the qa environment, the code is retrieved, and AI-assisted evaluations for quality and safety are conducted, followed by integration testing. The application is then deployed and made available for User Acceptance Testing (UAT).

  • In the prod environment, the same image built in the Continuous Integration Pipeline is deployed, ensuring consistency and reliability. Integration testing is conducted, and smoke testing ensures functionality post-deployment.

This structured approach streamlines workflows, reduces errors, and guarantees the efficient delivery of applications to production.