Do not treat this objective as a recognition exercise. Practise explaining and applying 'Implement security best practices: Understand GITHUB_TOKEN lifecycle (ephemeral, scoped), configure granular permissions, contrast with PAT; restrict write scopes' in a new scenario, then check your reasoning against the official source. Source context: Read in English Implement CI/CD pipelines for multi-agent systems with GitHub Actions Module 7 Units Feedback Advanced AI Engineer DevOps Engineer Solution Architect Azure Microsoft Foundry GitHub Implement enterprise CI/CD pipelines for multi-agent systems using GitHub Actions and Microsoft Foundry. Design coordinated deployment pipelines with agent version compatibility validation, implement progressive deployment strategies including canary releases, configure multi-environment agent deployments with infrastructure as code, and automate rollback triggered by quality regression detection. Learning objectives By the end of this module, you'll be able to: Design CI/CD pipelines that validate version compatibility across interdependent multi-agent systems Implement progressive deployment strategies including canary releases and blue-green deployment for agent updates Configure multi-environment deployment strategies for agent ecosystems from development through production Automate rollback procedures triggered by quality regression detection Add Prerequisites Before starting this module, you should have: Experience with GitHub Actions for CI/CD workflows in AI projects Familiarity with Microsoft Foundry project deployment Understanding of infrastructure as code with Bicep or Terraform Experience with GenAIOps practices from the Operationalize generative AI applications learning path or equivalent Proficiency in Python and YAML Get started with Azure Choose the Azure account that's right for you.
Objective
Implement security best practices: Understand GITHUB_TOKEN lifecycle (ephemeral, scoped), configure granular permissions, contrast with PAT; restrict write scopes