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GitHub Copilot and Docker: Smarter AI workflows from code to production

The Docker extension for GitHub Copilot, available today in the GitHub Marketplace, helps to generate portable applications and the cloud native components that keep them running smoothly. Join Derek McGowan, software engineer at Docker, to learn how Docker empowers developers to focus on innovation—closing the gap from first lines of code to production—by standardizing best practices and enabling integrations with tools like Copilot. Using preconfigured workflows for CI/CD pipelines ensures that updates to AI models or code are automatically tested and deployed and reduces manual intervention. Come and explore how this automation supports ongoing efficiency and improvements in AI models and systems.

, Software Engineer, Docker

Session Type: Product Demo

Key Takeaway 1: Accelerate AI/ML development by unifying local and cloud environments, enabling faster iteration and smoother transitions from development to production.

Key Takeaway 2: Generate portable cloud native applications and automate CI/CD workflows to streamline updates and boost development efficiency.

Key Takeaway 3: Simplify infrastructure management and shift focus to scaling AI/ML solutions while ensuring consistency across environments, from local development to cloud deployment.

Topic: AI, Automated Infrastructure Deployment, Cloud, Software Engineering, Collaboration, Productivity

Target Audience: Enterprise - Engineering Leadership, Enterprise - Developers, Open Source Developers or Maintainers

Industry: Applicable to all

Level: Level 200: Intermediate

GitHub Product: Copilot

Delivery Format: In-person, Recorded, On-demand