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Duration 21 hours
Course Outline
Foundations of Graphite and Contemporary Code Review Workflows
- Overview of Graphite’s architecture and primary features
- Concepts behind stacked pull requests and workflow automation
- Setting up Graphite with GitHub for collaborative team projects
Installation and Configuration of Graphite
- Deploying Graphite in development settings
- Connecting repositories and managing access permissions
- Configuring merge queues, PR inboxes, and code review policies
Streamlining Pull Request Workflows
- Implementing stacked PRs and tracking dependencies
- Minimizing merge conflicts to accelerate review speed
- Managing extensive codebases using Graphite’s review system
AI-Powered Code Review and Productivity Gains
- Leveraging Graphite’s AI code review assistant
- Integrating open-source LLMs such as Deepseek, Qwen, and Mistral Small for enhanced code insights
- Generating automated suggestions and enforcing quality standards
Graphite Integration with DevOps Ecosystems
- Connecting Graphite to CI/CD pipelines
- Integrating with GitHub Actions, Jenkins, and other automation tools
- Ensuring compliance and auditability in enterprise workflows
Analytics, Metrics, and Reporting
- Utilizing Graphite dashboards for team performance monitoring
- Identifying workflow bottlenecks and inefficiencies
- Creating custom reports and data visualizations
Scaling Graphite for Enterprise Environments
- Multi-team configurations and governance strategies
- Best practices for large-scale deployment
- Considerations for security, data retention, and compliance
Practical Workshop: End-to-End Implementation
- Establishing a complete enterprise-grade Graphite workflow
- Incorporating AI-based review pipelines
- Performing team performance analysis and planning improvements
Conclusion and Future Directions
Requirements
- A solid grasp of Git-based workflows
- Practical experience with software development and version control systems
- Familiarity with code review processes and CI/CD concepts
Target Audience
- Engineering leads and software development managers
- DevOps and platform engineering teams
- Senior developers and technical architects
Testimonials (1)
That i gained a knowledge regarding streamlit library from python and for sure i'll try to use it to improve applications in my team which are made in R shiny