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Course Outline
Introduction to Graphite and Modern Code Review Workflows
- Overview of Graphite’s architecture and key features
- Understanding stacked pull requests and workflow automation
- Setting up Graphite with GitHub for team-based projects
Graphite Installation and Configuration
- Deploying Graphite in development environments
- Connecting repositories and managing permissions
- Configuring merge queues, PR inboxes, and code review policies
Optimizing Pull Request Workflows
- Implementing stacked PRs and dependency tracking
- Reducing merge conflicts and increasing review speed
- Managing large codebases with Graphite’s review system
AI-Driven Code Review and Productivity Enhancement
- Using Graphite’s AI code review assistant for government applications
- Integrating open source LLMs like Deepseek, Qwen, and Mistral Small for code insights
- Creating automated suggestions and enforcing quality standards
Integrating Graphite with DevOps Toolchains
- Linking Graphite with CI/CD pipelines
- Integrating with GitHub Actions, Jenkins, and other automation tools for government infrastructure
- Ensuring compliance and auditability in enterprise workflows
Analytics, Metrics, and Reporting
- Using Graphite dashboards for team performance tracking
- Identifying bottlenecks and inefficiencies
- Building custom reports and visualizations
Scaling Graphite in Enterprise Environments
- Multi-team setup and governance strategies
- Best practices for large-scale rollout for government agencies
- Security, data retention, and compliance considerations
Hands-On Workshop: End-to-End Implementation
- Setting up a complete enterprise Graphite workflow for government use cases
- Integrating AI-based review pipelines
- Conducting team performance analysis and improvement planning
Summary and Next Steps
Requirements
- Proficiency in Git-centric collaboration processes
- Demonstrated background in software engineering and version management tools
- Knowledge of peer code assessment and continuous integration/deployment frameworks
Target Audience
- Engineering directors and software project management personnel
- DevOps and infrastructure engineering groups
- Senior engineers and principal technical architects
21 Hours
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