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Duration 21 hours (3 days)
Course Outline
Introduction to Graphite and Contemporary Code Review Workflows
- Overview of Graphite’s architecture and core capabilities
- Comprehending stacked pull requests and workflow automation
- Configuring Graphite with GitHub for team-oriented projects
Installing and Configuring Graphite
- Deploying Graphite within development environments
- Linking repositories and administering permissions
- Setting up merge queues, PR inboxes, and code review policies
Enhancing Pull Request Workflows
- Adopting stacked PRs and tracking dependencies
- Minimizing merge conflicts while accelerating review times
- Handling large codebases effectively using Graphite’s review system
AI-Powered Code Review and Productivity Boost
- Leveraging Graphite’s AI code review assistant
- Integrating open-source LLMs like Deepseek, Qwen, and Mistral Small for deeper code insights
- Generating automated suggestions and enforcing quality standards
Integrating Graphite into DevOps Toolchains
- Connecting Graphite with CI/CD pipelines
- Integration with GitHub Actions, Jenkins, and other automation tools
- Maintaining compliance and auditability in enterprise workflows
Analytics, Metrics, and Reporting
- Utilizing Graphite dashboards for monitoring team performance
- Spotting bottlenecks and areas of inefficiency
- Developing custom reports and data visualizations
Scaling Graphite for Enterprise Settings
- Establishing multi-team structures and governance strategies
- Best practices for large-scale deployment
- Addressing security, data retention, and compliance requirements
Hands-On Workshop: Complete Implementation
- Building a full-scale enterprise Graphite workflow
- Implementing AI-based review pipelines
- Performing team performance analysis and planning improvements
Wrap-Up and Future Steps
Requirements
- A solid grasp of Git-based workflows
- Practical experience with software development and version control systems
- Familiarity with code review practices 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