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Duration 21 hours
Course Outline
Introduction to Graphite and Contemporary Code Review Workflows
- An overview of Graphite’s architecture and core features
- Exploring stacked pull requests and workflow automation
- Configuring Graphite with GitHub for team-based projects
Installing and Configuring Graphite
- Deploying Graphite in development environments
- Linking repositories and managing access permissions
- Setting up merge queues, PR inboxes, and code review policies
Streamlining Pull Request Workflows
- Implementing stacked PRs and dependency tracking
- Minimizing merge conflicts while accelerating review speed
- Managing large codebases using Graphite’s review system
AI-Driven Code Review and Productivity Boost
- Leveraging Graphite’s AI code review assistant
- Incorporating open-source LLMs like Deepseek, Qwen, and Mistral Small for code insights
- Generating automated suggestions and enforcing quality standards
Integrating Graphite into DevOps Toolchains
- Connecting Graphite with CI/CD pipelines
- Integrating with GitHub Actions, Jenkins, and other automation tools
- Ensuring compliance and auditability in enterprise workflows
Analytics, Metrics, and Reporting
- Utilising Graphite dashboards to track team performance
- Identifying bottlenecks and process inefficiencies
- Creating custom reports and visualisations
Scaling Graphite in Enterprise Settings
- Multi-team setup and governance strategies
- Best practices for large-scale rollouts
- Addressing security, data retention, and compliance considerations
Hands-On Workshop: End-to-End Implementation
- Establishing a complete enterprise Graphite workflow
- Integrating AI-based review pipelines
- Conducting team performance analysis and planning improvements
Summary and Next Steps
Requirements
- A solid grasp of Git-based workflows
- Practical experience with software development and version control systems
- Working knowledge of code review 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
