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Duration 21 hours
Course Outline
Introduction to Graphite and Contemporary Code Review Workflows
- Insight into Graphite’s architecture and primary features
- Grasping the concept of stacked pull requests and workflow automation
- Setting up Graphite alongside GitHub for collaborative team projects
Setting Up Graphite: Installation and Configuration
- Deploying Graphite across various development environments
- Linking repositories and overseeing access permissions
- Tuning merge queues, PR inboxes, and establishing code review policies
Streamlining Pull Request Processes
- Adopting stacked PRs and monitoring dependencies
- Minimizing merge conflicts to accelerate review cycles
- Handling extensive codebases using Graphite’s review framework
Leveraging AI for Code Review and Productivity Gains
- Utilizing Graphite’s built-in AI code review assistant
- Incorporating open-source LLMs like Deepseek, Qwen, and Mistral Small for actionable code insights
- Generating automated suggestions and upholding quality benchmarks
Connecting Graphite to DevOps Ecosystems
- Synchronizing Graphite with CI/CD pipelines
- Integrating with GitHub Actions, Jenkins, and other automation utilities
- Maintaining compliance and audit trails within enterprise workflows
Data-Driven Insights: Analytics, Metrics, and Reporting
- Monitoring team performance via Graphite dashboards
- Pinpointing workflow bottlenecks and inefficiencies
- Developing bespoke reports and data visualizations
Expanding Graphite Adoption in Enterprise Settings
- Establishing multi-team configurations and governance frameworks
- Applying best practices for organization-wide deployment
- Addressing security, data retention, and compliance requirements
Practical Application: End-to-End Implementation Workshop
- Constructing a comprehensive enterprise Graphite workflow
- Incorporating AI-driven review pipelines
- Performing team performance analysis and formulating improvement strategies
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 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
