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Duration 21 hours
Course Outline
Introduction to Graphite and Modern Code Review Workflows
- Overview of Graphite’s architecture and core features.
- Exploring stacked pull requests and workflow automation.
- Setting up Graphite with GitHub for team-based projects.
Graphite Installation and Configuration
- Deploying Graphite within development environments.
- Connecting repositories and managing access permissions.
- Configuring merge queues, PR inboxes, and code review policies.
Optimizing Pull Request Workflows
- Implementing stacked PRs and tracking dependencies.
- Minimizing merge conflicts and accelerating review speed.
- Managing large codebases using Graphite’s review system.
AI-Driven Code Review and Productivity Enhancement
- 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.
Integrating Graphite with DevOps Toolchains
- Connecting Graphite with CI/CD pipelines.
- Integrating with GitHub Actions, Jenkins, and other automation tools.
- Ensuring compliance and auditability within enterprise workflows.
Analytics, Metrics, and Reporting
- Utilizing Graphite dashboards for team performance tracking.
- Identifying workflow bottlenecks and inefficiencies.
- Creating custom reports and visualizations.
Scaling Graphite in Enterprise Environments
- Implementing multi-team setups and governance strategies.
- Best practices for large-scale rollout.
- Considerations for security, data retention, and compliance.
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.
- 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
