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Workflow Recipes Overview

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Joao Palma edited this page Jan 29, 2026 · 4 revisions

Workflow Recipes Overview

Real-world workflow examples using DotRun across different team types and development scenarios. Each workflow provides complete setup instructions, script collections, and team collaboration patterns.

Available Workflows

Full-Stack Development

Complete web development workflow for teams using React frontend, Node.js backend, and PostgreSQL database.

Best for:

  • Web development teams (3-10 developers)
  • React + Node.js + PostgreSQL stack
  • Agile development with frequent deployments
  • Teams needing integrated frontend/backend tooling

Includes:

  • Frontend build and development scripts
  • Backend API development and testing
  • Database setup and migration tools
  • Integrated deployment pipeline
  • Team collaboration workflows

DevOps Pipeline

Enterprise-grade DevOps workflow for managing microservices on Kubernetes with comprehensive monitoring and security.

Best for:

  • DevOps and Platform teams
  • Microservices architecture
  • Kubernetes-based infrastructure
  • Enterprise environments requiring security and compliance

Includes:

  • Infrastructure automation (Terraform)
  • Kubernetes cluster management
  • Microservice deployment strategies
  • Monitoring and alerting
  • Security scanning and compliance

Data Science Team

Complete data science workflow with model training, experiment tracking, and deployment automation.

Best for:

  • Data science and ML engineering teams
  • Python-based ML workflows
  • Jupyter notebook environments
  • Model deployment and monitoring

Includes:

  • ML environment setup automation
  • Experiment tracking and management
  • Model training and validation pipelines
  • Data processing and analysis tools
  • Model deployment and serving

QA Automation

Comprehensive testing workflow covering web, API, and performance testing with reporting automation.

Best for:

  • QA and testing teams
  • Automated testing pipelines
  • Multi-platform testing (web, mobile, API)
  • Performance and load testing

Includes:

  • Automated test execution
  • Cross-browser testing
  • API testing and validation
  • Performance and load testing
  • Test reporting and metrics

Startup Development

Rapid development workflow optimized for small teams and quick iterations.

Best for:

  • Startup teams (2-5 developers)
  • Rapid prototyping and iteration
  • Resource-constrained environments
  • Simple deployment workflows

Includes:

  • All-in-one development setup
  • Rapid deployment scripts
  • Cost-effective infrastructure
  • Simplified team onboarding

Workflow Selection Guide

By Team Size

Team Size Recommended Workflows
1-3 developers Startup Development
3-10 developers Full-Stack Development
10+ developers DevOps Pipeline + specialized workflows

By Technology Stack

Stack Primary Workflow Additional Workflows
React + Node.js Full-Stack Development QA Automation
Microservices + K8s DevOps Pipeline Full-Stack Development
Python + ML Data Science Team DevOps Pipeline
Multi-platform QA Automation DevOps Pipeline

By Development Phase

Phase Focus Areas Recommended Workflows
Prototype Rapid development, simple deployment Startup Development
MVP Testing, basic automation Full-Stack Development
Scale Infrastructure, monitoring, security DevOps Pipeline
Enterprise Compliance, multi-team, governance All workflows with enterprise patterns

Common Patterns Across Workflows

Script Organization

All workflows follow consistent organization patterns:

bin/
├── development/     # Local development tools
├── testing/         # Test automation
├── deployment/      # Deployment scripts
├── monitoring/      # Health checks and monitoring
└── maintenance/     # Cleanup and maintenance

Team Collaboration

Standard collaboration patterns used across workflows:

  1. Collection Import: dr import <repo> <name>
  2. Daily Workflow: Documented command sequences
  3. Code Review: Automated validation scripts
  4. Documentation: Comprehensive inline and markdown docs

Environment Management

Consistent environment handling:

  • Development: Local setup and testing
  • Staging: Integration testing and QA
  • Production: Secure deployment and monitoring

Getting Started

1. Choose Your Workflow

Select the workflow that best matches your team size, technology stack, and development phase.

2. Import the Collection

Each workflow provides a Git repository you can import:

dr import <workflow-repo-url> <collection-name>

3. Customize for Your Team

Adapt the scripts and configurations to match your specific:

  • Technology choices
  • Deployment targets
  • Team processes
  • Security requirements

4. Establish Team Practices

Set up regular practices for:

  • Collection updates
  • Script maintenance
  • Documentation updates
  • New team member onboarding

Advanced Multi-Workflow Setups

Enterprise Multi-Team Setup

Large organizations often use multiple workflows:

# Shared infrastructure
dr import git@company.com/infrastructure.git infra

# Team-specific workflows
dr import git@company.com/frontend-tools.git frontend
dr import git@company.com/backend-tools.git backend
dr import git@company.com/data-tools.git data
dr import git@company.com/qa-tools.git qa

# Cross-team collaboration
dr infra/setup-environment team-a
dr frontend/deploy-staging
dr qa/test-environment staging

Workflow Evolution

Teams often evolve through workflows as they grow:

  1. Start: Startup Development
  2. Grow: Full-Stack Development
  3. Scale: DevOps Pipeline
  4. Specialize: Add Data Science or QA Automation

Best Practices

Collection Management

  • Version Control: Tag stable releases of collections
  • Documentation: Keep README and docs updated
  • Testing: Validate scripts before sharing
  • Security: Review scripts for sensitive data

Team Adoption

  • Gradual Rollout: Start with one workflow, expand gradually
  • Training: Ensure team understands DotRun concepts
  • Feedback: Collect and incorporate team feedback
  • Maintenance: Assign ownership for collection updates

Customization Guidelines

  • Fork, Don't Modify: Fork workflows to customize for your team
  • Contribute Back: Share useful improvements with the community
  • Document Changes: Maintain clear documentation of customizations
  • Stay Updated: Regularly sync with upstream improvements

Community Workflows

Contributing New Workflows

Have a workflow that would benefit others? Consider contributing:

  1. Document thoroughly: Include setup, usage, and examples
  2. Follow patterns: Use consistent organization and naming
  3. Test completely: Ensure scripts work in clean environments
  4. Submit PR: Share with the community via pull request

Workflow Requests

Need a workflow not listed here?

  • Check existing: Look for similar workflows to adapt
  • Request: Create a GitHub issue describing your needs
  • Collaborate: Work with community to develop the workflow

Support and Resources

Getting Help

  • Documentation: Each workflow includes comprehensive docs
  • Examples: Working examples in each workflow repository
  • Community: GitHub discussions and issues
  • Support: Professional support available for enterprise teams

Additional Resources

Choose your workflow and get started! Each workflow is designed to provide immediate value while scaling with your team's growth and changing needs.

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