All terms
Development

What is Trunk-Based Development

Development in single branch

Trunk-Based Development is a development methodology where all developers work in a single main branch (trunk/main), making frequent small commits.

Key Principles

  • All changes go directly to main/trunk
  • Short-lived feature branches (1-2 days max)
  • Frequent commits (several times a day)
  • Continuous integration is mandatory

Benefits

  • Minimized merge conflicts
  • Fast feedback
  • Simple commit history
  • Accelerated CI/CD processes
  • Reduced integration risk

Practices for Success

  • Feature Flags — hiding incomplete features
  • Trunk-based + Short-lived branches — branches for 1-2 days
  • Continuous Code Review — constant code review
  • Automated Testing — automated tests on every commit

Comparison with Git Flow

| Aspect | Trunk-Based | Git Flow | |--------|-------------|----------| | Branches | 1 main | Many long-lived | | Releases | Continuous | Scheduled | | Complexity | Low | High | | Conflicts | Rare | Frequent |

When to Use

  • Experienced teams with good test coverage
  • Projects with CI/CD
  • When frequent releases are needed

Benefits

Data Security. 24/7 automated threat monitoring. User behavior anomaly detection. Encryption and access control at all levels. Fraud losses reduced by 85%.

How to Start

Step 1: Integrations. Analyze existing systems and their API capabilities. Define integration points and data formats. Set up middleware for data exchange. Test integrations on real data before go-live.

ROI & Efficiency

Logistics ROI. Logistics costs drop 40% through route optimization. Inventory turnover increases 45%. On-time delivery reaches 95%. Product returns decrease 35% with better quality control.

Common Mistakes

Poor Data Quality. Garbage in, garbage out. Automation amplifies data problems exponentially. Conduct data quality assessment before starting. Set up validation and cleansing pipelines. Define a single source of truth.

Who Needs It

Consulting & Legal. Consulting firms automating reporting workflows. Law firms with high document volumes. Audit firms optimizing review processes. Businesses needing contract lifecycle management.

Practical Example

Case: HR & Recruiting. A company with 1,000 annual hires automated resume screening. AI analyzes 500 resumes in 10 minutes instead of 3 days manually. Hire quality improved 30% — the algorithm better predicts candidate fit.

Frequently Asked Questions

Q:How does automation help during a crisis?
Reduces operational costs without quality loss. Enables rapid scaling up and down. Remote work without efficiency loss. Automatic risk monitoring and early warning. Companies with automation recover from crises 2-3x faster than those without.
Q:What if automation isn't working?
Check data quality — it's the cause of 60% of problems. Ensure the process is properly documented. Conduct root cause analysis. Ask users about their issues. Often you need refinement, not replacement: rule tuning, model retraining, new system integration.
Q:How to choose an automation vendor?
Look for industry experience — at least 3-5 completed projects. Check reviews and case studies. Ask for a demo on your data. Pay attention to approach: waterfall vs agile. Ensure the vendor will transfer knowledge to your team, not create dependency.

Related terms

Git FlowFeature Flags