From Legacy Scripts to a Unified CI/CD Platform: A Practical Migration Playbook
Migrate from Jenkins, CircleCI, or custom scripts to modern GitLab CI or GitHub Actions without breaking deployments.
Why Migrate CI/CD Platforms?
Many engineering organizations find themselves trapped with legacy CI/CD systems that have become maintenance nightmares. Whether it's Jenkins instances requiring constant plugin updates, custom shell scripts scattered across repositories, or CircleCI configurations that no one dares to touch, the pain is real and growing.
Modern CI/CD platforms like GitLab CI and GitHub Actions offer compelling advantages: native Git integration, declarative pipeline definitions, built-in security scanning, and significantly lower operational overhead. But migration isn't trivial—especially when you're managing 50+ pipelines supporting production deployments.
This playbook documents the successful migration of 200+ Jenkins pipelines to GitLab CI over 12 weeks, with zero production incidents and minimal disruption to development teams. We'll share the strategy, tooling, and lessons learned.
70% Faster Builds
Modern runners and caching strategies significantly reduce build times
Built-in Security
SAST, DAST, and dependency scanning included by default
GitOps-Native
Pipeline configuration lives in Git, versioned and reviewable
Current State Assessment
Before migrating a single pipeline, conduct a thorough assessment of your current CI/CD landscape. Understanding what you have is critical to planning what you need.
Inventory Your Pipelines
Create a comprehensive inventory including:
- Pipeline Count & Complexity
How many pipelines? Simple builds or complex multi-stage deployments?
- Trigger Mechanisms
Git webhooks, scheduled jobs, manual triggers, API calls?
- External Dependencies
Docker registries, artifact repositories, secret managers, notification systems
- Deployment Targets
Kubernetes, EC2, Lambda, on-prem servers
- Custom Scripts & Tools
Groovy scripts, custom plugins, proprietary tooling
Real Example: 200-Pipeline Assessment
Our assessment revealed:
- • 212 total pipelines across 85 repositories
- • 45% simple build-test-deploy (good candidates for Phase 1)
- • 35% complex multi-stage with manual approvals
- • 20% legacy scripts with hard-coded secrets (required refactoring)
- • 12 custom Groovy scripts (needed rewriting)
Target Platform Selection
Choosing between GitLab CI, GitHub Actions, and CircleCI depends on your specific needs. Here's how they compare:
GitLab CI
- Best for: Teams already using GitLab or wanting complete DevOps platform
- Pros: Integrated security scanning, built-in container registry, powerful auto-DevOps features
- Cons: Steeper learning curve for .gitlab-ci.yml syntax, self-hosted runners require maintenance
GitHub Actions
- Best for: GitHub-hosted repositories, rapid prototyping, extensive marketplace
- Pros: Huge action marketplace, simple YAML syntax, tight GitHub integration
- Cons: Limited free minutes for private repos, less enterprise features than GitLab
CircleCI
- Best for: Docker-first workflows, mature performance optimization features
- Pros: Excellent caching, fast execution, good VCS integration
- Cons: Higher cost, less integrated than GitLab/GitHub solutions
Our Choice: GitLab CI
We chose GitLab CI for:
- • Unified platform: source control + CI/CD + security + registry
- • Self-hosted runners: complete control over build environment
- • Cost-effective: unlimited minutes on self-hosted runners
- • Compliance: air-gapped runners for regulated workloads
Migration Strategy: Gradual vs Big Bang
You have two approaches: migrate everything at once (big bang) or gradually migrate pipeline by pipeline. For most organizations, gradual migration is the safer choice.
Big Bang Migration
When to use:
- • Small teams (<10 pipelines)
- • Greenfield projects
- • Mandated deadline
Risks:
- • High chance of production impact
- • Team overwhelm
- • Difficult rollback
Gradual Migration (Recommended)
When to use:
- • Large pipeline inventory (50+)
- • Production-critical systems
- • Learning curve needed
Benefits:
- • Learn and improve iteratively
- • Easy rollback per pipeline
- • Team ramps up gradually
Recommended: 3-Phase Approach
- Phase 1: Proof of Concept (Weeks 1-3)
Migrate 3-5 low-risk pipelines to validate approach and tooling
- Phase 2: Parallel Running (Weeks 4-8)
Run new and old pipelines side-by-side, migrate 50% of pipelines
- Phase 3: Full Cutover (Weeks 9-12)
Complete migration, decommission legacy system
Phase 1: Proof of Concept (3-5 Pipelines)
Start with low-risk pipelines to validate your migration approach, tooling, and team readiness. Choose pipelines that represent different patterns you'll encounter.
Select Your POC Pipelines
Choose pipelines that cover different scenarios:
- Simple Build-Test Pipeline
Basic CI workflow to validate core functionality
- Docker Build & Push
Test container registry integration
- Deploy to Staging
Validate deployment automation and secrets management
Example: Jenkins to GitLab CI Migration
Before: Jenkinsfile
pipeline {
agent any
stages {
stage('Build') {
steps {
sh 'npm install'
sh 'npm run build'
}
}
stage('Test') {
steps {
sh 'npm test'
}
}
stage('Deploy') {
when { branch 'main' }
steps {
sh './deploy.sh production'
}
}
}
}After: .gitlab-ci.yml
stages:
- build
- test
- deploy
variables:
NODE_VERSION: "18"
build:
stage: build
image: node:${NODE_VERSION}
script:
- npm ci
- npm run build
artifacts:
paths:
- dist/
expire_in: 1 hour
cache:
paths:
- node_modules/
test:
stage: test
image: node:${NODE_VERSION}
script:
- npm ci
- npm test
coverage: '/All files[^|]*\|[^|]*\s+([\d\.]+)/'
deploy:
stage: deploy
image: alpine:latest
script:
- apk add --no-cache bash
- ./deploy.sh production
only:
- main
environment:
name: production
url: https://app.example.com
when: manualKey Improvements in GitLab CI Version
- • Explicit caching of node_modules (faster subsequent runs)
- • Artifact preservation between stages
- • Built-in coverage parsing
- • Environment tracking for deployments
- • Manual approval gate for production
Phase 2: Parallel Running
Run both old and new pipelines simultaneously to build confidence before fully committing. This gives you an escape hatch if issues arise.
Implementation Strategy
- Dual Webhook Configuration
Configure Git webhooks to trigger both Jenkins and GitLab CI
- Compare Outputs
Validate that both systems produce identical artifacts
- Monitor Metrics
Track build times, success rates, and reliability
- Team Training
Developers get hands-on experience with new system
Cost Consideration
Running parallel pipelines temporarily doubles your CI/CD costs. Budget for this during the transition period:
- • Estimated duration: 4-6 weeks
- • Additional cost: ~$2,000-5,000 depending on scale
- • Worth it: Eliminates risk of production breakage
Phase 3: Full Cutover
With confidence built from parallel running, switch fully to the new platform and decommission the legacy system.
Cutover Checklist
- Verify All Pipelines Migrated
100% of production pipelines must be operational
- Update Documentation
Developer guides, runbooks, incident response procedures
- Disable Old Webhooks
Prevent accidental triggers of legacy system
- Archive Legacy Configuration
Keep backups for 90 days before deletion
- Decommission Infrastructure
Shut down old Jenkins servers, reduce costs
0
Production Incidents
Zero downtime during entire migration
70%
Faster Builds
Average build time reduction
$3.2K
Monthly Savings
Reduced infrastructure and maintenance
Lessons Learned & Common Pitfalls
After completing 200+ pipeline migrations, here are the key lessons we learned:
What Worked Well
- Start with Simple Pipelines
Building confidence early accelerated later phases
- Automated Conversion Tools
Custom scripts converted 60% of basic Jenkins pipelines automatically
- Team Champions
Designated GitLab experts in each team smoothed adoption
- Comprehensive Logging
Detailed migration logs helped troubleshoot issues quickly
Common Pitfalls to Avoid
- Underestimating Secrets Migration
Secret rotation took 2x longer than expected—plan accordingly
- Ignoring Custom Scripts
Legacy Groovy scripts required complete rewrites, not simple ports
- Insufficient Runner Capacity
Provision 30% more runner capacity than calculated—queue times matter
- Poor Communication
Weekly migration updates kept stakeholders informed and reduced anxiety
Final Recommendations
- • Allocate 20% buffer time for unexpected issues
- • Invest in automated testing for pipeline configurations
- • Document everything—future you will thank present you
- • Celebrate milestones to maintain team morale
- • Keep legacy system running for 30 days post-migration
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