CI/CD migration projects look straightforward on paper. Take your existing pipelines, translate them to the new platform’s syntax, run some tests, and switch over. Vendor documentation makes it seem like a weekend project.
The reality is more complicated. Pipeline syntax is the easy part. Everything around it—the implicit knowledge, the integrations, the team dynamics—is where migrations actually succeed or fail.
The Knowledge Problem
Legacy CI systems accumulate tribal knowledge in ways that aren’t obvious until you try to migrate them. That Jenkins job someone created three years ago? It has environment variables that nobody documented, plugins with specific version requirements that break if upgraded, timing dependencies on other jobs that aren’t encoded anywhere, and workarounds for problems that have long since been forgotten.
The person who set it up may have left the organization. The documentation, if it exists, describes what was originally intended rather than what the system evolved into through years of patches and quick fixes. Some jobs have been modified by multiple people over time, each adding their own assumptions without fully understanding the previous state. The only accurate source of truth is the running system itself—and even that doesn’t explain why things work the way they do, only that they do work, most of the time.
Before translating pipelines to a new platform, you need to understand what they actually do. This means talking to the teams who use them, not just reading configuration files. It means watching builds run and observing what actually happens, including the parts that aren’t explicitly configured. It means documenting the implicit assumptions that never got written down because they were obvious at the time to people who are no longer available to explain them. This discovery phase often takes longer than expected and reveals complexity that wasn’t apparent from a surface review.
Integration Dependencies
Build pipelines don’t exist in isolation. They’re nodes in a larger system that connects to artifact repositories, testing infrastructure, deployment targets, notification systems, approval workflows, security scanning tools, and often internal systems that were built specifically to work with the current CI platform.
Migrating the pipeline means migrating—or replacing—all of these integrations. Some will have equivalent features on the new platform that work similarly enough that the transition is straightforward. Some won’t have direct equivalents, requiring you to find alternative approaches or build custom solutions. Some integrations may require rethinking the workflow entirely because the new platform handles certain concepts differently.
The notification system that posts build results to a Slack channel is easy to migrate—most platforms support this natively. The integration with the legacy deployment tool that nobody fully understands, which uses a custom protocol and was built by a contractor who left years ago, is not. The approval workflow that involves sending emails to specific people based on which files changed, with escalation paths and timeout behavior, may not map cleanly to the new platform’s approval model. Each of these integration points needs to be inventoried, understood, and either migrated or replaced—and the full list is often longer than anyone initially expects.
Parallel Running Is Essential
Cutting over completely on day one is high risk for production-critical pipelines. Too many things can break that weren’t anticipated, and when builds fail, development velocity drops to zero while everyone scrambles to diagnose problems they’ve never seen before.
Running old and new systems in parallel takes more effort—you’re maintaining two systems simultaneously, which means double the infrastructure cost and operational attention during the transition period. But it’s the only safe approach for pipelines that matter. Trigger both systems on the same commits. Compare results to verify they match. When discrepancies appear, investigate whether the new system is wrong, the old system was wrong, or the behavior is legitimately different in ways that need to be understood.
This parallel period reveals problems you won’t find in controlled testing. Timing issues that only appear under production load. Edge cases in rarely-exercised code paths that don’t get covered by normal test suites. Assumptions about the build environment—file system layout, network access, available tools—that held on the old platform but don’t hold on the new one. Race conditions that occur only when specific combinations of jobs run simultaneously. The parallel running period catches these problems when the old system is still available as a safety net, rather than discovering them after the cutover when you’re operating without a fallback.
Team Adoption
New CI/CD platforms mean new skills for everyone who interacts with them. Teams need to learn different configuration syntax, different mental models for how pipelines work, different patterns for common tasks, and different debugging approaches when things break. This learning takes time that teams would rather spend on feature work, and the disruption affects productivity during the transition period even when everything goes smoothly.
Migration succeeds when teams see genuine benefit in the new system—faster build times, better debugging tools, easier configuration for common workflows, clearer error messages when things fail. When teams experience these improvements firsthand, they become advocates for the migration rather than reluctant participants. Migration stalls when the new system feels like overhead imposed by someone else, when the benefits are theoretical rather than tangible, or when the new platform makes familiar tasks harder without obvious compensating advantages.
Involving teams early in the migration process helps build buy-in. Let them influence how their pipelines migrate—they know their workflows better than anyone. Address their specific pain points; if the biggest complaint about the old system is slow builds, make sure the new system is demonstrably faster. Show them what improves, not just what changes. When teams feel ownership over the migration rather than being subjected to it, the adoption challenges become much more manageable.
The Visibility Question
One unexpected challenge that often emerges mid-migration: not everyone who interacts with CI/CD information has direct access to the new platform, and they may not need or want that access. Operations teams checking deployment status, QA engineers tracking build progress, release managers coordinating launches, product managers wanting visibility into development velocity—these stakeholders may have relied on dashboards, reports, and tools built specifically on top of the legacy CI system.
Migration might require building new interfaces for these users rather than expecting them to learn the new platform’s native UI. A custom dashboard that surfaces build status, deployment progress, test results, and approval workflows in a format designed for their specific needs can be more valuable than forcing everyone into an interface designed for engineers managing pipelines. This dashboard work is easy to overlook in migration planning because it doesn’t involve the core pipeline functionality, but discovering the need late in the project can add significant scope.
Planning for the Long Tail
Most pipelines migrate relatively smoothly once you understand them. The standard build-test-deploy workflows, the main application pipelines, the jobs that run frequently and are well-understood—these represent the bulk of the work but often proceed without major surprises. Then there’s the long tail: the edge cases, the unusual configurations, the jobs nobody remembers creating but that definitely need to keep running.
Every organization has these long-tail jobs. The monthly report generation that only runs on the third Tuesday. The legacy integration tests that depend on a specific version of a database that can’t be upgraded. The release pipeline for a product that’s in maintenance mode with one release per year. The tool that generates documentation from code comments that was built by someone who left three years ago. Each of these requires individual attention, and collectively they can represent a significant portion of the total migration effort.
Plan for this reality. The bulk of migration—the high-volume, well-understood pipelines—might take weeks to migrate successfully. The long tail takes months, sometimes longer. Budget time accordingly in your planning, and resist the temptation to declare victory before the last pipeline is truly off the old system. Organizations that underestimate the long tail end up maintaining two CI systems indefinitely, which is often worse than completing the migration properly.
What Actually Matters
CI/CD migration is a people and process challenge disguised as a technical project. The syntax translation—converting Jenkinsfile to GitHub Actions YAML or GitLab CI configuration—is genuinely the easy part. Automated tools can help with basic conversion, and the fundamental concepts map across platforms. What determines success or failure lies elsewhere.
Success depends on understanding what actually exists in your current system, not just what’s documented or what people think exists. It depends on maintaining continuity for development teams while the infrastructure changes underneath them, so they can continue shipping software throughout the migration. It depends on bringing teams along as partners in the migration rather than imposing change on them from above. And it depends on planning for the full journey—including the long tail of edge cases—rather than optimistically assuming the migration is nearly complete when the main pipelines are working.
Get these factors right, and the technical migration follows naturally. The pipeline configurations get written, the integrations get built, the testing gets done. Skip these factors—try to treat migration as purely a technical exercise—and even perfect pipeline translations won’t save the project from adoption failure, missed edge cases, and organizational resistance that drags on indefinitely.