We’re running Camunda for some critical processes and it’s working, but the licensing model is starting to hurt the budget. Open-source alternatives like Flowable or Activiti look appealing on paper, but I’m honestly terrified of how we migrate without disrupting everything in the middle.
The challenge isn’t just about rewriting workflows—it’s about understanding where the risks are. Camunda has been handling our order processing and approval chains for two years now. If we rush the migration, we could break something that nobody notices until it costs us real money.
I’m wondering how other teams approached this:
- How did you actually build a prototype in a parallel environment without replicating the entire data model?
- What happens to in-flight processes during the cutover? Do you pause everything, or is there a way to migrate them mid-execution?
- How much of your Camunda BPMN files actually translated directly to your open-source platform, and what required rework?
- Did you find templates or patterns that made certain process types easier to migrate?
I know this is technical, but I’m also trying to figure out the business case. If we can prototype safely and show that we can hit our timelines and risk targets, finance will approve the budget. Are there ways to de-risk this that don’t require a full team lock-in for months?
We migrated from Camunda to Flowable three years ago, so this is fresh enough in my head that I remember the pain points.
The biggest insight: don’t try to migrate everything at once. We picked one isolated workflow first—something that was working well but wasn’t mission-critical. This let us understand the translation layer without betting the company on it.
Camunda’s BPMN 2.0 implementation is pretty solid, but Flowable has quirks. Service tasks behave slightly differently, boundary events have different timing semantics, and error handling feels less polished. We discovered this by actually running both in parallel for a month and comparing outputs.
For in-flight processes, we basically created a migration window. We had to pause new instances for about 4 hours while we migrated the active ones. It sounds worse than it feels—we just exported Camunda’s instance state and re-hydrated it in Flowable. The real trick was making sure our error handlers knew what to do if something went wrong mid-migration.
Templates helped a lot. For processes that were just sequential steps with approvals, migration time was maybe 20% of the engineering effort. For anything with complex gateway logic or compensation handling, it jumped to 80%+ rework.
Honestly, what would’ve made this 50% faster is if we’d had a tool that understood both BPMN formats and could at least flag the incompatibilities upfront. We did a lot of trial-and-error.
The reason migration feels so risky is that you’re betting on things working exactly the same way, and modern process engines have enough subtle differences that this assumption breaks.
When we approached this, we decided to treat it like any other major infrastructure change: we built a parallel environment, we ran sample workflows through both systems simultaneously, and we monitored for behavioral differences. What we found was that about 15% of our workflows had subtle timing or error-handling issues that only showed up under specific conditions.
For in-flight processes, you have options. The cleanest approach is to create a transition period where old instances finish in Camunda and new ones start in the open-source system. This stretches your cutover but reduces risk dramatically. We did this over two weeks rather than trying to force all instances over at once.
The template question matters because reusable workflow patterns let you batch similar migrations. We identified maybe 8 core patterns used across 60+ workflows. Once we got one pattern working perfectly, replicating it to similar processes was straightforward.
Prototyping safely means treating your target platform like an unknown. Don’t assume BPMN 2.0 compliance means perfect compatibility—test everything.
The most successful migrations I’ve seen follow this pattern: first, extract one simple workflow and rebuild it in the target platform. Second, run both simultaneously for a reporting period to verify outcomes match. Third, gradually shift traffic while keeping Camunda as a fallback. Only after you’ve proven pattern compatibility do you risk moving complex processes.
In-flight processes are the hard problem. The technically sound approach is asynchronous migration—you run both systems in parallel, with a bridge layer that translates state between them. It’s more complex than it sounds, but it lets you migrate on your timeline rather than forcing a big-bang cutover.
start with one simple workflow. run both camunda + target platform in parallel. monitor for 2 weeks. check compatibility. in-flight processes pause during cutover window. expect 20-50% rework depending on complexity.
Build in parallel environment first. Test BPMN compatibility on isolated workflow. Create gradual cutover plan to minimize downtime risk.
We actually went through something similar when we wanted to move away from a rigid, expensive BPM setup. The key realization was that you don’t have to choose between complexity and speed.
What made prototyping easier for us was using a platform that could handle BPMN workflows but also gave us flexibility to represent processes differently if needed. Instead of being locked into BPMN semantics, we could model the same process in multiple ways and pick the cleanest representation for the target platform.
For in-flight processes, we set up a validation layer that let new instances run in the target system while old ones finished in the legacy system. This gave us a real cutover window instead of forcing an all-or-nothing moment. We tested this with sample data first, then ran it live with a small percentage of traffic.
The piece that saved us the most time was having access to pattern libraries—pre-built approval flows, escalation chains, and error handlers. We didn’t start from zero; we adapted proven patterns and modified them for our specific use cases.
If you’re evaluating options for this kind of migration, Latenode gives you both the flexibility to model workflows however makes sense and the automation tooling to bridge systems during transition: https://latenode.com