Thanks for sharing your thoughts Jens. > be able to test it? … a Q&A/Testing environment to be able to sign-off changes. Yes, we’ve have built an isolated airflow environment to run regression checks before promoting to production.
As you suggested, we’re already running both generic and DAG-custom static checks in a CI job as a required step to merge to the main branch. > But then the "main" branch might be best suited if implemented on the test system In this case, problematic commits on “main” can choke other unrelated changes. So the other option would be to revert the problematic commits and deploy forward. However, a key limitation with this approach that remains is that a commit affecting multiple DAGs goes live for either all DAGs or none. Second important feature we get with this is instant DAG-level rollback without waiting for a revert commit to merge and be picked by airflow. I think DAG-level version pinning can also unlock a lot of flexibility for deployments including tiered rollouts, auto-rollback triggers, timed deployment windows and so on. Looking forward to hear your thoughts. Regards, Piyush On Sun, 19 Apr 2026 at 3:12 PM, Jens Scheffler <[email protected]> wrote: > Thanks Piyush for dropping the discussion! > > I think in general QA processes are important and a valid use case. So a > kind of pinning Dag versions really is important. > > Thinking about it, if you pin the version ... how would you then be able > to test it? I assume you would need (and should have or invest into) a > Q&A/Testing environment to be able to sign-off changes. Both in > infrastructure but also for Dag changes. > > If you are changing Dags first of all static checks on Dag code are very > much proposed as well as you can have tests implemented and test your > Dags and logic. Similar like software a CI/CD system will be a good > setup. Alongside Dag changes also have logical changes that mostly can > only be tested in a live system and not as static checks. > > Have you considered using Git and a set of branches for implementing > such staging? E.g. you have a git repo and you plan to make changes. > Then you would open a PR for the change and merge it to the "main" > branch - and there in your CI/CD you can check all sorts of static > checks and tests. But then the "main" branch might be best suited if > implemented on the test system. Once you validate the changes end-to-end > you could make another PR for example to a "prod" branch. And if your > production system is only pulling Dags from the "prod" branch then you > can have this merging strategy as a staging setup. > > Would this resolve your PING problem? Or which other detail in the use > case would require a PIN on top of a staging strategy? > > Jens > > P.S.: Have enabled your confluence account after it was created in order > to write to Confluence, sorry, typical pitfall after account creation > permissions were not set. Now it should work. Let me know if not. > > On 19.04.26 01:40, Piyush Maheshwari wrote: > > Hi everyone, > > I'm a new contributor to Airflow. I'd like to propose a new feature for > Airflow: DAG Version Pinning. > > Building on the foundation introduced by AIP-63: DAG Versioning ( > https://cwiki.apache.org/confluence/display/AIRFLOW/AIP-63%3A+DAG+Versioning), > this proposal aims to extend Airflow's capabilities to support true > continuous deployment (CD) gating and safer release cycles. > > The Problem & Use Cases > > Currently, the scheduler always creates DagRuns using the latest parsed > DagVersion. This means that the updated DAG code is deployed (takes effect) > right after the dag-processor processes it. While this is great for rapid > development, teams running business-critical pipelines often need stricter > deployment mechanisms. Specifically: > > > > * > > Safe Deployment Gating: The ability to pin a DAG to its last known > stable version while new code is parsed in the background. This allows the > new version to be held back until it passes automated regression tests or > receives explicit manual approval. > > * > > Instant Rollbacks: If an issue is detected in a newly promoted DAG > version, users need the capability to instantly roll back to a previous > version via the UI/API, without having to revert the underlying code and > wait for the repository sync and DAG processing cycle. > > > > High-Level Proposed Solution > > Introduce an optional active_dag_version_id to the DagModel. This field > can be used to pin a DAG version for scheduling and execution, while the > dag-processor can continue to parse and register newer DAG versions. > > > > * > > When this pin is set, the scheduler and API will respect the pinned > version for creating runs and executing tasks, separating the parsing of > new code from the execution of new code. > > * > > If the pin is NULL, the system defaults to the current behavior (always > executing the latest parsed version). This way, we can maintain complete > backwards compatibility. > > > > I have put together some detailed notes covering the data model changes, > database migrations, and edge cases with this approach. If there is general > alignment that this fits the vision for Airflow, I would like to take this > proposal through the formal AIP review process. > > But I would love to get the community's feedback on the feature and the > high-level approach. > > I'll also need someone to grant me access to create content on the > Airflow Confluence wiki. > > > > Thanks for your time! > > Regards, > > Piyush > > > > --------------------------------------------------------------------- > To unsubscribe, e-mail: [email protected] > For additional commands, e-mail: [email protected] > >
