> The idea to put all the closing into KPO would mean this is then only a solution in KPO cases, all other tasks related to Triggerer re-scheduling would still suffer from the same problem. So it would be a point solution.
All other cases do not suffer from resources taken by the KPO pod. I think the case you described is **really** KPO bound and the real problem is not that "next" method has lower priority. I believe that executing higher-priority tasks before lower-priority "next" tasks, after the trigger completes, is exactly how Airflow is designed. In this case I think the problem is that we are using the "next" deferrable method in KPOTrigger to do something that was **never** supposed to run as "next." A side effect is that the "pod" must be kept for much longer than necessary just to extract the Xcom. That, to be honest, makes very little sense; it seems like using a screwdriver to put in nails instead of a hammer. If the "next" method is only supposed to retrieve the XCom and save it to the database, there is absolutely no reason to have a scheduled task for it—this is, in my humble opinion (IMHO), the biggest problem to solve. Do you think there is a good reason to use the sidecar volume to store XCom data in this case, rather than Airflow's regular storage for XCom? For me that looks like a bad idea where we essntially uise Pod's side-car to store a value in some kind of intermediate storage, while there is nothing to prevent us to store it in the actual "target" storage. > But I think this is also one of the shortcomings that @dabla mentioned multiple times when he was starting to contribute the Async Iterator - I see no API endpoint in triggerer code (see e.g. providers/cncf/kubernetes/src/airflow/providers/cncf/kubernetes/triggers/pod.py) where the current API has an option to get a DB, supervisor or XCom context. Maybe I am blind not seeing this but I fear this is just missing and would be a larger enablement in the core for Triggerer to have such functions that in regular tasks executed by SDK have as context. Also there is no `context` object which providers this... but happy if you can enlighten me where and how code in Triggerer would be able to write an XCom if today available. We can add it if it's missing; that's not an issue. It's far less a disruptive chance than triggering communication with other components. This is a code change rather than an architectural change, which is always easier for Airflow users to implement (you just upgrade the Airflow version - no other changes in deployment are needed. > In our case it is also a bit more complex - but would be fair to tell it is then a Bosch only problem - we have inherited a custom operator on top of KPO to cover specific error triaging which e.g. marks task failed w/o retry if we see there is a deterministic error (like ImagePullBackOff - we know is not there we do not want to retry - or also for cases where our workload fails in problems we know are deterministic and a retry would be just waste of time and resources like an assert in the application we are testing). If all that logic is moved to triggerer it will in-deed be a bit harder as you know deploying changes to triggerer is less flexible than some operator code in Dag source tree. But we can also make this... with more time invested. But XCom need to be resolved. Yes, I understand that - but IMHO this is building on a flaw in the current implementation (which was never intended to be extended). And in this case as I understand it, that would involve adding the same functionality to KPOTrigger, not KPO itself. Yes. Breaking chance for you, but I think overall a better future for Airflow maintainability. With this change, I think the optimisation is even better than patching the behavior of the current KPO. And if needs be - we can even add some "extension points" and the ability to use a custom KPOTrigger rather than a custom KPO. I don't think this is a major change (even if it is somewhat more complex for some users - like Bosch). However, with this you can get even better performance than with the "hack" using an executor because you will entirely skip re-entry and the need to start a new pod **just** to pull the XCom and save it in the database. That sounds like an overall win-win. That might be a major change (breaking, requiring a significant info/changelog for KPO) - reqiuiring new version of Airflow to provide the API that is possibly missing in 3.1.0 - but IMHO absolutlely worth doing - coul be also nicely conditioned by version of Airflow cncf.Kubernetes is installed on. I thinnk while slightly more complex for Bosh to pull-off, it might be better for Airflow as a product. J. On Sat, Mar 21, 2026 at 10:49 PM Jens Scheffler <[email protected]> wrote: > Hi Jarek, et al. > > You are not missing any obvious and I understand the rationale of > coupling is what your concern is. > > So your counter proposal would get back to the point I had in my list of > alternatives with the name "Finish-up the work on triggerer w/o return > to Worker". That had the ending with "Main blocker in this view is XCom > access." > > The idea to put all the closing into KPO would mean this is then only a > solution in KPO cases, all other tasks related to Triggerer > re-scheduling would still suffer from the same problem. So it would be a > point solution. > > But I think this is also one of the shortcomings that @dabla mentioned > multiple times when he was starting to contribute the Async Iterator - I > see no API endpoint in triggerer code (see e.g. > providers/cncf/kubernetes/src/airflow/providers/cncf/kubernetes/triggers/pod.py) > > where the current API has an option to get a DB, supervisor or XCom > context. Maybe I am blind not seeing this but I fear this is just > missing and would be a larger enablement in the core for Triggerer to > have such functions that in regular tasks executed by SDK have as > context. Also there is no `context` object which providers this... but > happy if you can enlighten me where and how code in Triggerer would be > able to write an XCom if today available. > > In our case it is also a bit more complex - but would be fair to tell it > is then a Bosch only problem - we have inherited a custom operator on > top of KPO to cover specific error triaging which e.g. marks task failed > w/o retry if we see there is a deterministic error (like > ImagePullBackOff - we know is not there we do not want to retry - or > also for cases where our workload fails in problems we know are > deterministic and a retry would be just waste of time and resources like > an assert in the application we are testing). If all that logic is moved > to triggerer it will in-deed be a bit harder as you know deploying > changes to triggerer is less flexible than some operator code in Dag > source tree. But we can also make this... with more time invested. But > XCom need to be resolved. > > Jens > > On 21.03.26 15:56, Jarek Potiuk wrote: > > It took me a bit time - I wanted to go a bit deeper and look closer aht e > > > > I also share a bit of Niko's concerns. Running executor code from the > > Triggerer significantly changes the architectural approach and > boundaries. > > And yeah - it's not really tied to multi-team, it's a general issue (in > > multi-team triggerer is per team, so you can be sure that "what is in > team, > > stays in team"). > > > > But it does change which system components communicate with each other. > For > > example, the Triggerer needs access to the Celery queue for Celery > > Executor, which is otherwise unnecessary. Similarly, the Triggerer will > > need access to start Pods if the K8S executor is used. I'm not even sure > > what would happen with the Edge executor. From what I understand, the > Edge > > Executor actively loops and checks for tasks, purges jobs etc. It pulls > > data from the database so I can imagine it simply enqueues the workload > and > > then the "real" Edge executor takes over (I believe that will be the > case). > > However, this significantly crosses the current boundaries of which > > component does what. > > > > Not mentioning the secutity implication - the JWT token generator in your > > solution works on triggerer, and that's pretty much breaks the (future) > > assumption that Triggerer does not need to know the secret necessary to > > generate the token - and has a lot implications (for multi-team for > example > > - but not only) - generally a lot of the future task isolation work is > > based that the user code has no chances to see the secret to generate the > > tokens. > > > > While I think this is a good temporary solution for you, I understand the > > use case and its merit; it's not a niche one. Pretty much anyone with KPO > > and lots of deferred tasks will have this case. But I've been thinking > > outside of the box actually. I am not sure if I'm right, but this seems > to > > *really* be a problem with how KPO's Xcom passing is done via the sidecar > > for this Triggerer -> next() handover. But it does not have to be this > way. > > > > Conceptually, I see absolutely no problem saving the XCom where it > belongs: > > either the DB or XCom Backend. This operation is almost exclusively > > I/O-bound, so it can easily be done asynchronously. It could be done in > > KPOTrigger via the supervising process (which has DB access) instead of > > passing things back for scheduling. If KPOTriggerer sees that the Pod is > > completed it could simply ask the supervisor to perform all the tasks > > currently done in KPO's `trigger_reentry`. And that it would not even > cause > > any re-entry, KPOTriggerer could wait for the supervisor to perform the > > action and write to the XCom database or XCom backend, and would simply > > "complete" the task. Triggerer could even have a separate event loop for > > such "finalization," and all of it could be done asynchronously to scale > > things. > > > > There would be no "reentry" workload to run at all, because all > completion > > could happen in the Triggerer. And I think the Triggerer, similar to the > > worker, can communicate with all components. It has access to the DB > > (through triggerer supervisor process) and can also communicate with the > > XCom backend (you should be able to perform XCom Push from the Triggerer > > supervisor (not necessarily from the event loop process). Aside probably > > much more notwork traffic for the Triggerer to save/retrieve XComs from > > multiple deferred KPOs. I can't see any problem with it ( and it can be > > nicely scaled out by adding more triggerers) > > > > Or am I missing something obvious ? > > > > J. > > > > > > On Sat, Mar 21, 2026 at 12:17 PM Jens Scheffler <[email protected]> > wrote: > > > >> Hey Niko, > >> > >> thanks as well for the response with reasoning. I understand that you do > >> not prefer a coupling for a +0. > >> > >> Is there any other option (hint: some where listed "Options we > >> considered") that you would propose as better solution? Or is the +0 > >> just the "least of worse"? > >> > >> Jens > >> > >> On 20.03.26 02:03, Oliveira, Niko wrote: > >>> Hey Jens et al., > >>> > >>> That is three datapoints now so there is indeed some demand. Not sure > if > >> that pushes it over the limit of needing this, but it's more compelling > now. > >>> To your 2) in your last reply Jens: My concern wasn't Multi-Team > >> specifically or anything to do with config. More just that this changes > the > >> (mostly unwritten) contract that the scheduler wholly owns and interacts > >> with executors. Up until this change one could depend on this being true > >> and that there is only ever one instance of any executor (per team now, > >> since two teams can have the same executor between them). But now your > >> changes are instantiating executors and queuing work with them. So all > >> future executor/scheduling changes need to keep this in mind. It simply > >> increases the surface area of execution/scheduling in Airflow and we now > >> have a multi-writer situation which always brings extra complexity. If > >> there is enough demand then we should do it. Seems to be a few > requesters > >> now, which I think brings me to a +0 on this one. > >>> Thanks again for the discussion! > >>> > >>> ________________________________ > >>> From: André Ahlert<[email protected]> > >>> Sent: Thursday, March 19, 2026 1:15 PM > >>> To:[email protected] <[email protected]> > >>> Subject: RE: [EXT] [DISCUSS] PR: Option to directly submit to worker > >> queue from Triggerer > >>> CAUTION: This email originated from outside of the organization. Do not > >> click links or open attachments unless you can confirm the sender and > know > >> the content is safe. > >>> > >>> > >>> AVERTISSEMENT: Ce courrier électronique provient d’un expéditeur > >> externe. Ne cliquez sur aucun lien et n’ouvrez aucune pièce jointe si > vous > >> ne pouvez pas confirmer l’identité de l’expéditeur et si vous n’êtes pas > >> certain que le contenu ne présente aucun risque. > >>> > >>> > >>> Hi all, > >>> > >>> This discussion resonates with problems we've seen on a fintech > client's > >>> setup. Heavy KPO usage in deferred mode, Celery executor, pools with > >>> include_deferred=True. When a batch of tasks finishes on the cluster > and > >>> flips back to SCHEDULED, the pool slots are released and tasks have to > >>> recompete through the scheduler for what amounts to seconds of cleanup > >>> work. In our case the cloud cost was not the main concern, but it > raised > >> a > >>> real architectural question: why does a task that already passed all > >>> concurrency checks need to go through the entire scheduling loop again > >> just > >>> to collect XCom and delete a pod? > >>> > >>> On the architectural concerns, I think the mini-scheduler comparison > from > >>> Airflow 2 does not hold. That feature made full scheduling decisions > >>> (concurrency, pools, priority). This PR makes none. It re-enqueues a > task > >>> that allready satisfied all those checks. The task already had a slot, > >>> already was running. We are just sending it back to finish. > >>> > >>> Fact that it is opt-in with a safe fallback to SCHEDULED makes this > very > >>> low risk. If nobody configures direct_queueing_executors, behavior is > >>> identical to today. Marking it experimental for a release or two would > >> also > >>> be fine. > >>> > >>> On the use case being narrow: any deployment using deferred mode with > >>> Celery at scale will eventually hit this. Issue #57210 shows > independent > >>> reports of the same pattern. It is inherent to the DEFERRED -> > SCHEDULED > >> -> > >>> QUEUED state machine under pool contention, not specific to one setup. > >>> > >>> +1 (non-binding) on getting this into main. > >>> > >>> Thanks Jens for bringing this one. > >>> > >>> André Ahlert > >>> > >>> Em qui., 19 de mar. de 2026 às 14:24, Jens Scheffler< > [email protected] > >>> > >>> escreveu: > >>> > >>>> Hi Niko, > >>>> > >>>> thanks for the feedback. > >>>> > >>>> (1) I think the use case is not really narrow, @tirkarthi also pointed > >>>> to issuehttps://github.com/apache/airflow/issues/57210 - So this > would > >>>> be closed as well > >>>> > >>>> (2) I aimed to include support for Multi-Team (that was even adding > some > >>>> complexity compared to the local patch in 3.1.7. Yes so the config > >>>> property is atm global such that if you set it enabled for > >>>> CeleryExecutor it would be for all Executors in all teams. But if you > >>>> wish and see a reason we can also model the config being team specific > >>>> (e.g. only team_a uses CeleryExecutor and team_b does not optimize - > >>>> though not sure if there is a need to separate). Routing and queueing > >>>> for sure is respectinv the correct Executor/queue instance to route to > >>>> in the PR. > >>>> See > >>>> > >>>> > >> > https://github.com/apache/airflow/pull/63489/changes#diff-c30603fe0a3527e23af541ba115c91c85c9c213e6d105af6a48c88a7018a5799R333 > >>>> and > >>>> > >>>> > >> > https://github.com/apache/airflow/pull/63489/changes#diff-c30603fe0a3527e23af541ba115c91c85c9c213e6d105af6a48c88a7018a5799R347 > >>>> Jens > >>>> > >>>> On 18.03.26 23:34, Oliveira, Niko wrote: > >>>>> Thanks for the write-up Jens, it helps to have the full context of > your > >>>> thought process. > >>>>> The code changes themselves are small and fairly elegant. But this > >>>> breaks the invariant that there is only ever one instance of each > >> executor > >>>> (per team) and that they live in the scheduler process and the > >> scheduler is > >>>> the only thing that interacts with them in a scheduling capacity. To > me > >>>> it's quite a large logical change in Airflow behaviour/operation. When > >>>> reasoning about execution and scheduling there is now another source > >> that > >>>> will always need to be considered, ensuring it works and is tested > when > >>>> executor related changes are made, etc. This has been fraught for us > in > >> the > >>>> past in ways that were hard to predict beforehand. > >>>>> The usecase seems quite narrow and focused on how you folks use > >> Airflow. > >>>> Are you hearing from any other users who are asking for something like > >>>> this? I'm just not sure I see enough evidence that it truly belongs in > >>>> apache/airflow main. > >>>>> Cheers, > >>>>> Niko > >>>>> > >>>>> ________________________________ > >>>>> From: Jens Scheffler<[email protected]> > >>>>> Sent: Wednesday, March 18, 2026 2:56 PM > >>>>> To:[email protected] <[email protected]> > >>>>> Subject: [EXT] [DISCUSS] PR: Option to directly submit to worker > queue > >>>> from Triggerer > >>>>> CAUTION: This email originated from outside of the organization. Do > not > >>>> click links or open attachments unless you can confirm the sender and > >> know > >>>> the content is safe. > >>>>> > >>>>> AVERTISSEMENT: Ce courrier électronique provient d’un expéditeur > >>>> externe. Ne cliquez sur aucun lien et n’ouvrez aucune pièce jointe si > >> vous > >>>> ne pouvez pas confirmer l’identité de l’expéditeur et si vous n’êtes > pas > >>>> certain que le contenu ne présente aucun risque. > >>>>> > >>>>> Dear Airflow Devs! > >>>>> > >>>>> TLDR: Because of operational problems in processing workload we > propose > >>>>> an extension allowing to directly re-queue tasks from triggerer. The > PR > >>>>> raised demand to discuss to ensure awareness for the change is > >> available. > >>>>> Pull Request: Allow direct queueing from triggerer > >>>>> <https://github.com/apache/airflow/pull/63489#top> #63489 > >>>>> https://github.com/apache/airflow/pull/63489 > >>>>> > >>>>> The Use Case/Problem Statement: > >>>>> > >>>>> We use Airflow for many workflows of scaled long and large Dags in > >>>>> running 80% KPO workload. To ensure KPO can run scaled and long w/o > >>>>> operation interruptions (worker restart due to re-deployment, Pods > with > >>>>> workload sometimes running 4-10h) and to be able to scale to > thousands > >>>>> of running KPO Pods we need to use and leverage deferred mode > >>>> excessively. > >>>>> In KPO with deferred a task is first scheduled to a (Celery in our > >> case) > >>>>> worker which prepares the Pod manifest and starts the Pod. From there > >> it > >>>>> hands-over to triggerer which monitors the Pod running and tails the > >> log > >>>>> so that a user can watch progress. Once the Pod is completed it > returns > >>>>> back to a (Celery) worker that finishes-up work, extracts XCom, makes > >>>>> error handling and cleans-up the Pod from K8s. This also means that > the > >>>>> Pod is only finished when the XCom is pulled from side-car, the > "base" > >>>>> container might be completed and the Pod is only done and deleted > when > >>>>> the XCom is collected. Until KPO collects XCom the Pod keeps running. > >>>>> > >>>>> The current method of scheduling in Airflow is that the Scheduler > >> checks > >>>>> all rules of concurrency (max_active_tasks, max_tis_per_dagrun, > >>>>> pools...) in state scheduled before a task is queued to be started. > On > >>>>> the worker when started it is directly set to "deferred" and then a > >>>>> triggerer picks-up (no re-scheduling or active distribution to a > >>>>> triggerer). On the way back today triggerer marks the task > "scheduled" > >>>>> which means the scheduler logic needs to pick-up the task again for > >>>>> competition. With all other workload. And re-schedule with all > >>>>> concurrency and priority checks like initially to get to queued to be > >>>>> re-assigned to a (Celery) worker. This implicitly means leaving the > >>>>> state of "deferred" to "scheduled" the task loses the allocated pool > >>>>> slot and also need to re-allocate this. > >>>>> > >>>>> It most regular situations this is okay. In our scenario it is a > >>>>> problem: We have many Dags competing for the K8s cluster resources > and > >>>>> the concurrency features of Airflow joined with priority controls > >> should > >>>>> ensure that important workload runs first. Once there is residual > >>>>> capacity less important batches can consume cluster resources. And > with > >>>>> "consume resources" also refers to Pods sitting on the cluster. They > >>>>> free up the cluster space only at point of XCom collected and Pod > >>>>> removed. Before they still consume CPU and ephemeral storage > >>>>> allocations. We limit the amount of workload being able to be sent to > >>>>> K8s by Airflow pools which are the ultimate limit for concurrency on > >>>>> different node pools (e.g. nodes with GPU and nodes w/o GPU). Other > >>>>> workload often runs on Edge workers or directly as Python in Celery. > >>>>> > >>>>> With multiple Dags and different priorities we had these two effects: > >>>>> > >>>>> (1) A lower priority batch is running ~N*100 Pods in deferred. A > higher > >>>>> priority large batch is started. Pods finishing from the lower > priority > >>>>> tasks are assumed to drain the cluster, when they end the task > >> instances > >>>>> are set to "scheduled" and... then stay there until all tasks of the > >>>>> higher priority tasks are worked off (assuming the higher priority > >> tasks > >>>>> are not limited leaving room for the lower priority tasks). So base > >>>>> container of the Pods are completed, the XCom side car waits long - > we > >>>>> have seen even 24h - to be XCom collected to be cleaned. > >>>>> > >>>>> (a) Additional side effect if pending long the AutoScaler > might > >>>>> pick such a node as scaling victim because really idle and after > grace > >>>>> period kills the Pod - Later when the workload returns to worker the > >> Pod > >>>>> is showing a HTTP 404 as being gone, XCom is lost... in most cases > need > >>>>> to run a retry, else it is anyway a delay and additional hours of > >>>>> re-execution. If no retry just raising failures to users. > >>>>> > >>>>> (b) We had the side effect that newer high priority workload > was > >>>>> not scheduled by K8s to the (almost idle) Nodes because the previous > >>>>> pending Pods allocated still ephemeral storage and not sufficient > space > >>>>> was on K8s nodes for new workload... so the old Pods blocked the new > >> and > >>>>> the higher priority task instances blocked the cleanup of the lower > >> prio > >>>>> instances. A lot of tasks were in a kind of dead-lock. > >>>>> > >>>>> (c) As the re-set to state "scheduled" from triggerer also > sets > >> the > >>>>> "scheduled" date of the task instance also the from the same "low > >>>>> priority" Dag other pending scheduled task instances are often > started > >>>>> earlier. So workers pick-up new tasks to start new Pods but a lot of > >> old > >>>>> Pods are sitting there idle waiting to collect XCom to clean-up > >>>>> > >>>>> (2) Also sometimes because of operational urgency we use the > >>>>> "enable/disable" scheduling flag on Dags in the UI to > administratively > >>>>> turn-off Dag scheduling to leave space for other Dags... or to drain > >> the > >>>>> cluster for some operational procedures e.g. to have a safe ground > >>>>> before maintenance. But as the Dag needs to be actively scheduled to > >>>>> process the return from triggerer. If you turn off scheduling the > >>>>> workload in flight is never finishing and is getting stuck like > >>>>> described before. Pods are stale on the cluster, nobody picks-up the > >>>>> XCom. And the problematic scenario is also there is no way to "clean > >> up" > >>>>> such tasks to finish these Dags w/o turning on scheduling... but then > >>>>> also new tasks are queued and you are just not able to drain the > >>>>> cluster. I know we discussed multiple times that we might need a > >> "drain" > >>>>> mode to let existing Dags finish but not scheduling new Dag runs... > but > >>>>> such feature is also missing. To say: Scheduling new tasks is tightly > >>>>> coupled with the scheduling of cleanup. Not possible to separate. > >>>>> Getting to the problems as 1 (a-c) as well in the scenario (2). > >>>>> > >>>>> We thought a while about which options we would have to contribute to > >>>>> improve in general. Assumption and condition is that the initial > start > >>>>> on the (Celery) Worker is fast, most time is spent (once) on the > >>>>> triggerer and the return to worker is actually only made for a few > >>>>> seconds to clean-up. And of course we want to minimize latency to (I) > >>>>> free the allocated resources and (II) not to have any additional > >>>>> artificial delay for the user. Which a bit contradicts with the > efforts > >>>>> to flip from worker to triggerer and back again. > >>>>> > >>>>> Options we considered: > >>>>> > >>>>> * Proposing a new "state" for a task instance, e.g. > "re-schedule" > >> that > >>>>> is handled with priority by scheduler. > >>>>> But the scheduler is already a big beast of complexity, adding > >>>>> another loop to handle re-scheduled with all existing > complexity > >>>>> might be a large complexity to be added and adding another > state > >> in > >>>>> the state model also adds a lot of overhead from > documentation to > >>>> UI... > >>>>> * Finish-up the work on triggerer w/o return to Worker. It is > only > >>>>> about cleaning the KPO and... > >>>>> Unfortunately more than just monitoring is very complex to > >> implement > >>>>> and especially XCom DB access is not a desired concept and > >> triggerer > >>>>> does not have support. We also have some specific triaging and > >> error > >>>>> handling automation extended on top of KPO which all in async > >> with > >>>>> the limited capabilities of triggerer would be hard to > implement. > >>>>> Main blocker in this view is XCom access. > >>>>> * Dynamically increase priority of a task returning from > triggerer. > >>>>> We considered "patching" the priority_weight value of the task > >>>>> instance on the triggerer before return to ensure that tasks > >>>>> returning are just elevated in priority. First we made this > from > >> the > >>>>> side via SQL (UPDATE task_instance SET priority_weight=1000 > WHERE > >>>>> state='scheduled' AND next_method='trigger_reentry') but > >> actually if > >>>>> the task failed and restarted then it is hard to find and > reset > >> the > >>>>> priority back... still a retry would need to be reset down... > all > >>>>> feels like a workaround. > >>>>> * Implementing a special mode in Scheduler to select tasks with > >>>>> "next_method" being set as signal they are returning from > >> triggerer > >>>>> in a special way... assuming they have a Pool slot and exclude > >> some > >>>>> of the concurrency checks (As in "scheduled" state the pool > slot > >> is > >>>>> actually "lost") > >>>>> But this hard to really propose... as this might be even > harder > >> than > >>>>> the first option as well as the today complex code would get > even > >>>>> harder in scheduler to consider exceptions in concurrency... > with > >>>>> the risk that such special cases exceed the planned > concurrency > >>>>> limits if otherwise the pools are exhausted before already. > >>>>> * Adding a REST API that the triggerer can call on scheduler to > >>>>> cross-post workload. > >>>>> That would need to add a new connection and component > bundling, a > >>>>> REST API endpoint would need to be added for schedulers to > >> receive > >>>>> these push calls. Probably an alternative but also adds > >>>>> architectural dependability. > >>>>> * The PR we propose to discuss here: If the task skips > "scheduled" > >>>>> state and moves to queue directly the pool slot keeps > allocated > >>>>> (assuming that Deferred in actively counting into pool and > >>>>> concurrency limits). Code looked not too complex as just the > >>>>> enqueuing logic from Scheduler could be integrated. > >>>>> In this it is considering that such direct queuing is only > >> possible > >>>>> if the executor supports queues (not working for > >> LocalExecutor!). So > >>>>> the proposed PR made it explicitly opt-in. > >>>>> > >>>>> Reasons (and pro-arguments) why we propose to have the PR on main: > >>>>> > >>>>> * As of a lot of operational problems recently we tested this > and > >>>>> patched this locally into our 3.1.7 triggerer. Works smoothly > on > >>>>> production since ~1 week > >>>>> * If something goes wrong or Executor is not supported then the > >>>>> existing path setting to "scheduled" is always used as safe > >> fallback > >>>>> * It is selective and is an opt-in feature > >>>>> * We dramatically reduced latency from Pod completion to cleanup > >> some > >>>>> sometimes 6-24h to a few seconds > >>>>> * We assume the cleanup as return from Worker is a small effort > >> only > >>>>> so no harm even if temporarily over-loading some limits > >>>>> * ...But frankly speaking the concurrency limits and Pools were > >>>>> checked initially at time of start. Limiting cleanup later on > >>>>> concurrency limits is not adding any benefits but just delays > and > >>>>> problems. We just want to finish-up work. > >>>>> * But finally actually over-loading is not possible as still the > >> Redis > >>>>> queue is in between - so any free Celery Worker will pick the > >> task. > >>>>> Even in over-load it will just sit in Celery queue for a > moment. > >>>>> * It is a relatively small change > >>>>> * Off-loads scheduler by 50% for all deferred tasks (need to > pass > >>>>> scheduler only once) > >>>>> * Due to reduced latency on cleanup more "net workload" > >> schedulable on > >>>>> the cluster, higher cloud utilization / less idle time. > >>>>> > >>>>> Hearing the feedback on PR reflecting with the devils advocate I > could > >>>>> understand the counter arguments: > >>>>> > >>>>> * In Airflow 2 there was a mini-scheduler, there was a hard > fight > >> in > >>>>> Airflow 3 to get rid of this! > >>>>> Understand. But we do not want to add a "mini scheduler" we > just > >>>>> want to use parts of the Executor code to push the task > instance > >> to > >>>>> queue and skip scheduling. It is NOT the target to make any > more > >> and > >>>>> schedule anything else. > >>>>> * This would skip all concurrency checks and potentially > over-load > >> the > >>>>> workers! > >>>>> No. Concurrency rules are checked when the workload is > initially > >>>>> started. I know there are parallel bugs we are fighting with > to > >>>>> ensure deferred status is counted on all levels into > concurrency > >> to > >>>>> correctly keep limits. Assuming that you enable counting > deferred > >>>>> into pools, a direct re-queue to worker is just keeping the > >> level of > >>>>> concurrency not adding more workload... just transferring > back. > >> And > >>>>> Celery for example has a queue so not really over-loading. It > is > >>>>> mainly intended to clean-up workload which is a low effort > task. > >>>>> * We plan to cut-off components and untangle package > dependencies. > >>>>> After worker the Dag parser and triggerer are next. Linking to > >>>>> Executor defeats these plans! > >>>>> Yes, understood. But also today the setting of the > task_instance > >> is > >>>>> using direct DB access... and would in such surgery need to be > >> cut > >>>>> to the level that the DB access would need to be moved to > >> execution > >>>>> API back-end. So the cut for re-queueing would move to > execution > >> API > >>>>> in future, not triggerer. I think it would be valid to think > >> about > >>>>> the options if such distribution is made how that might > evolve in > >>>>> future. > >>>>> * This option is risky and we have concerns people have more > >> errors. > >>>>> Feature is opt-in, need to be configured. Per default as > >> proposed in > >>>>> the PR it is not active. Would be also acceptable to mark this > >>>>> experimental for a while. > >>>>> > >>>>> Sorry, a bit longer text. Happy to get feedback. > >>>>> > >>>>> Jens > >>>>> > >>>> --------------------------------------------------------------------- > >>>> To unsubscribe, e-mail:[email protected] > >>>> For additional commands, e-mail:[email protected] > >>>> > >>>> > > --------------------------------------------------------------------- > To unsubscribe, e-mail: [email protected] > For additional commands, e-mail: [email protected] > >
