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Provide support for multiple triggers #476
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Thoughts @jeffhollan? |
Interesting. How would this exactly calculate the final replicas count? Sum across all triggers? Or what is the idea on the scaling logic here? |
I would say that we just scale out if both criteria has met. As far as I know we just add one instance every time based on the metric but you're more thinking in terms of the HPA underneath it or? |
Yeah, but it is interesting scenario for sure. We should look into this. |
The |
Hi, is there any update on where this feature stands? |
We have a similar use case as we watch multiple Redis lists from same deployment.. it would be nice if I could also specify a single trigger with a regex on the queue name, and get the scaler to watch all matching queues then allow also scale on total sum of elements across all queues. @inuyasha82 FYI |
I think the change is not hard to implement, i have an idea even where to put it, i can probably work on it in the next weeks. |
This will be finalized with #733, right @zroubalik ? |
@tomkerkhove yes! |
Solved in #966 |
Just verifying - This is only for ScaledObject I presume? |
I think it should work for ScaledJob as well. @TsuyoshiUshio could you please confirm? |
Hi, Could you please provide an example for multiple triggers for rabbitmq? I have deleted KEDA 1.5 and deployed KEDA 2.0.0-rc2 in our dev cluster. If I create following yaml (single trigger), everything works:
If I add triggers it breaks (I need 5 but even 2 breaks it):
Also, in the documentation: It shows |
@alegmal and what problem are you exactly facing? |
Figured it out. Apparently scaledobjects.keda.k8s.io was not really deleted and it did not let me delete it. After running that command it instantly deleted crd/scaledobjects.keda.k8s.io and now everything seems to work! |
@alegmal glad to hear that :) Yeah it is important to delete the old CRDs first (https://keda.sh/docs/2.0/migration/#migrating-from-keda-v1-to-v2) |
Signed-off-by: Federico Hernandez <f@ederi.co>
Provide support for multiple triggers that act as an
AND
.Use-Case
Queue processing that persists orders in the database.
As of today, we can autoscale based on message count but if our DB DTU is at 99% capacity we'll only make it worse.
Specification
Kudos to @jornbeyers for idea
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