Hello Okku,
I looked into your case and even though I cannot divulge private
information in a public post, there is this[1] article that states that the
max is five transactional tasks into the task queues during a single
transaction. It also says that the tasks are enqueued, rather than acting
in parallel. Obviously, if they happen fast, they may appear as parallel.
But in this case, they are slow from your perspective. And I think what you
are asking is why they are throttled every second when they take ms to
complete (as shown in the picture above), rather than what the ceiling
should be.
For example, in the picture, the 33rd second of 23:26 has 5 tasks and you
should aim to reach that consistently if you want it to be faster (but it
will never fully be parallel since they are enqueued). If you have them all
in the same run_in_transaction() function, that could be the cause of it.
It's hard to say what should and shouldn't be the best pattern due to the
semantics of your application, but I think it might be best to look at it
in reverse and try to figure why certain tasks can happen 5 times a second
and then duplicate that as an appropriate pattern in your application.
The bug that was confirmed previously was more of an outage. Engineers can
relate those delays to outages. However if you are experiencing this three
times with months apart, a secondary problem could be the root cause.
I understand that your initial question was if others are having this issue
and I will let others answer, but I did some research for that too and
didn't find it to be common. If you need further specific assistance, it
might best best to do a support ticket. Otherwise, try to isolate why
certain tasks are faster than others in comparison with your business logic.
[1]
https://cloud.google.com/appengine/docs/standard/python/datastore/transactions#transactional_task_enqueuing
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