Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

admission,goschedstats: add metrics for non work-conserving CPU behavior #96511

Open
wants to merge 1 commit into
base: master
Choose a base branch
from

Conversation

sumeerbhola
Copy link
Collaborator

We have encountered scenarios with a large number of goroutines, which often causes an increase in the runnable goroutines, while the mean CPU utilization stays low (sometimes as low as 25%). Since there are non-zero runnable goroutines, at very short time scales of a few millis, CPU utilization must be 100% at those time scales. Since admission control (AC) samples the runnable goroutine count every 1ms, in order to react to such short time scales, we do see some drop in the slot count in some of these scenarios, and see queueing in the AC queues. The concern that comes up when seeing such queueing is whether AC is making the situation worse in its attempt to shift some queueing from the goroutine scheduler into the AC queue. Note that since admission.kv_slot_adjuster.overload_threshold is set to 32, AC does allow for significant queuing in the goroutine scheduler too, in an attempt to be work conserving. But it is still possible that the slot adjustment logic is being too slow to react and not allowing enough concurrency to keep the CPUs busy.

This PR adds two metrics to measure this behavior. These are still subject to sampling errors, but they are tied to the 1ms sampling of CPULoad. The admission.granter.cpu_non_work_conserving_duration.kv is incremented by the sampling duration * number of idle Ps if there are requests waiting in the AC KV (CPU) queue. Since we have observed idle P's even when there are runnable goroutines (which is not the fault of AC), there is another metric admission.granter.cpu_non_work_conserving_due_to_admission_duration.kv which discounts the number of idle Ps by the number of runnable goroutines.

These metrics give a sense of how much CPU capacity we are wasting per second. For example, if the first metric has a value 0.5s/s and we have 10 CPUs, so 10s/s of capacity, we are wasting 5% of the CPU. If the second metric is 0.3s/s then 3% of that CPU wastage can be attributed to AC queueing not behaving well. That is, one may expect CPU utilization to increase by 3% if AC is switched off. These metrics don't tell us the real latency impact of turning off AC, but the expectation is that if the reduction in CPU utilization due to AC divided by the observed CPU utilization (with AC on) is very small, the latency benefit of turning off AC will be small.

Epic: none

Fixes: #96495

@sumeerbhola sumeerbhola requested a review from a team as a code owner February 3, 2023 17:20
@cockroach-teamcity
Copy link
Member

This change is Reviewable

@sumeerbhola sumeerbhola force-pushed the work_conserving branch 3 times, most recently from 37a5a72 to 738829c Compare February 6, 2023 18:11
@sumeerbhola sumeerbhola requested a review from a team February 6, 2023 18:11
Copy link
Contributor

@abarganier abarganier left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

New metrics in general LGTM, just one small nit re: some additional clarification in the HELP text.

(not commenting on specific ways we're recording/using the metrics).

Reviewable status: :shipit: complete! 0 of 0 LGTMs obtained (waiting on @irfansharif and @sumeerbhola)


pkg/util/admission/granter.go line 652 at r1 (raw file):

	}
	// NB: Both the following metrics do not look at the SQL queues, since if
	// the KV queue is empty the only throttling on the SQL queues is via grant

nit: If neither of these metrics look at SQL queues, I think it'd be nice to include that information in the help text for both metrics.

Code quote:

	// NB: Both the following metrics do not look at the SQL queues, since if
	// the KV queue is empty the only throttling on the SQL queues is via grant
	// chaining, which should only cause delays if there is no CPU available.

@sumeerbhola sumeerbhola force-pushed the work_conserving branch 2 times, most recently from 5ab18e7 to 3167e0a Compare February 8, 2023 19:39
We have encountered scenarios with a large number of goroutines, which often
causes an increase in the runnable goroutines, while the mean CPU utilization
stays low (sometimes as low as 25%). Since there are non-zero runnable
goroutines, at very short time scales of a few millis, CPU utilization must
be 100% at those time scales. Since admission control (AC) samples the
runnable goroutine count every 1ms, in order to react to such short time
scales, we do see some drop in the slot count in some of these scenarios, and
see queueing in the AC queues. The concern that comes up when seeing such
queueing is whether AC is making the situation worse in its attempt to shift
some queueing from the goroutine scheduler into the AC queue. Note that since
admission.kv_slot_adjuster.overload_threshold is set to 32, AC does allow for
significant queuing in the goroutine scheduler too, in an attempt to be work
conserving. But it is still possible that the slot adjustment logic is being
too slow to react and not allowing enough concurrency to keep the CPUs busy.

This PR adds two metrics to measure this behavior. These are still subject
to sampling errors, but they are tied to the 1ms sampling of CPULoad.
The admission.granter.cpu_non_work_conserving_duration.kv is incremented
by the sampling duration * number of idle Ps if there are requests waiting
in the AC KV (CPU) queue. Since we have observed idle P's even when there are
runnable goroutines (which is not the fault of AC), there is another metric
admission.granter.cpu_non_work_conserving_due_to_admission_duration.kv
which discounts the number of idle Ps by the number of runnable goroutines.

These metrics give a sense of how much CPU capacity we are wasting per
second. For example, if the first metric has a value 0.5s/s and we have
10 CPUs, so 10s/s of capacity, we are wasting 5% of the CPU. If the second
metric is 0.3s/s then 3% of that CPU wastage can be attributed to AC
queueing not behaving well. That is, one may expect CPU utilization to
increase by 3% if AC is switched off. These metrics don't tell us the real
latency impact of turning off AC, but the expectation is that if the
reduction in CPU utilization due to AC divided by the observed CPU
utilization (with AC on) is very small, the latency benefit of turning off
AC will be small.

Epic: none
Fixes: cockroachdb#96495
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

admission: CPU metrics for high concurrency scenarios
3 participants