Question:
<!-- Please use this template while reporting a bug and provide as much info as possible. Not doing so may result in your bug not being addressed in a timely manner. Thanks!--What happened: In our stress testing, we found the deadlock issue in PLEG relist() for healthy checking and Kubelet syncLoop() The goroutine stack trace is as following We did some investigation, and found the following issue. The main loop for event processing in Kubelet will check if there are some runtimeErrors: if yes, wait until runtime back to normal; if no, it will call syncLoopIteration to read and process events. And the runtime healthChecks depends on the But in the relist() impl, it will send the pod lifecycle event to eventChannel which may introduce deadlock when eventChannel is full. And in the above code, the eventChannel will not be consumed if the runtime is not healthy. In some situation, the eventChannel may full, and the relist() will hang in sending new pod lifecycle event. And the runtime status will not be able to recovered. It is related to issues What you expected to happen: No such issue How to reproduce it (as minimally and precisely as possible): It is not easy to reproduce, it happens after few days stress testing (scaling the deployment repeatedly with high load). Anything else we need to know?: Environment: Kubernetes version (use ): 1.11.5 Cloud provider or hardware configuration: Bare metal OS (e.g. from /etc/os-release): CentOS 7.4 Kernel (e.g. ): Linux bjc-qtt-k8s-node-010 3.10.0-693.2.2.el7.x8664 SMP Tue Sep 12 22:26:13 UTC 2017 x8664 x8664 x8664 GNU/Linux Install tools: kubeadm Others: <!-- DO NOT EDIT BELOW THIS LINE --/kind bug
/sig node
Sure, thank you We had some internal fix to break the deadlock, but I am wondering if there are good fix for such kind of issue.
When pleg do relist, can we invoke to judge runtime is ok, if not, not do relist
I submit a PR
Thanks for finding the issue! The issue description makes sense to me. I think PLEG is a core component, we should try our best to unblock it. The event channel becoming full seems more like an issue in the event consumer side, which shouldn't block PLEG. One solution is to queue the events in PLEG and send later, but that doesn't fundamentally solve the problem, if we don't set a limit on the event number we queue, it seems like a potential memory leak to me; if we set a limit, we may eventually hit this problem again. Another solution is to add a retry for sending event in PLEG, and set a bit in PLEG in between the retry which tells that PLEG is not blocking, it is trying to send out the event. And in the function of PLEG, it returns healthy if the bit is set. Actually, even if we fail to send the event and discard it, since we have already updated the pod cache, the periodical pod resync should eventually pick it up. This may delay pod sync for up to . But if the channel is full, it means that either 1) the syncloop is blocked for some reason, or 2) the node is under heavy loads. In both cases, even the event is successfully sent, the pod sync will likely be delayed anyhow. We can: 1) Enlarge the event channel size to reduce the chance that the channel becoming full. Currently it is arbitrarily set as . 2) Discard the event in PLEG if the channel is already full. In the 3 options above, I'm fine with either 2 or 3. Option 2 doesn't have the 1min pod sync delay, but a bit ad-hoc; option 3 is more generic, but may delay pod sync. There might be other options. /cc Any thoughts?
If PLEG is already blocked by a full event channel, this doesn't help right?
cc/ This looks like the one production issue you mentioned to me a while back.
of options enumerated, option 3 was preferred for me.
Thanks for reporting the issue! what was the load on the node that triggered this condition? If the node wasn't function at all, and the events slowly built up over time, bumping the size of the channel won't help. This should work, and doesn't complicate the logic in PLEG more, so it's my preferred option too. We need some unit tests, and ideally, a stress test, as mentioned in the sig-node meeting.
Agree, giving a proper size for event channel is tricky as the scale also grows with time. We will ship fix as option 3 () for 1.14. Thanks for summarizing all these up as sig meeting! /assign
If possible, could you share in how large the stress is? It helps understand the issue and kubelet stress handling more. :)
Sure, our product team ( ) will input the stress test data after removing sensitive information in follow up comments.
Thanks for reply. Following is our testcase to reproduce this issue: The test cluster has 5 node on aliyun ECS(like EC2). Three 4C8G machine as master node, Two 96C384G as worker node. Firstly, We create 2 deployment running on the worker node. One deployment is http server pods. Another is siege pods to produce network stress to http server deployment. Those stress test deployments produce 50 CPU Core load on worker node. Then we create a job frequently create/delete 20 pod every 5 seconds. After about 1 day of stess test, The worker node will become NotReady. Dig the pprof goroutine stacktrace found the channel block in .
Yeah, I can see how frequent container state change can cause this issue. The number is very useful, thanks a lot!
cloud you please help to share how to dump the goroutines stack trace of kubelet like what you pasted in your comment. thanks a lot.
This issue is fixed by
using pprof is a answer to my question thank you anyway.

if events[i].Type == ContainerChanged { continue } <del> g.eventChannel <- events[i] </del> <ins> select { case g.eventChannel <- events[i]: default: metrics.PLEGDiscardEvents.WithLabelValues().Inc() klog.Error("event channel is full, discard this relist() cycle event") } </ins> } }


Question:
<!-- Please use this template while reporting a bug and provide as much info as possible. Not doing so may result in your bug not being addressed in a timely manner. Thanks!--What happened: In our stress testing, we found the deadlock issue in PLEG relist() for healthy checking and Kubelet syncLoop() The goroutine stack trace is as following We did some investigation, and found the following issue. The main loop for event processing in Kubelet will check if there are some runtimeErrors: if yes, wait until runtime back to normal; if no, it will call syncLoopIteration to read and process events. And the runtime healthChecks depends on the But in the relist() impl, it will send the pod lifecycle event to eventChannel which may introduce deadlock when eventChannel is full. And in the above code, the eventChannel will not be consumed if the runtime is not healthy. In some situation, the eventChannel may full, and the relist() will hang in sending new pod lifecycle event. And the runtime status will not be able to recovered. It is related to issues What you expected to happen: No such issue How to reproduce it (as minimally and precisely as possible): It is not easy to reproduce, it happens after few days stress testing (scaling the deployment repeatedly with high load). Anything else we need to know?: Environment: Kubernetes version (use ): 1.11.5 Cloud provider or hardware configuration: Bare metal OS (e.g. from /etc/os-release): CentOS 7.4 Kernel (e.g. ): Linux bjc-qtt-k8s-node-010 3.10.0-693.2.2.el7.x8664 SMP Tue Sep 12 22:26:13 UTC 2017 x8664 x8664 x8664 GNU/Linux Install tools: kubeadm Others: <!-- DO NOT EDIT BELOW THIS LINE --/kind bug
/sig node
Sure, thank you We had some internal fix to break the deadlock, but I am wondering if there are good fix for such kind of issue.
When pleg do relist, can we invoke to judge runtime is ok, if not, not do relist
I submit a PR
Thanks for finding the issue! The issue description makes sense to me. I think PLEG is a core component, we should try our best to unblock it. The event channel becoming full seems more like an issue in the event consumer side, which shouldn't block PLEG. One solution is to queue the events in PLEG and send later, but that doesn't fundamentally solve the problem, if we don't set a limit on the event number we queue, it seems like a potential memory leak to me; if we set a limit, we may eventually hit this problem again. Another solution is to add a retry for sending event in PLEG, and set a bit in PLEG in between the retry which tells that PLEG is not blocking, it is trying to send out the event. And in the function of PLEG, it returns healthy if the bit is set. Actually, even if we fail to send the event and discard it, since we have already updated the pod cache, the periodical pod resync should eventually pick it up. This may delay pod sync for up to . But if the channel is full, it means that either 1) the syncloop is blocked for some reason, or 2) the node is under heavy loads. In both cases, even the event is successfully sent, the pod sync will likely be delayed anyhow. We can: 1) Enlarge the event channel size to reduce the chance that the channel becoming full. Currently it is arbitrarily set as . 2) Discard the event in PLEG if the channel is already full. In the 3 options above, I'm fine with either 2 or 3. Option 2 doesn't have the 1min pod sync delay, but a bit ad-hoc; option 3 is more generic, but may delay pod sync. There might be other options. /cc Any thoughts?
If PLEG is already blocked by a full event channel, this doesn't help right?
cc/ This looks like the one production issue you mentioned to me a while back.
of options enumerated, option 3 was preferred for me.
Thanks for reporting the issue! what was the load on the node that triggered this condition? If the node wasn't function at all, and the events slowly built up over time, bumping the size of the channel won't help. This should work, and doesn't complicate the logic in PLEG more, so it's my preferred option too. We need some unit tests, and ideally, a stress test, as mentioned in the sig-node meeting.
Agree, giving a proper size for event channel is tricky as the scale also grows with time. We will ship fix as option 3 () for 1.14. Thanks for summarizing all these up as sig meeting! /assign
If possible, could you share in how large the stress is? It helps understand the issue and kubelet stress handling more. :)
Sure, our product team ( ) will input the stress test data after removing sensitive information in follow up comments.
Thanks for reply. Following is our testcase to reproduce this issue: The test cluster has 5 node on aliyun ECS(like EC2). Three 4C8G machine as master node, Two 96C384G as worker node. Firstly, We create 2 deployment running on the worker node. One deployment is http server pods. Another is siege pods to produce network stress to http server deployment. Those stress test deployments produce 50 CPU Core load on worker node. Then we create a job frequently create/delete 20 pod every 5 seconds. After about 1 day of stess test, The worker node will become NotReady. Dig the pprof goroutine stacktrace found the channel block in .
Yeah, I can see how frequent container state change can cause this issue. The number is very useful, thanks a lot!
cloud you please help to share how to dump the goroutines stack trace of kubelet like what you pasted in your comment. thanks a lot.
This issue is fixed by
using pprof is a answer to my question thank you anyway.

const ( testContainerRuntimeType = "fooRuntime" <ins> // largeChannelCap is a large enough capacity to hold all events in a single test. largeChannelCap = 100 </ins> ) type TestGenericPLEG struct {


Question:
<!-- Please use this template while reporting a bug and provide as much info as possible. Not doing so may result in your bug not being addressed in a timely manner. Thanks!--What happened: In our stress testing, we found the deadlock issue in PLEG relist() for healthy checking and Kubelet syncLoop() The goroutine stack trace is as following We did some investigation, and found the following issue. The main loop for event processing in Kubelet will check if there are some runtimeErrors: if yes, wait until runtime back to normal; if no, it will call syncLoopIteration to read and process events. And the runtime healthChecks depends on the But in the relist() impl, it will send the pod lifecycle event to eventChannel which may introduce deadlock when eventChannel is full. And in the above code, the eventChannel will not be consumed if the runtime is not healthy. In some situation, the eventChannel may full, and the relist() will hang in sending new pod lifecycle event. And the runtime status will not be able to recovered. It is related to issues What you expected to happen: No such issue How to reproduce it (as minimally and precisely as possible): It is not easy to reproduce, it happens after few days stress testing (scaling the deployment repeatedly with high load). Anything else we need to know?: Environment: Kubernetes version (use ): 1.11.5 Cloud provider or hardware configuration: Bare metal OS (e.g. from /etc/os-release): CentOS 7.4 Kernel (e.g. ): Linux bjc-qtt-k8s-node-010 3.10.0-693.2.2.el7.x8664 SMP Tue Sep 12 22:26:13 UTC 2017 x8664 x8664 x8664 GNU/Linux Install tools: kubeadm Others: <!-- DO NOT EDIT BELOW THIS LINE --/kind bug
/sig node
Sure, thank you We had some internal fix to break the deadlock, but I am wondering if there are good fix for such kind of issue.
When pleg do relist, can we invoke to judge runtime is ok, if not, not do relist
I submit a PR
Thanks for finding the issue! The issue description makes sense to me. I think PLEG is a core component, we should try our best to unblock it. The event channel becoming full seems more like an issue in the event consumer side, which shouldn't block PLEG. One solution is to queue the events in PLEG and send later, but that doesn't fundamentally solve the problem, if we don't set a limit on the event number we queue, it seems like a potential memory leak to me; if we set a limit, we may eventually hit this problem again. Another solution is to add a retry for sending event in PLEG, and set a bit in PLEG in between the retry which tells that PLEG is not blocking, it is trying to send out the event. And in the function of PLEG, it returns healthy if the bit is set. Actually, even if we fail to send the event and discard it, since we have already updated the pod cache, the periodical pod resync should eventually pick it up. This may delay pod sync for up to . But if the channel is full, it means that either 1) the syncloop is blocked for some reason, or 2) the node is under heavy loads. In both cases, even the event is successfully sent, the pod sync will likely be delayed anyhow. We can: 1) Enlarge the event channel size to reduce the chance that the channel becoming full. Currently it is arbitrarily set as . 2) Discard the event in PLEG if the channel is already full. In the 3 options above, I'm fine with either 2 or 3. Option 2 doesn't have the 1min pod sync delay, but a bit ad-hoc; option 3 is more generic, but may delay pod sync. There might be other options. /cc Any thoughts?
If PLEG is already blocked by a full event channel, this doesn't help right?
cc/ This looks like the one production issue you mentioned to me a while back.
of options enumerated, option 3 was preferred for me.
Thanks for reporting the issue! what was the load on the node that triggered this condition? If the node wasn't function at all, and the events slowly built up over time, bumping the size of the channel won't help. This should work, and doesn't complicate the logic in PLEG more, so it's my preferred option too. We need some unit tests, and ideally, a stress test, as mentioned in the sig-node meeting.
Agree, giving a proper size for event channel is tricky as the scale also grows with time. We will ship fix as option 3 () for 1.14. Thanks for summarizing all these up as sig meeting! /assign
If possible, could you share in how large the stress is? It helps understand the issue and kubelet stress handling more. :)
Sure, our product team ( ) will input the stress test data after removing sensitive information in follow up comments.
Thanks for reply. Following is our testcase to reproduce this issue: The test cluster has 5 node on aliyun ECS(like EC2). Three 4C8G machine as master node, Two 96C384G as worker node. Firstly, We create 2 deployment running on the worker node. One deployment is http server pods. Another is siege pods to produce network stress to http server deployment. Those stress test deployments produce 50 CPU Core load on worker node. Then we create a job frequently create/delete 20 pod every 5 seconds. After about 1 day of stess test, The worker node will become NotReady. Dig the pprof goroutine stacktrace found the channel block in .
Yeah, I can see how frequent container state change can cause this issue. The number is very useful, thanks a lot!
cloud you please help to share how to dump the goroutines stack trace of kubelet like what you pasted in your comment. thanks a lot.
This issue is fixed by
using pprof is a answer to my question thank you anyway.

} func newTestGenericPLEG() *TestGenericPLEG { <ins> return newTestGenericPLEGWithChannelSize(largeChannelCap) } func newTestGenericPLEGWithChannelSize(eventChannelCap int) *TestGenericPLEG { </ins> fakeRuntime := &containertest.FakeRuntime{} clock := clock.NewFakeClock(time.Time{}) // The channel capacity should be large enough to hold all events in a


Question:
<!-- Please use this template while reporting a bug and provide as much info as possible. Not doing so may result in your bug not being addressed in a timely manner. Thanks!--What happened: In our stress testing, we found the deadlock issue in PLEG relist() for healthy checking and Kubelet syncLoop() The goroutine stack trace is as following We did some investigation, and found the following issue. The main loop for event processing in Kubelet will check if there are some runtimeErrors: if yes, wait until runtime back to normal; if no, it will call syncLoopIteration to read and process events. And the runtime healthChecks depends on the But in the relist() impl, it will send the pod lifecycle event to eventChannel which may introduce deadlock when eventChannel is full. And in the above code, the eventChannel will not be consumed if the runtime is not healthy. In some situation, the eventChannel may full, and the relist() will hang in sending new pod lifecycle event. And the runtime status will not be able to recovered. It is related to issues What you expected to happen: No such issue How to reproduce it (as minimally and precisely as possible): It is not easy to reproduce, it happens after few days stress testing (scaling the deployment repeatedly with high load). Anything else we need to know?: Environment: Kubernetes version (use ): 1.11.5 Cloud provider or hardware configuration: Bare metal OS (e.g. from /etc/os-release): CentOS 7.4 Kernel (e.g. ): Linux bjc-qtt-k8s-node-010 3.10.0-693.2.2.el7.x8664 SMP Tue Sep 12 22:26:13 UTC 2017 x8664 x8664 x8664 GNU/Linux Install tools: kubeadm Others: <!-- DO NOT EDIT BELOW THIS LINE --/kind bug
/sig node
Sure, thank you We had some internal fix to break the deadlock, but I am wondering if there are good fix for such kind of issue.
When pleg do relist, can we invoke to judge runtime is ok, if not, not do relist
I submit a PR
Thanks for finding the issue! The issue description makes sense to me. I think PLEG is a core component, we should try our best to unblock it. The event channel becoming full seems more like an issue in the event consumer side, which shouldn't block PLEG. One solution is to queue the events in PLEG and send later, but that doesn't fundamentally solve the problem, if we don't set a limit on the event number we queue, it seems like a potential memory leak to me; if we set a limit, we may eventually hit this problem again. Another solution is to add a retry for sending event in PLEG, and set a bit in PLEG in between the retry which tells that PLEG is not blocking, it is trying to send out the event. And in the function of PLEG, it returns healthy if the bit is set. Actually, even if we fail to send the event and discard it, since we have already updated the pod cache, the periodical pod resync should eventually pick it up. This may delay pod sync for up to . But if the channel is full, it means that either 1) the syncloop is blocked for some reason, or 2) the node is under heavy loads. In both cases, even the event is successfully sent, the pod sync will likely be delayed anyhow. We can: 1) Enlarge the event channel size to reduce the chance that the channel becoming full. Currently it is arbitrarily set as . 2) Discard the event in PLEG if the channel is already full. In the 3 options above, I'm fine with either 2 or 3. Option 2 doesn't have the 1min pod sync delay, but a bit ad-hoc; option 3 is more generic, but may delay pod sync. There might be other options. /cc Any thoughts?
If PLEG is already blocked by a full event channel, this doesn't help right?
cc/ This looks like the one production issue you mentioned to me a while back.
of options enumerated, option 3 was preferred for me.
Thanks for reporting the issue! what was the load on the node that triggered this condition? If the node wasn't function at all, and the events slowly built up over time, bumping the size of the channel won't help. This should work, and doesn't complicate the logic in PLEG more, so it's my preferred option too. We need some unit tests, and ideally, a stress test, as mentioned in the sig-node meeting.
Agree, giving a proper size for event channel is tricky as the scale also grows with time. We will ship fix as option 3 () for 1.14. Thanks for summarizing all these up as sig meeting! /assign
If possible, could you share in how large the stress is? It helps understand the issue and kubelet stress handling more. :)
Sure, our product team ( ) will input the stress test data after removing sensitive information in follow up comments.
Thanks for reply. Following is our testcase to reproduce this issue: The test cluster has 5 node on aliyun ECS(like EC2). Three 4C8G machine as master node, Two 96C384G as worker node. Firstly, We create 2 deployment running on the worker node. One deployment is http server pods. Another is siege pods to produce network stress to http server deployment. Those stress test deployments produce 50 CPU Core load on worker node. Then we create a job frequently create/delete 20 pod every 5 seconds. After about 1 day of stess test, The worker node will become NotReady. Dig the pprof goroutine stacktrace found the channel block in .
Yeah, I can see how frequent container state change can cause this issue. The number is very useful, thanks a lot!
cloud you please help to share how to dump the goroutines stack trace of kubelet like what you pasted in your comment. thanks a lot.
This issue is fixed by
using pprof is a answer to my question thank you anyway.

pleg := &GenericPLEG{ relistPeriod: time.Hour, runtime:      fakeRuntime, <del> eventChannel: make(chan *PodLifecycleEvent, 100), </del> <ins> eventChannel: make(chan *PodLifecycleEvent, eventChannelCap), </ins> podRecords:   make(podRecords), clock:        clock, }


Question:
<!-- Please use this template while reporting a bug and provide as much info as possible. Not doing so may result in your bug not being addressed in a timely manner. Thanks!--What happened: In our stress testing, we found the deadlock issue in PLEG relist() for healthy checking and Kubelet syncLoop() The goroutine stack trace is as following We did some investigation, and found the following issue. The main loop for event processing in Kubelet will check if there are some runtimeErrors: if yes, wait until runtime back to normal; if no, it will call syncLoopIteration to read and process events. And the runtime healthChecks depends on the But in the relist() impl, it will send the pod lifecycle event to eventChannel which may introduce deadlock when eventChannel is full. And in the above code, the eventChannel will not be consumed if the runtime is not healthy. In some situation, the eventChannel may full, and the relist() will hang in sending new pod lifecycle event. And the runtime status will not be able to recovered. It is related to issues What you expected to happen: No such issue How to reproduce it (as minimally and precisely as possible): It is not easy to reproduce, it happens after few days stress testing (scaling the deployment repeatedly with high load). Anything else we need to know?: Environment: Kubernetes version (use ): 1.11.5 Cloud provider or hardware configuration: Bare metal OS (e.g. from /etc/os-release): CentOS 7.4 Kernel (e.g. ): Linux bjc-qtt-k8s-node-010 3.10.0-693.2.2.el7.x8664 SMP Tue Sep 12 22:26:13 UTC 2017 x8664 x8664 x8664 GNU/Linux Install tools: kubeadm Others: <!-- DO NOT EDIT BELOW THIS LINE --/kind bug
/sig node
Sure, thank you We had some internal fix to break the deadlock, but I am wondering if there are good fix for such kind of issue.
When pleg do relist, can we invoke to judge runtime is ok, if not, not do relist
I submit a PR
Thanks for finding the issue! The issue description makes sense to me. I think PLEG is a core component, we should try our best to unblock it. The event channel becoming full seems more like an issue in the event consumer side, which shouldn't block PLEG. One solution is to queue the events in PLEG and send later, but that doesn't fundamentally solve the problem, if we don't set a limit on the event number we queue, it seems like a potential memory leak to me; if we set a limit, we may eventually hit this problem again. Another solution is to add a retry for sending event in PLEG, and set a bit in PLEG in between the retry which tells that PLEG is not blocking, it is trying to send out the event. And in the function of PLEG, it returns healthy if the bit is set. Actually, even if we fail to send the event and discard it, since we have already updated the pod cache, the periodical pod resync should eventually pick it up. This may delay pod sync for up to . But if the channel is full, it means that either 1) the syncloop is blocked for some reason, or 2) the node is under heavy loads. In both cases, even the event is successfully sent, the pod sync will likely be delayed anyhow. We can: 1) Enlarge the event channel size to reduce the chance that the channel becoming full. Currently it is arbitrarily set as . 2) Discard the event in PLEG if the channel is already full. In the 3 options above, I'm fine with either 2 or 3. Option 2 doesn't have the 1min pod sync delay, but a bit ad-hoc; option 3 is more generic, but may delay pod sync. There might be other options. /cc Any thoughts?
If PLEG is already blocked by a full event channel, this doesn't help right?
cc/ This looks like the one production issue you mentioned to me a while back.
of options enumerated, option 3 was preferred for me.
Thanks for reporting the issue! what was the load on the node that triggered this condition? If the node wasn't function at all, and the events slowly built up over time, bumping the size of the channel won't help. This should work, and doesn't complicate the logic in PLEG more, so it's my preferred option too. We need some unit tests, and ideally, a stress test, as mentioned in the sig-node meeting.
Agree, giving a proper size for event channel is tricky as the scale also grows with time. We will ship fix as option 3 () for 1.14. Thanks for summarizing all these up as sig meeting! /assign
If possible, could you share in how large the stress is? It helps understand the issue and kubelet stress handling more. :)
Sure, our product team ( ) will input the stress test data after removing sensitive information in follow up comments.
Thanks for reply. Following is our testcase to reproduce this issue: The test cluster has 5 node on aliyun ECS(like EC2). Three 4C8G machine as master node, Two 96C384G as worker node. Firstly, We create 2 deployment running on the worker node. One deployment is http server pods. Another is siege pods to produce network stress to http server deployment. Those stress test deployments produce 50 CPU Core load on worker node. Then we create a job frequently create/delete 20 pod every 5 seconds. After about 1 day of stess test, The worker node will become NotReady. Dig the pprof goroutine stacktrace found the channel block in .
Yeah, I can see how frequent container state change can cause this issue. The number is very useful, thanks a lot!
cloud you please help to share how to dump the goroutines stack trace of kubelet like what you pasted in your comment. thanks a lot.
This issue is fixed by
using pprof is a answer to my question thank you anyway.

verifyEvents(t, expected, actual) } <ins> // TestEventChannelFull test when channel is full, the events will be discard. func TestEventChannelFull(t *testing.T) { testPleg := newTestGenericPLEGWithChannelSize(4) pleg, runtime := testPleg.pleg, testPleg.runtime ch := pleg.Watch() // The first relist should send a PodSync event to each pod. runtime.AllPodList = []*containertest.FakePod{ {Pod: &kubecontainer.Pod{ ID: "1234", Containers: []*kubecontainer.Container{ createTestContainer("c1", kubecontainer.ContainerStateExited), createTestContainer("c2", kubecontainer.ContainerStateRunning), createTestContainer("c3", kubecontainer.ContainerStateUnknown), }, }}, {Pod: &kubecontainer.Pod{ ID: "4567", Containers: []*kubecontainer.Container{ createTestContainer("c1", kubecontainer.ContainerStateExited), }, }}, } pleg.relist() // Report every running/exited container if we see them for the first time. expected := []*PodLifecycleEvent{ {ID: "1234", Type: ContainerStarted, Data: "c2"}, {ID: "4567", Type: ContainerDied, Data: "c1"}, {ID: "1234", Type: ContainerDied, Data: "c1"}, } actual := getEventsFromChannel(ch) verifyEvents(t, expected, actual) runtime.AllPodList = []*containertest.FakePod{ {Pod: &kubecontainer.Pod{ ID: "1234", Containers: []*kubecontainer.Container{ createTestContainer("c2", kubecontainer.ContainerStateExited), createTestContainer("c3", kubecontainer.ContainerStateRunning), }, }}, {Pod: &kubecontainer.Pod{ ID: "4567", Containers: []*kubecontainer.Container{ createTestContainer("c4", kubecontainer.ContainerStateRunning), }, }}, } pleg.relist() // event channel is full, discard events expected = []*PodLifecycleEvent{ {ID: "1234", Type: ContainerRemoved, Data: "c1"}, {ID: "1234", Type: ContainerDied, Data: "c2"}, {ID: "1234", Type: ContainerStarted, Data: "c3"}, {ID: "4567", Type: ContainerRemoved, Data: "c1"}, } actual = getEventsFromChannel(ch) verifyEvents(t, expected, actual) } </ins> func TestDetectingContainerDeaths(t *testing.T) { // Vary the number of relists after the container started and before the // container died to account for the changes in pleg's internal states.


Question:
Related: On Windows, kubelet reports only the cumulative for cpu usage. On Linux, kubelet reports both and the instantaneous . Although In the future, most components/monitoring pipelines will switch to using the cumulative metrics, a few features still depend on the instantaneous metrics today. Examples are: , HPA/VPA. Kubelet should report this metrics on Windows to support the existing features. /cc who explained to me what features depend on the cpu metrics. /cc /cc
- is this something that's clear enough in the CRI layer that you can implement it, or do we need to fix that first?
/assign
do you have any notes or a doc you can point to that better describes what features depend on which metrics? It would be good for us to share and see if anything other than is broken
The horizontal and vertical pod autoscalers also depend on the
Documentation on metrics API and metrics server (i.e., the aggregator): The metrics-server pod keeps spewing errors like this: Running : I haven't verified whether pod autoscaling works in my cluster, but I assume they won't since metrics server seems to discard the metrics from the windows pods. I believe the implementation is in kubelet (for the docker integration), so this should not need CRI changes.
I think this is generally an issue for non-Docker CRIs (not necessarily Windows-exclusive). The kubelet source code suggests that these metrics will be gathered from the CRI (if the CRI is not Docker). The struct that kubelet expects returned from the ContainerStats RPC does not include usageNanoCores. Does this mean that, until this is resolved, custom CRIs are unable to satisfactorily report metrics to the 'metrics-server'?
- are you able to work on this?
that is a good point. For CRI runtimes, the kubelet should calculate the average over 10s to produce this metric.
Good point. We designed CRI around core metrics API, but some CRI runtimes have integrated with cadvisor directly to fill the gap while we wait for core metrics API. I think it's reasonable for kubelet to do this on behalf of all CRI runtimes. I spoke to offline, and this would probably require no more than 2 days of work. If sig-windows (e.g., can pick this up, that'd be great. has agreed to review the changes (thanks!) If not, we should clearly document that this is not supported in Windows GA for 1.14.
thanks for the update. we will wait to hear back from
Currently, is got from docker's stats API on Windows. From docker stats API , only is available, hence is not set on Windows: Do you know any way to get instantaneous for Windows containers?
I have no idea. any idea?
I think this is broader than just a Windows issue. Officially supported tools such as the kubernetes metrics-server expect the field, but custom CRIs that conform to the interfaces defined in the package are not given the liberty to return this value.
suggested previously to cache the stats temporarily and compute the stats using the diff. David, could you chime in on how this could be done? Yes, this was mentioned in the previous comments too. There are plans to transition those components off this field, but it's WIP. We are looking for a workaround in kubelet for now.
my biggest worry is that if we say this impacts the horizonal POD autoscaler, how is that passing in our end2end and conformance tests?
Do you test HPA? It's not part of conformance, and I doubt this is included in windows testing.
As to how this could be done, in and we could just add a in the struct, which we assign the previous CpuUsage metric for each container. Then, when we need to calculate the rate, we pass the previous CpuUsage along with the current one to , and calculate a rate based on the timestamp and values.
ListPodCPUAndMemoryStats() we could just add a map[string]*runtimeapi.CpuUsage in the criStatsProvider struct I've done some tinkering on this myself and I originally thought that it would be as simple as that. It gets much more complicated when you have to work in between the existing cAdvisor-based logic. I assume the intent is to cut it out entirely eventually, but the information passed through the CRI doesn't even come close to being so comprehensive. So far I've found that this approach fixes the problem for the "/stats/summary" api, but not necessarily for the other apis. In particular, "/stats/container" seems to be completely based on cAdvisor, being unimpacted by the changes we made to those two functions. Some monitoring tools and metrics scrapers rely on the "/stats/container" api for their metrics, which means it is insufficient to update one api without doing the other.
We don't need to fill in everything in the summary API, just "usageNanoCores". The "/stats/summary" api is the one used by the metrics server, which is why we care about it in this case. The "/stats/container" isn't something we need to implement to support this.
we a couple of tickets to validate if HPA for Windows containers works. My guess is that it works for memory and not for CPU metrics because of this issue. If this is complicated to fix, i wonder if waiting for the CRI containerD changes in windows would be the best option for supporting this.
containerd and cri-o bypass this issue by leveraging cadvisor as a temporary solution. I don't think that'd work for windows.
Sorry the for late response. HPA is actually working for Windows containers. e.g. in my cluster (v1.12.5), cpu-based HPA is working as expected: Which version of kubernetes are you referring for HPA issues?
are you running heapster, or the metrics server to serve HPA? Heapster uses the cumulative metric, but the metrics-server uses the 10 average rate metric.
metrics-server is used in my cluster.
See .
/milestone v1.14

"path" "sort" "strings" <ins> "sync" </ins> "time" cadvisorfs "github.com/google/cadvisor/fs"


Question:
Related: On Windows, kubelet reports only the cumulative for cpu usage. On Linux, kubelet reports both and the instantaneous . Although In the future, most components/monitoring pipelines will switch to using the cumulative metrics, a few features still depend on the instantaneous metrics today. Examples are: , HPA/VPA. Kubelet should report this metrics on Windows to support the existing features. /cc who explained to me what features depend on the cpu metrics. /cc /cc
- is this something that's clear enough in the CRI layer that you can implement it, or do we need to fix that first?
/assign
do you have any notes or a doc you can point to that better describes what features depend on which metrics? It would be good for us to share and see if anything other than is broken
The horizontal and vertical pod autoscalers also depend on the
Documentation on metrics API and metrics server (i.e., the aggregator): The metrics-server pod keeps spewing errors like this: Running : I haven't verified whether pod autoscaling works in my cluster, but I assume they won't since metrics server seems to discard the metrics from the windows pods. I believe the implementation is in kubelet (for the docker integration), so this should not need CRI changes.
I think this is generally an issue for non-Docker CRIs (not necessarily Windows-exclusive). The kubelet source code suggests that these metrics will be gathered from the CRI (if the CRI is not Docker). The struct that kubelet expects returned from the ContainerStats RPC does not include usageNanoCores. Does this mean that, until this is resolved, custom CRIs are unable to satisfactorily report metrics to the 'metrics-server'?
- are you able to work on this?
that is a good point. For CRI runtimes, the kubelet should calculate the average over 10s to produce this metric.
Good point. We designed CRI around core metrics API, but some CRI runtimes have integrated with cadvisor directly to fill the gap while we wait for core metrics API. I think it's reasonable for kubelet to do this on behalf of all CRI runtimes. I spoke to offline, and this would probably require no more than 2 days of work. If sig-windows (e.g., can pick this up, that'd be great. has agreed to review the changes (thanks!) If not, we should clearly document that this is not supported in Windows GA for 1.14.
thanks for the update. we will wait to hear back from
Currently, is got from docker's stats API on Windows. From docker stats API , only is available, hence is not set on Windows: Do you know any way to get instantaneous for Windows containers?
I have no idea. any idea?
I think this is broader than just a Windows issue. Officially supported tools such as the kubernetes metrics-server expect the field, but custom CRIs that conform to the interfaces defined in the package are not given the liberty to return this value.
suggested previously to cache the stats temporarily and compute the stats using the diff. David, could you chime in on how this could be done? Yes, this was mentioned in the previous comments too. There are plans to transition those components off this field, but it's WIP. We are looking for a workaround in kubelet for now.
my biggest worry is that if we say this impacts the horizonal POD autoscaler, how is that passing in our end2end and conformance tests?
Do you test HPA? It's not part of conformance, and I doubt this is included in windows testing.
As to how this could be done, in and we could just add a in the struct, which we assign the previous CpuUsage metric for each container. Then, when we need to calculate the rate, we pass the previous CpuUsage along with the current one to , and calculate a rate based on the timestamp and values.
ListPodCPUAndMemoryStats() we could just add a map[string]*runtimeapi.CpuUsage in the criStatsProvider struct I've done some tinkering on this myself and I originally thought that it would be as simple as that. It gets much more complicated when you have to work in between the existing cAdvisor-based logic. I assume the intent is to cut it out entirely eventually, but the information passed through the CRI doesn't even come close to being so comprehensive. So far I've found that this approach fixes the problem for the "/stats/summary" api, but not necessarily for the other apis. In particular, "/stats/container" seems to be completely based on cAdvisor, being unimpacted by the changes we made to those two functions. Some monitoring tools and metrics scrapers rely on the "/stats/container" api for their metrics, which means it is insufficient to update one api without doing the other.
We don't need to fill in everything in the summary API, just "usageNanoCores". The "/stats/summary" api is the one used by the metrics server, which is why we care about it in this case. The "/stats/container" isn't something we need to implement to support this.
we a couple of tickets to validate if HPA for Windows containers works. My guess is that it works for memory and not for CPU metrics because of this issue. If this is complicated to fix, i wonder if waiting for the CRI containerD changes in windows would be the best option for supporting this.
containerd and cri-o bypass this issue by leveraging cadvisor as a temporary solution. I don't think that'd work for windows.
Sorry the for late response. HPA is actually working for Windows containers. e.g. in my cluster (v1.12.5), cpu-based HPA is working as expected: Which version of kubernetes are you referring for HPA issues?
are you running heapster, or the metrics server to serve HPA? Heapster uses the cumulative metric, but the metrics-server uses the 10 average rate metric.
metrics-server is used in my cluster.
See .
/milestone v1.14

kubetypes "k8s.io/kubernetes/pkg/kubelet/types" ) <ins> var ( // defaultCachePeriod is the default cache period for each cpuUsage. defaultCachePeriod = 10 * time.Minute ) </ins> // criStatsProvider implements the containerStatsProvider interface by getting // the container stats from CRI. type criStatsProvider struct {


Question:
Related: On Windows, kubelet reports only the cumulative for cpu usage. On Linux, kubelet reports both and the instantaneous . Although In the future, most components/monitoring pipelines will switch to using the cumulative metrics, a few features still depend on the instantaneous metrics today. Examples are: , HPA/VPA. Kubelet should report this metrics on Windows to support the existing features. /cc who explained to me what features depend on the cpu metrics. /cc /cc
- is this something that's clear enough in the CRI layer that you can implement it, or do we need to fix that first?
/assign
do you have any notes or a doc you can point to that better describes what features depend on which metrics? It would be good for us to share and see if anything other than is broken
The horizontal and vertical pod autoscalers also depend on the
Documentation on metrics API and metrics server (i.e., the aggregator): The metrics-server pod keeps spewing errors like this: Running : I haven't verified whether pod autoscaling works in my cluster, but I assume they won't since metrics server seems to discard the metrics from the windows pods. I believe the implementation is in kubelet (for the docker integration), so this should not need CRI changes.
I think this is generally an issue for non-Docker CRIs (not necessarily Windows-exclusive). The kubelet source code suggests that these metrics will be gathered from the CRI (if the CRI is not Docker). The struct that kubelet expects returned from the ContainerStats RPC does not include usageNanoCores. Does this mean that, until this is resolved, custom CRIs are unable to satisfactorily report metrics to the 'metrics-server'?
- are you able to work on this?
that is a good point. For CRI runtimes, the kubelet should calculate the average over 10s to produce this metric.
Good point. We designed CRI around core metrics API, but some CRI runtimes have integrated with cadvisor directly to fill the gap while we wait for core metrics API. I think it's reasonable for kubelet to do this on behalf of all CRI runtimes. I spoke to offline, and this would probably require no more than 2 days of work. If sig-windows (e.g., can pick this up, that'd be great. has agreed to review the changes (thanks!) If not, we should clearly document that this is not supported in Windows GA for 1.14.
thanks for the update. we will wait to hear back from
Currently, is got from docker's stats API on Windows. From docker stats API , only is available, hence is not set on Windows: Do you know any way to get instantaneous for Windows containers?
I have no idea. any idea?
I think this is broader than just a Windows issue. Officially supported tools such as the kubernetes metrics-server expect the field, but custom CRIs that conform to the interfaces defined in the package are not given the liberty to return this value.
suggested previously to cache the stats temporarily and compute the stats using the diff. David, could you chime in on how this could be done? Yes, this was mentioned in the previous comments too. There are plans to transition those components off this field, but it's WIP. We are looking for a workaround in kubelet for now.
my biggest worry is that if we say this impacts the horizonal POD autoscaler, how is that passing in our end2end and conformance tests?
Do you test HPA? It's not part of conformance, and I doubt this is included in windows testing.
As to how this could be done, in and we could just add a in the struct, which we assign the previous CpuUsage metric for each container. Then, when we need to calculate the rate, we pass the previous CpuUsage along with the current one to , and calculate a rate based on the timestamp and values.
ListPodCPUAndMemoryStats() we could just add a map[string]*runtimeapi.CpuUsage in the criStatsProvider struct I've done some tinkering on this myself and I originally thought that it would be as simple as that. It gets much more complicated when you have to work in between the existing cAdvisor-based logic. I assume the intent is to cut it out entirely eventually, but the information passed through the CRI doesn't even come close to being so comprehensive. So far I've found that this approach fixes the problem for the "/stats/summary" api, but not necessarily for the other apis. In particular, "/stats/container" seems to be completely based on cAdvisor, being unimpacted by the changes we made to those two functions. Some monitoring tools and metrics scrapers rely on the "/stats/container" api for their metrics, which means it is insufficient to update one api without doing the other.
We don't need to fill in everything in the summary API, just "usageNanoCores". The "/stats/summary" api is the one used by the metrics server, which is why we care about it in this case. The "/stats/container" isn't something we need to implement to support this.
we a couple of tickets to validate if HPA for Windows containers works. My guess is that it works for memory and not for CPU metrics because of this issue. If this is complicated to fix, i wonder if waiting for the CRI containerD changes in windows would be the best option for supporting this.
containerd and cri-o bypass this issue by leveraging cadvisor as a temporary solution. I don't think that'd work for windows.
Sorry the for late response. HPA is actually working for Windows containers. e.g. in my cluster (v1.12.5), cpu-based HPA is working as expected: Which version of kubernetes are you referring for HPA issues?
are you running heapster, or the metrics server to serve HPA? Heapster uses the cumulative metric, but the metrics-server uses the 10 average rate metric.
metrics-server is used in my cluster.
See .
/milestone v1.14

imageService internalapi.ImageManagerService // logMetrics provides the metrics for container logs logMetricsService LogMetricsService <ins> // cpuUsageCache caches the cpu usage for containers. cpuUsageCache map[string]*runtimeapi.CpuUsage mutex         sync.Mutex </ins> } // newCRIStatsProvider returns a containerStatsProvider implementation that


Question:
Related: On Windows, kubelet reports only the cumulative for cpu usage. On Linux, kubelet reports both and the instantaneous . Although In the future, most components/monitoring pipelines will switch to using the cumulative metrics, a few features still depend on the instantaneous metrics today. Examples are: , HPA/VPA. Kubelet should report this metrics on Windows to support the existing features. /cc who explained to me what features depend on the cpu metrics. /cc /cc
- is this something that's clear enough in the CRI layer that you can implement it, or do we need to fix that first?
/assign
do you have any notes or a doc you can point to that better describes what features depend on which metrics? It would be good for us to share and see if anything other than is broken
The horizontal and vertical pod autoscalers also depend on the
Documentation on metrics API and metrics server (i.e., the aggregator): The metrics-server pod keeps spewing errors like this: Running : I haven't verified whether pod autoscaling works in my cluster, but I assume they won't since metrics server seems to discard the metrics from the windows pods. I believe the implementation is in kubelet (for the docker integration), so this should not need CRI changes.
I think this is generally an issue for non-Docker CRIs (not necessarily Windows-exclusive). The kubelet source code suggests that these metrics will be gathered from the CRI (if the CRI is not Docker). The struct that kubelet expects returned from the ContainerStats RPC does not include usageNanoCores. Does this mean that, until this is resolved, custom CRIs are unable to satisfactorily report metrics to the 'metrics-server'?
- are you able to work on this?
that is a good point. For CRI runtimes, the kubelet should calculate the average over 10s to produce this metric.
Good point. We designed CRI around core metrics API, but some CRI runtimes have integrated with cadvisor directly to fill the gap while we wait for core metrics API. I think it's reasonable for kubelet to do this on behalf of all CRI runtimes. I spoke to offline, and this would probably require no more than 2 days of work. If sig-windows (e.g., can pick this up, that'd be great. has agreed to review the changes (thanks!) If not, we should clearly document that this is not supported in Windows GA for 1.14.
thanks for the update. we will wait to hear back from
Currently, is got from docker's stats API on Windows. From docker stats API , only is available, hence is not set on Windows: Do you know any way to get instantaneous for Windows containers?
I have no idea. any idea?
I think this is broader than just a Windows issue. Officially supported tools such as the kubernetes metrics-server expect the field, but custom CRIs that conform to the interfaces defined in the package are not given the liberty to return this value.
suggested previously to cache the stats temporarily and compute the stats using the diff. David, could you chime in on how this could be done? Yes, this was mentioned in the previous comments too. There are plans to transition those components off this field, but it's WIP. We are looking for a workaround in kubelet for now.
my biggest worry is that if we say this impacts the horizonal POD autoscaler, how is that passing in our end2end and conformance tests?
Do you test HPA? It's not part of conformance, and I doubt this is included in windows testing.
As to how this could be done, in and we could just add a in the struct, which we assign the previous CpuUsage metric for each container. Then, when we need to calculate the rate, we pass the previous CpuUsage along with the current one to , and calculate a rate based on the timestamp and values.
ListPodCPUAndMemoryStats() we could just add a map[string]*runtimeapi.CpuUsage in the criStatsProvider struct I've done some tinkering on this myself and I originally thought that it would be as simple as that. It gets much more complicated when you have to work in between the existing cAdvisor-based logic. I assume the intent is to cut it out entirely eventually, but the information passed through the CRI doesn't even come close to being so comprehensive. So far I've found that this approach fixes the problem for the "/stats/summary" api, but not necessarily for the other apis. In particular, "/stats/container" seems to be completely based on cAdvisor, being unimpacted by the changes we made to those two functions. Some monitoring tools and metrics scrapers rely on the "/stats/container" api for their metrics, which means it is insufficient to update one api without doing the other.
We don't need to fill in everything in the summary API, just "usageNanoCores". The "/stats/summary" api is the one used by the metrics server, which is why we care about it in this case. The "/stats/container" isn't something we need to implement to support this.
we a couple of tickets to validate if HPA for Windows containers works. My guess is that it works for memory and not for CPU metrics because of this issue. If this is complicated to fix, i wonder if waiting for the CRI containerD changes in windows would be the best option for supporting this.
containerd and cri-o bypass this issue by leveraging cadvisor as a temporary solution. I don't think that'd work for windows.
Sorry the for late response. HPA is actually working for Windows containers. e.g. in my cluster (v1.12.5), cpu-based HPA is working as expected: Which version of kubernetes are you referring for HPA issues?
are you running heapster, or the metrics server to serve HPA? Heapster uses the cumulative metric, but the metrics-server uses the 10 average rate metric.
metrics-server is used in my cluster.
See .
/milestone v1.14

runtimeService:    runtimeService, imageService:      imageService, logMetricsService: logMetricsService, <ins> cpuUsageCache:     make(map[string]*runtimeapi.CpuUsage), </ins> } }


Question:
Related: On Windows, kubelet reports only the cumulative for cpu usage. On Linux, kubelet reports both and the instantaneous . Although In the future, most components/monitoring pipelines will switch to using the cumulative metrics, a few features still depend on the instantaneous metrics today. Examples are: , HPA/VPA. Kubelet should report this metrics on Windows to support the existing features. /cc who explained to me what features depend on the cpu metrics. /cc /cc
- is this something that's clear enough in the CRI layer that you can implement it, or do we need to fix that first?
/assign
do you have any notes or a doc you can point to that better describes what features depend on which metrics? It would be good for us to share and see if anything other than is broken
The horizontal and vertical pod autoscalers also depend on the
Documentation on metrics API and metrics server (i.e., the aggregator): The metrics-server pod keeps spewing errors like this: Running : I haven't verified whether pod autoscaling works in my cluster, but I assume they won't since metrics server seems to discard the metrics from the windows pods. I believe the implementation is in kubelet (for the docker integration), so this should not need CRI changes.
I think this is generally an issue for non-Docker CRIs (not necessarily Windows-exclusive). The kubelet source code suggests that these metrics will be gathered from the CRI (if the CRI is not Docker). The struct that kubelet expects returned from the ContainerStats RPC does not include usageNanoCores. Does this mean that, until this is resolved, custom CRIs are unable to satisfactorily report metrics to the 'metrics-server'?
- are you able to work on this?
that is a good point. For CRI runtimes, the kubelet should calculate the average over 10s to produce this metric.
Good point. We designed CRI around core metrics API, but some CRI runtimes have integrated with cadvisor directly to fill the gap while we wait for core metrics API. I think it's reasonable for kubelet to do this on behalf of all CRI runtimes. I spoke to offline, and this would probably require no more than 2 days of work. If sig-windows (e.g., can pick this up, that'd be great. has agreed to review the changes (thanks!) If not, we should clearly document that this is not supported in Windows GA for 1.14.
thanks for the update. we will wait to hear back from
Currently, is got from docker's stats API on Windows. From docker stats API , only is available, hence is not set on Windows: Do you know any way to get instantaneous for Windows containers?
I have no idea. any idea?
I think this is broader than just a Windows issue. Officially supported tools such as the kubernetes metrics-server expect the field, but custom CRIs that conform to the interfaces defined in the package are not given the liberty to return this value.
suggested previously to cache the stats temporarily and compute the stats using the diff. David, could you chime in on how this could be done? Yes, this was mentioned in the previous comments too. There are plans to transition those components off this field, but it's WIP. We are looking for a workaround in kubelet for now.
my biggest worry is that if we say this impacts the horizonal POD autoscaler, how is that passing in our end2end and conformance tests?
Do you test HPA? It's not part of conformance, and I doubt this is included in windows testing.
As to how this could be done, in and we could just add a in the struct, which we assign the previous CpuUsage metric for each container. Then, when we need to calculate the rate, we pass the previous CpuUsage along with the current one to , and calculate a rate based on the timestamp and values.
ListPodCPUAndMemoryStats() we could just add a map[string]*runtimeapi.CpuUsage in the criStatsProvider struct I've done some tinkering on this myself and I originally thought that it would be as simple as that. It gets much more complicated when you have to work in between the existing cAdvisor-based logic. I assume the intent is to cut it out entirely eventually, but the information passed through the CRI doesn't even come close to being so comprehensive. So far I've found that this approach fixes the problem for the "/stats/summary" api, but not necessarily for the other apis. In particular, "/stats/container" seems to be completely based on cAdvisor, being unimpacted by the changes we made to those two functions. Some monitoring tools and metrics scrapers rely on the "/stats/container" api for their metrics, which means it is insufficient to update one api without doing the other.
We don't need to fill in everything in the summary API, just "usageNanoCores". The "/stats/summary" api is the one used by the metrics server, which is why we care about it in this case. The "/stats/container" isn't something we need to implement to support this.
we a couple of tickets to validate if HPA for Windows containers works. My guess is that it works for memory and not for CPU metrics because of this issue. If this is complicated to fix, i wonder if waiting for the CRI containerD changes in windows would be the best option for supporting this.
containerd and cri-o bypass this issue by leveraging cadvisor as a temporary solution. I don't think that'd work for windows.
Sorry the for late response. HPA is actually working for Windows containers. e.g. in my cluster (v1.12.5), cpu-based HPA is working as expected: Which version of kubernetes are you referring for HPA issues?
are you running heapster, or the metrics server to serve HPA? Heapster uses the cumulative metric, but the metrics-server uses the 10 average rate metric.
metrics-server is used in my cluster.
See .
/milestone v1.14

} ps.Containers = append(ps.Containers, *cs) } <ins> // cleanup outdated caches. p.cleanupOutdatedCaches() </ins> result := make([]statsapi.PodStats, 0, len(sandboxIDToPodStats)) for _, s := range sandboxIDToPodStats {


Question:
Related: On Windows, kubelet reports only the cumulative for cpu usage. On Linux, kubelet reports both and the instantaneous . Although In the future, most components/monitoring pipelines will switch to using the cumulative metrics, a few features still depend on the instantaneous metrics today. Examples are: , HPA/VPA. Kubelet should report this metrics on Windows to support the existing features. /cc who explained to me what features depend on the cpu metrics. /cc /cc
- is this something that's clear enough in the CRI layer that you can implement it, or do we need to fix that first?
/assign
do you have any notes or a doc you can point to that better describes what features depend on which metrics? It would be good for us to share and see if anything other than is broken
The horizontal and vertical pod autoscalers also depend on the
Documentation on metrics API and metrics server (i.e., the aggregator): The metrics-server pod keeps spewing errors like this: Running : I haven't verified whether pod autoscaling works in my cluster, but I assume they won't since metrics server seems to discard the metrics from the windows pods. I believe the implementation is in kubelet (for the docker integration), so this should not need CRI changes.
I think this is generally an issue for non-Docker CRIs (not necessarily Windows-exclusive). The kubelet source code suggests that these metrics will be gathered from the CRI (if the CRI is not Docker). The struct that kubelet expects returned from the ContainerStats RPC does not include usageNanoCores. Does this mean that, until this is resolved, custom CRIs are unable to satisfactorily report metrics to the 'metrics-server'?
- are you able to work on this?
that is a good point. For CRI runtimes, the kubelet should calculate the average over 10s to produce this metric.
Good point. We designed CRI around core metrics API, but some CRI runtimes have integrated with cadvisor directly to fill the gap while we wait for core metrics API. I think it's reasonable for kubelet to do this on behalf of all CRI runtimes. I spoke to offline, and this would probably require no more than 2 days of work. If sig-windows (e.g., can pick this up, that'd be great. has agreed to review the changes (thanks!) If not, we should clearly document that this is not supported in Windows GA for 1.14.
thanks for the update. we will wait to hear back from
Currently, is got from docker's stats API on Windows. From docker stats API , only is available, hence is not set on Windows: Do you know any way to get instantaneous for Windows containers?
I have no idea. any idea?
I think this is broader than just a Windows issue. Officially supported tools such as the kubernetes metrics-server expect the field, but custom CRIs that conform to the interfaces defined in the package are not given the liberty to return this value.
suggested previously to cache the stats temporarily and compute the stats using the diff. David, could you chime in on how this could be done? Yes, this was mentioned in the previous comments too. There are plans to transition those components off this field, but it's WIP. We are looking for a workaround in kubelet for now.
my biggest worry is that if we say this impacts the horizonal POD autoscaler, how is that passing in our end2end and conformance tests?
Do you test HPA? It's not part of conformance, and I doubt this is included in windows testing.
As to how this could be done, in and we could just add a in the struct, which we assign the previous CpuUsage metric for each container. Then, when we need to calculate the rate, we pass the previous CpuUsage along with the current one to , and calculate a rate based on the timestamp and values.
ListPodCPUAndMemoryStats() we could just add a map[string]*runtimeapi.CpuUsage in the criStatsProvider struct I've done some tinkering on this myself and I originally thought that it would be as simple as that. It gets much more complicated when you have to work in between the existing cAdvisor-based logic. I assume the intent is to cut it out entirely eventually, but the information passed through the CRI doesn't even come close to being so comprehensive. So far I've found that this approach fixes the problem for the "/stats/summary" api, but not necessarily for the other apis. In particular, "/stats/container" seems to be completely based on cAdvisor, being unimpacted by the changes we made to those two functions. Some monitoring tools and metrics scrapers rely on the "/stats/container" api for their metrics, which means it is insufficient to update one api without doing the other.
We don't need to fill in everything in the summary API, just "usageNanoCores". The "/stats/summary" api is the one used by the metrics server, which is why we care about it in this case. The "/stats/container" isn't something we need to implement to support this.
we a couple of tickets to validate if HPA for Windows containers works. My guess is that it works for memory and not for CPU metrics because of this issue. If this is complicated to fix, i wonder if waiting for the CRI containerD changes in windows would be the best option for supporting this.
containerd and cri-o bypass this issue by leveraging cadvisor as a temporary solution. I don't think that'd work for windows.
Sorry the for late response. HPA is actually working for Windows containers. e.g. in my cluster (v1.12.5), cpu-based HPA is working as expected: Which version of kubernetes are you referring for HPA issues?
are you running heapster, or the metrics server to serve HPA? Heapster uses the cumulative metric, but the metrics-server uses the 10 average rate metric.
metrics-server is used in my cluster.
See .
/milestone v1.14

if stats.Cpu.UsageCoreNanoSeconds != nil { result.CPU.UsageCoreNanoSeconds = &stats.Cpu.UsageCoreNanoSeconds.Value } <ins> usageNanoCores := p.getContainerUsageNanoCores(stats) if usageNanoCores != nil { result.CPU.UsageNanoCores = usageNanoCores } </ins> } if stats.Memory != nil { result.Memory.Time = metav1.NewTime(time.Unix(0, stats.Memory.Timestamp))


Question:
Related: On Windows, kubelet reports only the cumulative for cpu usage. On Linux, kubelet reports both and the instantaneous . Although In the future, most components/monitoring pipelines will switch to using the cumulative metrics, a few features still depend on the instantaneous metrics today. Examples are: , HPA/VPA. Kubelet should report this metrics on Windows to support the existing features. /cc who explained to me what features depend on the cpu metrics. /cc /cc
- is this something that's clear enough in the CRI layer that you can implement it, or do we need to fix that first?
/assign
do you have any notes or a doc you can point to that better describes what features depend on which metrics? It would be good for us to share and see if anything other than is broken
The horizontal and vertical pod autoscalers also depend on the
Documentation on metrics API and metrics server (i.e., the aggregator): The metrics-server pod keeps spewing errors like this: Running : I haven't verified whether pod autoscaling works in my cluster, but I assume they won't since metrics server seems to discard the metrics from the windows pods. I believe the implementation is in kubelet (for the docker integration), so this should not need CRI changes.
I think this is generally an issue for non-Docker CRIs (not necessarily Windows-exclusive). The kubelet source code suggests that these metrics will be gathered from the CRI (if the CRI is not Docker). The struct that kubelet expects returned from the ContainerStats RPC does not include usageNanoCores. Does this mean that, until this is resolved, custom CRIs are unable to satisfactorily report metrics to the 'metrics-server'?
- are you able to work on this?
that is a good point. For CRI runtimes, the kubelet should calculate the average over 10s to produce this metric.
Good point. We designed CRI around core metrics API, but some CRI runtimes have integrated with cadvisor directly to fill the gap while we wait for core metrics API. I think it's reasonable for kubelet to do this on behalf of all CRI runtimes. I spoke to offline, and this would probably require no more than 2 days of work. If sig-windows (e.g., can pick this up, that'd be great. has agreed to review the changes (thanks!) If not, we should clearly document that this is not supported in Windows GA for 1.14.
thanks for the update. we will wait to hear back from
Currently, is got from docker's stats API on Windows. From docker stats API , only is available, hence is not set on Windows: Do you know any way to get instantaneous for Windows containers?
I have no idea. any idea?
I think this is broader than just a Windows issue. Officially supported tools such as the kubernetes metrics-server expect the field, but custom CRIs that conform to the interfaces defined in the package are not given the liberty to return this value.
suggested previously to cache the stats temporarily and compute the stats using the diff. David, could you chime in on how this could be done? Yes, this was mentioned in the previous comments too. There are plans to transition those components off this field, but it's WIP. We are looking for a workaround in kubelet for now.
my biggest worry is that if we say this impacts the horizonal POD autoscaler, how is that passing in our end2end and conformance tests?
Do you test HPA? It's not part of conformance, and I doubt this is included in windows testing.
As to how this could be done, in and we could just add a in the struct, which we assign the previous CpuUsage metric for each container. Then, when we need to calculate the rate, we pass the previous CpuUsage along with the current one to , and calculate a rate based on the timestamp and values.
ListPodCPUAndMemoryStats() we could just add a map[string]*runtimeapi.CpuUsage in the criStatsProvider struct I've done some tinkering on this myself and I originally thought that it would be as simple as that. It gets much more complicated when you have to work in between the existing cAdvisor-based logic. I assume the intent is to cut it out entirely eventually, but the information passed through the CRI doesn't even come close to being so comprehensive. So far I've found that this approach fixes the problem for the "/stats/summary" api, but not necessarily for the other apis. In particular, "/stats/container" seems to be completely based on cAdvisor, being unimpacted by the changes we made to those two functions. Some monitoring tools and metrics scrapers rely on the "/stats/container" api for their metrics, which means it is insufficient to update one api without doing the other.
We don't need to fill in everything in the summary API, just "usageNanoCores". The "/stats/summary" api is the one used by the metrics server, which is why we care about it in this case. The "/stats/container" isn't something we need to implement to support this.
we a couple of tickets to validate if HPA for Windows containers works. My guess is that it works for memory and not for CPU metrics because of this issue. If this is complicated to fix, i wonder if waiting for the CRI containerD changes in windows would be the best option for supporting this.
containerd and cri-o bypass this issue by leveraging cadvisor as a temporary solution. I don't think that'd work for windows.
Sorry the for late response. HPA is actually working for Windows containers. e.g. in my cluster (v1.12.5), cpu-based HPA is working as expected: Which version of kubernetes are you referring for HPA issues?
are you running heapster, or the metrics server to serve HPA? Heapster uses the cumulative metric, but the metrics-server uses the 10 average rate metric.
metrics-server is used in my cluster.
See .
/milestone v1.14

return result } <ins> // getContainerUsageNanoCores gets usageNanoCores based on cached usageCoreNanoSeconds. func (p *criStatsProvider) getContainerUsageNanoCores(stats *runtimeapi.ContainerStats) *uint64 { if stats == nil || stats.Cpu == nil || stats.Cpu.UsageCoreNanoSeconds == nil { return nil } p.mutex.Lock() defer func() { // Update cache with new value. p.cpuUsageCache[stats.Attributes.Id] = stats.Cpu p.mutex.Unlock() }() cached, ok := p.cpuUsageCache[stats.Attributes.Id] if !ok || cached.UsageCoreNanoSeconds == nil { return nil } nanoSeconds := stats.Cpu.Timestamp - cached.Timestamp usageNanoCores := (stats.Cpu.UsageCoreNanoSeconds.Value - cached.UsageCoreNanoSeconds.Value) * uint64(time.Second/time.Nanosecond) / uint64(nanoSeconds) return &usageNanoCores } func (p *criStatsProvider) cleanupOutdatedCaches() { p.mutex.Lock() defer p.mutex.Unlock() for k, v := range p.cpuUsageCache { if v == nil { delete(p.cpuUsageCache, k) } if time.Since(time.Unix(0, v.Timestamp)) > defaultCachePeriod { delete(p.cpuUsageCache, k) } } } </ins> // removeTerminatedContainer returns the specified container but with // the stats of the terminated containers removed. func removeTerminatedContainer(containers []*runtimeapi.Container) []*runtimeapi.Container {


Question:
Related: On Windows, kubelet reports only the cumulative for cpu usage. On Linux, kubelet reports both and the instantaneous . Although In the future, most components/monitoring pipelines will switch to using the cumulative metrics, a few features still depend on the instantaneous metrics today. Examples are: , HPA/VPA. Kubelet should report this metrics on Windows to support the existing features. /cc who explained to me what features depend on the cpu metrics. /cc /cc
- is this something that's clear enough in the CRI layer that you can implement it, or do we need to fix that first?
/assign
do you have any notes or a doc you can point to that better describes what features depend on which metrics? It would be good for us to share and see if anything other than is broken
The horizontal and vertical pod autoscalers also depend on the
Documentation on metrics API and metrics server (i.e., the aggregator): The metrics-server pod keeps spewing errors like this: Running : I haven't verified whether pod autoscaling works in my cluster, but I assume they won't since metrics server seems to discard the metrics from the windows pods. I believe the implementation is in kubelet (for the docker integration), so this should not need CRI changes.
I think this is generally an issue for non-Docker CRIs (not necessarily Windows-exclusive). The kubelet source code suggests that these metrics will be gathered from the CRI (if the CRI is not Docker). The struct that kubelet expects returned from the ContainerStats RPC does not include usageNanoCores. Does this mean that, until this is resolved, custom CRIs are unable to satisfactorily report metrics to the 'metrics-server'?
- are you able to work on this?
that is a good point. For CRI runtimes, the kubelet should calculate the average over 10s to produce this metric.
Good point. We designed CRI around core metrics API, but some CRI runtimes have integrated with cadvisor directly to fill the gap while we wait for core metrics API. I think it's reasonable for kubelet to do this on behalf of all CRI runtimes. I spoke to offline, and this would probably require no more than 2 days of work. If sig-windows (e.g., can pick this up, that'd be great. has agreed to review the changes (thanks!) If not, we should clearly document that this is not supported in Windows GA for 1.14.
thanks for the update. we will wait to hear back from
Currently, is got from docker's stats API on Windows. From docker stats API , only is available, hence is not set on Windows: Do you know any way to get instantaneous for Windows containers?
I have no idea. any idea?
I think this is broader than just a Windows issue. Officially supported tools such as the kubernetes metrics-server expect the field, but custom CRIs that conform to the interfaces defined in the package are not given the liberty to return this value.
suggested previously to cache the stats temporarily and compute the stats using the diff. David, could you chime in on how this could be done? Yes, this was mentioned in the previous comments too. There are plans to transition those components off this field, but it's WIP. We are looking for a workaround in kubelet for now.
my biggest worry is that if we say this impacts the horizonal POD autoscaler, how is that passing in our end2end and conformance tests?
Do you test HPA? It's not part of conformance, and I doubt this is included in windows testing.
As to how this could be done, in and we could just add a in the struct, which we assign the previous CpuUsage metric for each container. Then, when we need to calculate the rate, we pass the previous CpuUsage along with the current one to , and calculate a rate based on the timestamp and values.
ListPodCPUAndMemoryStats() we could just add a map[string]*runtimeapi.CpuUsage in the criStatsProvider struct I've done some tinkering on this myself and I originally thought that it would be as simple as that. It gets much more complicated when you have to work in between the existing cAdvisor-based logic. I assume the intent is to cut it out entirely eventually, but the information passed through the CRI doesn't even come close to being so comprehensive. So far I've found that this approach fixes the problem for the "/stats/summary" api, but not necessarily for the other apis. In particular, "/stats/container" seems to be completely based on cAdvisor, being unimpacted by the changes we made to those two functions. Some monitoring tools and metrics scrapers rely on the "/stats/container" api for their metrics, which means it is insufficient to update one api without doing the other.
We don't need to fill in everything in the summary API, just "usageNanoCores". The "/stats/summary" api is the one used by the metrics server, which is why we care about it in this case. The "/stats/container" isn't something we need to implement to support this.
we a couple of tickets to validate if HPA for Windows containers works. My guess is that it works for memory and not for CPU metrics because of this issue. If this is complicated to fix, i wonder if waiting for the CRI containerD changes in windows would be the best option for supporting this.
containerd and cri-o bypass this issue by leveraging cadvisor as a temporary solution. I don't think that'd work for windows.
Sorry the for late response. HPA is actually working for Windows containers. e.g. in my cluster (v1.12.5), cpu-based HPA is working as expected: Which version of kubernetes are you referring for HPA issues?
are you running heapster, or the metrics server to serve HPA? Heapster uses the cumulative metric, but the metrics-server uses the 10 average rate metric.
metrics-server is used in my cluster.
See .
/milestone v1.14

m.InodesUsed = resource.NewQuantity(int64(seed+offsetInodeUsage), resource.BinarySI) return m } <ins> func TestGetContainerUsageNanoCores(t *testing.T) { var value0 uint64 var value1 uint64 = 10000000000 tests := []struct { desc          string cpuUsageCache map[string]*runtimeapi.CpuUsage stats         *runtimeapi.ContainerStats expected      *uint64 }{ { desc:          "should return nil if stats is nil", cpuUsageCache: map[string]*runtimeapi.CpuUsage{}, }, { desc:          "should return nil if cpu stats is nil", cpuUsageCache: map[string]*runtimeapi.CpuUsage{}, stats: &runtimeapi.ContainerStats{ Attributes: &runtimeapi.ContainerAttributes{ Id: "1", }, Cpu: nil, }, }, { desc:          "should return nil if usageCoreNanoSeconds is nil", cpuUsageCache: map[string]*runtimeapi.CpuUsage{}, stats: &runtimeapi.ContainerStats{ Attributes: &runtimeapi.ContainerAttributes{ Id: "1", }, Cpu: &runtimeapi.CpuUsage{ Timestamp:            1, UsageCoreNanoSeconds: nil, }, }, }, { desc:          "should return nil if cpu stats is not cached yet", cpuUsageCache: map[string]*runtimeapi.CpuUsage{}, stats: &runtimeapi.ContainerStats{ Attributes: &runtimeapi.ContainerAttributes{ Id: "1", }, Cpu: &runtimeapi.CpuUsage{ Timestamp: 1, UsageCoreNanoSeconds: &runtimeapi.UInt64Value{ Value: 10000000000, }, }, }, }, { desc: "should return zero value if cached cpu stats is equal to current value", stats: &runtimeapi.ContainerStats{ Attributes: &runtimeapi.ContainerAttributes{ Id: "1", }, Cpu: &runtimeapi.CpuUsage{ Timestamp: 1, UsageCoreNanoSeconds: &runtimeapi.UInt64Value{ Value: 10000000000, }, }, }, cpuUsageCache: map[string]*runtimeapi.CpuUsage{ "1": { Timestamp: 0, UsageCoreNanoSeconds: &runtimeapi.UInt64Value{ Value: 10000000000, }, }, }, expected: &value0, }, { desc: "should return correct value if cached cpu stats is not equal to current value", stats: &runtimeapi.ContainerStats{ Attributes: &runtimeapi.ContainerAttributes{ Id: "1", }, Cpu: &runtimeapi.CpuUsage{ Timestamp: int64(time.Second / time.Nanosecond), UsageCoreNanoSeconds: &runtimeapi.UInt64Value{ Value: 20000000000, }, }, }, cpuUsageCache: map[string]*runtimeapi.CpuUsage{ "1": { Timestamp: 0, UsageCoreNanoSeconds: &runtimeapi.UInt64Value{ Value: 10000000000, }, }, }, expected: &value1, }, } for _, test := range tests { provider := &criStatsProvider{cpuUsageCache: test.cpuUsageCache} real := provider.getContainerUsageNanoCores(test.stats) assert.Equal(t, test.expected, real, test.desc) } } </ins>


Question:
<!-- Please use this template while reporting a bug and provide as much info as possible. Not doing so may result in your bug not being addressed in a timely manner. Thanks!--What happened: I configured Kubelet to run as a service on Windows, with a setting to restart on failure (). I noticed that it restarts even when I explicitly stop the service with , even though the documentation states the following (I left it at , the default): What you expected to happen: I expected the Kubelet to only restart when killed unexpectedly, per above docs. Anything else we need to know?: I think the problem might be due to this part of our service control integration, but I'm not really sure: It looks like we send and then , but the official golang example sends and just returns without exiting. (). Is this difference meaningful? Kubernetes version (use ): 1.13.2 Cloud provider or hardware configuration: GCE OS (e.g. from /etc/os-release): Windows /cc /sig node /sig windows
The same should apply to kube-proxy as well.
i believe you implemented this functionality. can you please take a look? cc:

importpath = "k8s.io/kubernetes/pkg/windows/service", deps = select({ "@io_bazel_rules_go//go/platform:windows": [ <ins> "//staging/src/k8s.io/apiserver/pkg/server:go_default_library", </ins> "//vendor/golang.org/x/sys/windows:go_default_library", "//vendor/golang.org/x/sys/windows/svc:go_default_library", "//vendor/k8s.io/klog:go_default_library",


Question:
<!-- Please use this template while reporting a bug and provide as much info as possible. Not doing so may result in your bug not being addressed in a timely manner. Thanks!--What happened: I configured Kubelet to run as a service on Windows, with a setting to restart on failure (). I noticed that it restarts even when I explicitly stop the service with , even though the documentation states the following (I left it at , the default): What you expected to happen: I expected the Kubelet to only restart when killed unexpectedly, per above docs. Anything else we need to know?: I think the problem might be due to this part of our service control integration, but I'm not really sure: It looks like we send and then , but the official golang example sends and just returns without exiting. (). Is this difference meaningful? Kubernetes version (use ): 1.13.2 Cloud provider or hardware configuration: GCE OS (e.g. from /etc/os-release): Windows /cc /sig node /sig windows
The same should apply to kube-proxy as well.
i believe you implemented this functionality. can you please take a look? cc:

import ( "os" <ins> "time" "k8s.io/apiserver/pkg/server" </ins> "k8s.io/klog" "golang.org/x/sys/windows"


Question:
<!-- Please use this template while reporting a bug and provide as much info as possible. Not doing so may result in your bug not being addressed in a timely manner. Thanks!--What happened: I configured Kubelet to run as a service on Windows, with a setting to restart on failure (). I noticed that it restarts even when I explicitly stop the service with , even though the documentation states the following (I left it at , the default): What you expected to happen: I expected the Kubelet to only restart when killed unexpectedly, per above docs. Anything else we need to know?: I think the problem might be due to this part of our service control integration, but I'm not really sure: It looks like we send and then , but the official golang example sends and just returns without exiting. (). Is this difference meaningful? Kubernetes version (use ): 1.13.2 Cloud provider or hardware configuration: GCE OS (e.g. from /etc/os-release): Windows /cc /sig node /sig windows
The same should apply to kube-proxy as well.
i believe you implemented this functionality. can you please take a look? cc:

case svc.Interrogate: s <- c.CurrentStatus case svc.Stop, svc.Shutdown: <del> s <- svc.Status{State: svc.Stopped} // TODO: Stop the kubelet gracefully instead of killing the process os.Exit(0) </del> <ins> klog.Infof("Service stopping") // We need to translate this request into a signal that can be handled by the the signal handler // handling shutdowns normally (currently apiserver/pkg/server/signal.go). // If we do not do this, our main threads won't be notified of the upcoming shutdown. // Since Windows services do not use any console, we cannot simply generate a CTRL_BREAK_EVENT // but need a dedicated notification mechanism. graceful := server.RequestShutdown() // Free up the control handler and let us terminate as gracefully as possible. // If that takes too long, the service controller will kill the remaining threads. // As per https://docs.microsoft.com/en-us/windows/desktop/services/service-control-handler-function s <- svc.Status{State: svc.StopPending} // If we cannot exit gracefully, we really only can exit our process, so atleast the // service manager will think that we gracefully exited. At the time of writing this comment this is // needed for applications that do not use signals (e.g. kube-proxy) if !graceful { go func() { // Ensure the SCM was notified (The operation above (send to s) was received and communicated to the // service control manager - so it doesn't look like the service crashes) time.Sleep(1 * time.Second) os.Exit(0) }() } break Loop </ins> } } }


Question:
<!-- Please use this template while reporting a bug and provide as much info as possible. Not doing so may result in your bug not being addressed in a timely manner. Thanks!--What happened: I configured Kubelet to run as a service on Windows, with a setting to restart on failure (). I noticed that it restarts even when I explicitly stop the service with , even though the documentation states the following (I left it at , the default): What you expected to happen: I expected the Kubelet to only restart when killed unexpectedly, per above docs. Anything else we need to know?: I think the problem might be due to this part of our service control integration, but I'm not really sure: It looks like we send and then , but the official golang example sends and just returns without exiting. (). Is this difference meaningful? Kubernetes version (use ): 1.13.2 Cloud provider or hardware configuration: GCE OS (e.g. from /etc/os-release): Windows /cc /sig node /sig windows
The same should apply to kube-proxy as well.
i believe you implemented this functionality. can you please take a look? cc:

) var onlyOneSignalHandler = make(chan struct{}) <ins> var shutdownHandler chan os.Signal </ins> // SetupSignalHandler registered for SIGTERM and SIGINT. A stop channel is returned // which is closed on one of these signals. If a second signal is caught, the program


Question:
<!-- Please use this template while reporting a bug and provide as much info as possible. Not doing so may result in your bug not being addressed in a timely manner. Thanks!--What happened: I configured Kubelet to run as a service on Windows, with a setting to restart on failure (). I noticed that it restarts even when I explicitly stop the service with , even though the documentation states the following (I left it at , the default): What you expected to happen: I expected the Kubelet to only restart when killed unexpectedly, per above docs. Anything else we need to know?: I think the problem might be due to this part of our service control integration, but I'm not really sure: It looks like we send and then , but the official golang example sends and just returns without exiting. (). Is this difference meaningful? Kubernetes version (use ): 1.13.2 Cloud provider or hardware configuration: GCE OS (e.g. from /etc/os-release): Windows /cc /sig node /sig windows
The same should apply to kube-proxy as well.
i believe you implemented this functionality. can you please take a look? cc:

func SetupSignalHandler() <-chan struct{} { close(onlyOneSignalHandler) // panics when called twice <ins> shutdownHandler = make(chan os.Signal, 2) </ins> stop := make(chan struct{}) <del> c := make(chan os.Signal, 2) signal.Notify(c, shutdownSignals...) </del> <ins> signal.Notify(shutdownHandler, shutdownSignals...) </ins> go func() { <del> <-c </del> <ins> <-shutdownHandler </ins> close(stop) <del> <-c </del> <ins> <-shutdownHandler </ins> os.Exit(1) // second signal. Exit directly. }() return stop } <ins> // RequestShutdown emulates a received event that is considered as shutdown signal (SIGTERM/SIGINT) // This returns whether a handler was notified func RequestShutdown() bool { if shutdownHandler != nil { select { case shutdownHandler <- shutdownSignals[0]: return true default: } } return false } </ins>


Question:
We merged to allow configurable volume limits for Cinder. But proposed adding such a limit to as well, among other things this will enable us to support node specific limits more easily - /sig openstack /sig storage /sig scheduling
/assign
cc
/kind feature
This will require updating in-tree Openstack cloudprovider code. are we onboard with that?
What would be the extent of the modification? It must not break current compatibility, and the in-tree provider is scheduled for removal this year. I'm ok with it as long as existing users aren't broken by it.
it should be a change into which would add a new configurable field. It would be backward compatible but would allow admins to configure different limits on a node if they must.
/milestone v1.14 We're entering and this looks relevant to the 1.14 release. Please if I am incorrect

// BlockStorageOpts is used to talk to Cinder service type BlockStorageOpts struct { <del> BSVersion       string `gcfg:"bs-version"`        // overrides autodetection. v1 or v2. Defaults to auto TrustDevicePath bool   `gcfg:"trust-device-path"` // See Issue #33128 IgnoreVolumeAZ  bool   `gcfg:"ignore-volume-az"` </del> <ins> BSVersion             string `gcfg:"bs-version"`        // overrides autodetection. v1 or v2. Defaults to auto TrustDevicePath       bool   `gcfg:"trust-device-path"` // See Issue #33128 IgnoreVolumeAZ        bool   `gcfg:"ignore-volume-az"` NodeVolumeAttachLimit int    `gcfg:"node-volume-attach-limit"` // override volume attach limit for Cinder. Default is : 256 </ins> } // RouterOpts is used for Neutron routes


Question:
We merged to allow configurable volume limits for Cinder. But proposed adding such a limit to as well, among other things this will enable us to support node specific limits more easily - /sig openstack /sig storage /sig scheduling
/assign
cc
/kind feature
This will require updating in-tree Openstack cloudprovider code. are we onboard with that?
What would be the extent of the modification? It must not break current compatibility, and the in-tree provider is scheduled for removal this year. I'm ok with it as long as existing users aren't broken by it.
it should be a change into which would add a new configurable field. It would be backward compatible but would allow admins to configure different limits on a node if they must.
/milestone v1.14 We're entering and this looks relevant to the 1.14 release. Please if I am incorrect

return &os, nil } <ins> // NewFakeOpenStackCloud creates and returns an instance of Openstack cloudprovider. // Mainly for use in tests that require instantiating Openstack without having // to go through cloudprovider interface. func NewFakeOpenStackCloud(cfg Config) (*OpenStack, error) { provider, err := openstack.NewClient(cfg.Global.AuthURL) if err != nil { return nil, err } emptyDuration := MyDuration{} if cfg.Metadata.RequestTimeout == emptyDuration { cfg.Metadata.RequestTimeout.Duration = time.Duration(defaultTimeOut) } provider.HTTPClient.Timeout = cfg.Metadata.RequestTimeout.Duration os := OpenStack{ provider:     provider, region:       cfg.Global.Region, lbOpts:       cfg.LoadBalancer, bsOpts:       cfg.BlockStorage, routeOpts:    cfg.Route, metadataOpts: cfg.Metadata, } return &os, nil } </ins> // Initialize passes a Kubernetes clientBuilder interface to the cloud provider func (os *OpenStack) Initialize(clientBuilder cloudprovider.ControllerClientBuilder, stop <-chan struct{}) { }


Question:
We merged to allow configurable volume limits for Cinder. But proposed adding such a limit to as well, among other things this will enable us to support node specific limits more easily - /sig openstack /sig storage /sig scheduling
/assign
cc
/kind feature
This will require updating in-tree Openstack cloudprovider code. are we onboard with that?
What would be the extent of the modification? It must not break current compatibility, and the in-tree provider is scheduled for removal this year. I'm ok with it as long as existing users aren't broken by it.
it should be a change into which would add a new configurable field. It would be backward compatible but would allow admins to configure different limits on a node if they must.
/milestone v1.14 We're entering and this looks relevant to the 1.14 release. Please if I am incorrect

return os.bsOpts.TrustDevicePath } <ins> // NodeVolumeAttachLimit specifies number of cinder volumes that can be attached to this node. func (os *OpenStack) NodeVolumeAttachLimit() int { return os.bsOpts.NodeVolumeAttachLimit } </ins> // GetLabelsForVolume implements PVLabeler.GetLabelsForVolume func (os *OpenStack) GetLabelsForVolume(ctx context.Context, pv *v1.PersistentVolume) (map[string]string, error) { // Ignore if not Cinder.


Question:
We merged to allow configurable volume limits for Cinder. But proposed adding such a limit to as well, among other things this will enable us to support node specific limits more easily - /sig openstack /sig storage /sig scheduling
/assign
cc
/kind feature
This will require updating in-tree Openstack cloudprovider code. are we onboard with that?
What would be the extent of the modification? It must not break current compatibility, and the in-tree provider is scheduled for removal this year. I'm ok with it as long as existing users aren't broken by it.
it should be a change into which would add a new configurable field. It would be backward compatible but would allow admins to configure different limits on a node if they must.
/milestone v1.14 We're entering and this looks relevant to the 1.14 release. Please if I am incorrect

], embed = [":go_default_library"], deps = [ <ins> "//pkg/cloudprovider/providers/openstack:go_default_library", </ins> "//pkg/util/mount:go_default_library", "//pkg/volume:go_default_library", "//pkg/volume/testing:go_default_library", <ins> "//pkg/volume/util:go_default_library", </ins> "//staging/src/k8s.io/api/core/v1:go_default_library", "//staging/src/k8s.io/apimachinery/pkg/api/resource:go_default_library", "//staging/src/k8s.io/apimachinery/pkg/apis/meta/v1:go_default_library",


Question:
We merged to allow configurable volume limits for Cinder. But proposed adding such a limit to as well, among other things this will enable us to support node specific limits more easily - /sig openstack /sig storage /sig scheduling
/assign
cc
/kind feature
This will require updating in-tree Openstack cloudprovider code. are we onboard with that?
What would be the extent of the modification? It must not break current compatibility, and the in-tree provider is scheduled for removal this year. I'm ok with it as long as existing users aren't broken by it.
it should be a change into which would add a new configurable field. It would be backward compatible but would allow admins to configure different limits on a node if they must.
/milestone v1.14 We're entering and this looks relevant to the 1.14 release. Please if I am incorrect

if cloud.ProviderName() != openstack.ProviderName { return nil, fmt.Errorf("Expected Openstack cloud, found %s", cloud.ProviderName()) } <ins> openstackCloud, ok := cloud.(*openstack.OpenStack) if ok && openstackCloud.NodeVolumeAttachLimit() > 0 { volumeLimits[util.CinderVolumeLimitKey] = int64(openstackCloud.NodeVolumeAttachLimit()) } </ins> return volumeLimits, nil }


Question:
We merged to allow configurable volume limits for Cinder. But proposed adding such a limit to as well, among other things this will enable us to support node specific limits more easily - /sig openstack /sig storage /sig scheduling
/assign
cc
/kind feature
This will require updating in-tree Openstack cloudprovider code. are we onboard with that?
What would be the extent of the modification? It must not break current compatibility, and the in-tree provider is scheduled for removal this year. I'm ok with it as long as existing users aren't broken by it.
it should be a change into which would add a new configurable field. It would be backward compatible but would allow admins to configure different limits on a node if they must.
/milestone v1.14 We're entering and this looks relevant to the 1.14 release. Please if I am incorrect

"k8s.io/api/core/v1" "k8s.io/apimachinery/pkg/types" utiltesting "k8s.io/client-go/util/testing" <ins> "k8s.io/kubernetes/pkg/cloudprovider/providers/openstack" </ins> "k8s.io/kubernetes/pkg/util/mount" "k8s.io/kubernetes/pkg/volume" volumetest "k8s.io/kubernetes/pkg/volume/testing" <ins> "k8s.io/kubernetes/pkg/volume/util" </ins> ) func TestCanSupport(t *testing.T) {