If a CRI error occurs during the terminating phase after a pod is
force deleted (API or static) then the housekeeping loop will not
deliver updates to the pod worker which prevents the pod's state
machine from progressing. The pod will remain in the terminating
phase but no further attempts to terminate or cleanup will occur
until the kubelet is restarted.
The pod worker now maintains a store of the pods state that it is
attempting to reconcile and uses that to resync unknown pods when
SyncKnownPods() is invoked, so that failures in sync methods for
unknown pods no longer hang forever.
The pod worker's store tracks desired updates and the last update
applied on podSyncStatuses. Each goroutine now synchronizes to
acquire the next work item, context, and whether the pod can start.
This synchronization moves the pending update to the stored last
update, which will ensure third parties accessing pod worker state
don't see updates before the pod worker begins synchronizing them.
As a consequence, the update channel becomes a simple notifier
(struct{}) so that SyncKnownPods can coordinate with the pod worker
to create a synthetic pending update for unknown pods (i.e. no one
besides the pod worker has data about those pods). Otherwise the
pending update info would be hidden inside the channel.
In order to properly track pending updates, we have to be very
careful not to mix RunningPods (which are calculated from the
container runtime and are missing all spec info) and config-
sourced pods. Update the pod worker to avoid using ToAPIPod()
and instead require the pod worker to directly use
update.Options.Pod or update.Options.RunningPod for the
correct methods. Add a new SyncTerminatingRuntimePod to prevent
accidental invocations of runtime only pod data.
Finally, fix SyncKnownPods to replay the last valid update for
undesired pods which drives the pod state machine towards
termination, and alter HandlePodCleanups to:
- terminate runtime pods that aren't known to the pod worker
- launch admitted pods that aren't known to the pod worker
Any started pods receive a replay until they reach the finished
state, and then are removed from the pod worker. When a desired
pod is detected as not being in the worker, the usual cause is
that the pod was deleted and recreated with the same UID (almost
always a static pod since API UID reuse is statistically
unlikely). This simplifies the previous restartable pod support.
We are careful to filter for active pods (those not already
terminal or those which have been previously rejected by
admission). We also force a refresh of the runtime cache to
ensure we don't see an older version of the state.
Future changes will allow other components that need to view the
pod worker's actual state (not the desired state the podManager
represents) to retrieve that info from the pod worker.
Several bugs in pod lifecycle have been undetectable at runtime
because the kubelet does not clearly describe the number of pods
in use. To better report, add the following metrics:
kubelet_desired_pods: Pods the pod manager sees
kubelet_active_pods: "Admitted" pods that gate new pods
kubelet_mirror_pods: Mirror pods the kubelet is tracking
kubelet_working_pods: Breakdown of pods from the last sync in
each phase, orphaned state, and static or not
kubelet_restarted_pods_total: A counter for pods that saw a
CREATE before the previous pod with the same UID was finished
kubelet_orphaned_runtime_pods_total: A counter for pods detected
at runtime that were not known to the kubelet. Will be
populated at Kubelet startup and should never be incremented
after.
Add a metric check to our e2e tests that verifies the values are
captured correctly during a serial test, and then verify them in
detail in unit tests.
Adds 23 series to the kubelet /metrics endpoint.
Add node e2e test to verify that static pods can be started after a
previous static pod with the same config temporarily failed termination.
The scenario is:
1. Static pod is started
2. Static pod is deleted
3. Static pod termination fails (internally `syncTerminatedPod` fails)
4. At later time, pod termination should succeed
5. New static pod with the same config is (re)-added
6. New static pod is expected to start successfully
To repro this scenario, setup a pod using a NFS mount. The NFS server is
stopped which will result in volumes failing to unmount and
`syncTerminatedPod` to fail. The NFS server is later started, allowing
the volume to unmount successfully.
xref:
1. https://github.com/kubernetes/kubernetes/pull/113145#issuecomment-1289587988
2. https://github.com/kubernetes/kubernetes/pull/113065
3. https://github.com/kubernetes/kubernetes/pull/113093
Signed-off-by: David Porter <david@porter.me>
Add a node e2e to verify that if a static pod is terminated while the
container runtime or CRI returns an error, the pod is eventually
terminated successfully.
This test serves as a regression test for k8s.io/issue/113145 which
fixes an issue where force deleted pods may not be terminated if the
container runtime fails during a `syncTerminatingPod`.
To test this behavior, start a static pod, stop the container runtime,
and later start the container runtime. The static pod is expected to
eventually terminate successfully.
To start and stop the container runtime, we need to find the container
runtime systemd unit name. Introduce a util function
`findContainerRuntimeServiceName` which finds the unit name by getting
the pid of the container runtime from the existing
`ContainerRuntimeProcessName` flag passed into node e2e and using
systemd dbus `GetUnitNameByPID` function to convert the pid of the
container runtime to a unit name. Using the unit name, introduce helper
functions to start and stop the container runtime.
Signed-off-by: David Porter <david@porter.me>
Update github.com/coreos/go-systemd/v22 to v22.4.0 which introduces
`GetUnitNameByPID`. This function will be used in node e2e to get the
container runtime systemd unit name.
Performed by:
$ hack/pin-dependency.sh github.com/coreos/go-systemd/v22 v22.4.0
$ hack/update-vendor.sh
Signed-off-by: David Porter <david@porter.me>
Follow-up of:
- https://github.com/kubernetes/kubernetes/pull/115634
The current retention policy prevent creation or update of new objects
until the existing one are deleted based on the retention period.
Signed-off-by: Arnaud Meukam <ameukam@gmail.com>
This change helps users understand the state of their encryption
config if storage migration is not consistently run with key ID
rotation.
Signed-off-by: Monis Khan <mok@microsoft.com>
In order to implement the `full-pcpus-only` cpumanager policy option,
we leverage the implementation of the algorithm which picks CPUs.
By design, CPUs are taken from the biggest chunk available (socket
or NUMA zone) to physical cores, down to single cores.
Leveraging this, if the requested CPU count is a multiple of the SMT
level (commonly 2), we're guaranteed that only full physical cores
will be taken.
The hidden assumption here is this holds true by construction iff
the user reserved CPUs (if any) considering full physical CPUs.
IOW, if the user did intentionally or mistakely reserve single threads
which are no core siblings[1], then the simple check we implemented
is not sufficient.
A easy example can probably outline this better. With this setup:
cores: [(0, 4), (1, 5), (2, 6), (3, 8)] (in parens: thread siblings).
SMT level: 2 (each tuple is 2 elements)
Reserved CPUs: 0,1 (explicit pick using `--reserved-cpus`)
A container then requests 6 cpus. full-pcpus-only check: 6 % 2 == 0. Passed.
The CPU allocator will take first full cores, (2,6) and (3,8), and will
then pick the remaining single CPUs. The allocation will succeed, but
it's incorrect.
We can fix this case with a stricter precheck.
We need to additionally consider all the core siblings of the reserved
CPUs as unavailable when computing the free cpus, before to start the
actual allocation. Doing so, we fall back in the intended behavior, and
by construction all possible CPUs allocation whose number is multiple
of the SMT level are now correct again.
+++
[1] or thread siblings in the linux parlance, in any case:
hyperthread siblings of the same physical core
Signed-off-by: Francesco Romani <fromani@redhat.com>
Passing in a context instead of a stop channel has several advantages:
- ensures that client-go calls return as soon as the controller is asked to stop
- contextual logging can be used
By passing that context down to its own functions and checking it while
waiting, the lease controller also doesn't get stuck in backoffEnsureLease
anymore (https://github.com/kubernetes/kubernetes/issues/116196).
Update go-jose from v2.2.2 to v2.6.0.
This is to make the kubernetes code compatible with newer go-jose versions that have a small breaking change (`jwt.NewNumericDate()` returns a pointer).
Signed-off-by: Max Goltzsche <max.goltzsche@gmail.com>
