- Move from the old github.com/golang/glog to k8s.io/klog
- klog as explicit InitFlags() so we add them as necessary
- we update the other repositories that we vendor that made a similar
change from glog to klog
* github.com/kubernetes/repo-infra
* k8s.io/gengo/
* k8s.io/kube-openapi/
* github.com/google/cadvisor
- Entirely remove all references to glog
- Fix some tests by explicit InitFlags in their init() methods
Change-Id: I92db545ff36fcec83afe98f550c9e630098b3135
After my previous changes HPA wasn't behaving correctly in the following
situation:
- Pods use a lot of CPU during initilization, become ready right after they initialize,
- Scale up triggers,
- When new pods become ready HPA counts their usage (even though it's not related to any work that needs doing),
- Another scale up, even though existing pods can handle work, no problem.
This updates the HPA controller to use the polymorphic scale client from
client-go. This should enable HPAs to work with arbitrary scalable
resources, instead of just those in the extensions API group (meaning we
can deprecate the copy of ReplicationController in extensions/v1beta1).
It also means that the HPA controller now pays attention to the
APIVersion field in `scaleTargetRef` (more specifically, the group part
of it).
Note that currently, discovery information on which resources are
available where is only fetched once (the first time that it's
requested). In the future, we may want a refreshing discovery REST
mapper.
Automatic merge from submit-queue (batch tested with PRs 51956, 50708)
Move autoscaling/v2 from alpha1 to beta1
This graduates autoscaling/v2alpha1 to autoscaling/v2beta1. The move is more-or-less just a straightforward rename.
Part of kubernetes/features#117
```release-note
v2 of the autoscaling API group, including improvements to the HorizontalPodAutoscaler, has moved from alpha1 to beta1.
```
This commit only sends updates if the status has actually changed.
Since the HPA runs at a regular interval, this should reduce the volume
of writes, especially on short HPA intervals with relatively constant
metrics.
Since the HPA controller pulls information from an external source that
makes no guarantees about consistency, it's possible for the HPA
to get into an infinite update loop -- if the metrics change with
every query, the HPA controller will run it's normal reconcilation,
post a status update, see that status update itself, fetch new metrics,
and if those metrics are different, post another status update, and
repeat. This can lead to continuously updating a single HPA.
By rate-limiting each HPA to once per sync interval, we prevent this
from happening.
This commit switches over the HPA controller to use the custom metrics
API. It also converts the HPA controller to use the generated client
in k8s.io/metrics for the resource metrics API.
In order to enable support, you must enable
`--horizontal-pod-autoscaler-use-rest-clients` on the
controller-manager, which will switch the HPA controller's MetricsClient
implementation over to use the standard rest clients for both custom
metrics and resource metrics. This requires that at the least resource
metrics API is registered with kube-aggregator, and that the controller
manager is pointed at kube-aggregator. For this to work, Heapster
must be serving the new-style API server (`--api-server=true`).
This commit converts the HPA controller over to using the new version of
the HorizontalPodAutoscaler object found in autoscaling/v2alpha1. Note
that while the autoscaler will accept requests for object metrics, the
scale client will return an error on attempts to get object metrics
(since that requires the new custom metrics API, which is not yet
implemented).
This also enables the HPA object in v2alpha1 as a retrievable API
version by default.
stewart-yu