Currently, the HPA considers unready pods the same as ready pods when
looking at their CPU and custom metric usage. However, pods frequently
use extra CPU during initialization, so we want to consider them
separately.
This commit causes the HPA to consider unready pods as having 0 CPU
usage when scaling up, and ignores them when scaling down. If, when
scaling up, factoring the unready pods as having 0 CPU would cause a
downscale instead, we simply choose not to scale. Otherwise, we simply
scale up at the reduced amount caculated by factoring the pods in at
zero CPU usage.
The effect is that unready pods cause the autoscaler to be a bit more
conservative -- large increases in CPU usage can still cause scales,
even with unready pods in the mix, but will not cause the scale factors
to be as large, in anticipation of the new pods later becoming ready and
handling load.
Similarly, if there are pods for which no metrics have been retrieved,
these pods are treated as having 100% of the requested metric when
scaling down, and 0% when scaling up. As above, this cannot change the
direction of the scale.
This commit also changes the HPA to ignore superfluous metrics -- as
long as metrics for all ready pods are present, the HPA we make scaling
decisions. Currently, this only works for CPU. For custom metrics, we
cannot identify which metrics go to which pods if we get superfluous
metrics, so we abort the scale.
Automatic merge from submit-queue
Enable HPA controller based on autoscaling/v1 api group
ref #29778
``` release-note
Enable HPA controller based on autoscaling/v1 api group.
```
Automatic merge from submit-queue
lister-gen updates
- Remove "zz_generated." prefix from generated lister file names
- Add support for expansion interfaces
- Switch to new generated JobLister
@deads2k @liggitt @sttts @mikedanese @caesarxuchao for the lister-gen changes
@soltysh @deads2k for the informer / job controller changes
Automatic merge from submit-queue
convert SA controller to shared informers
convert the SA controller to shared informer + workqueue.
I think one of @derekwaynecarr @ncdc or @liggitt
Alter how runtime.SerializeInfo is represented to simplify negotiation
and reduce the need to allocate during negotiation. Simplify the dynamic
client's logic around negotiating type. Add more tests for media type
handling where necessary.
Automatic merge from submit-queue
Add ECDSA support for service account tokens
Fixes#28180
```release-note
ECDSA keys can now be used for signing and verifying service account tokens.
```
Automatic merge from submit-queue
Abstraction of endpoints in leaderelection code
**Problem Statement**:
Currently the Leader Election code is hard coded against the endpoints api. This causes performance issues on large scale clusters due to incessant iptables refreshes, see: https://github.com/kubernetes/kubernetes/issues/26637
The goal of this PR is to:
- Abstract Endpoints out of the leader election code
- Fix a known bug in the event recording
fixes#18386
**Special notes for your reviewer**:
This is a 1st pass at abstracting the details of endpoints out into an interface. Any suggestions around how we we want to refactor this interface is welcome and could be addressed in either this PR or follow on PR.
/cc @ncdc @wojtek-t @rrati
Automatic merge from submit-queue
Dynamic provisioning for flocker volume plugin
Refactor flocker volume plugin
* [x] Support provisioning beta (#29006)
* [x] Support deletion
* [x] Use bind mounts instead of /flocker in containers
* [x] support ownership management or SELinux relabeling.
* [x] adds volume specification via datasetUUID (this is guranted to be unique)
I based my refactor work to replicate pretty much GCE-PD behaviour
**Related issues**: #29006#26908
@jsafrane @mattbates @wallrj @wallnerryan
Dr. Stefan Schimanski