HPA will treat initial size of autoscalee to avoid hastily overriding
recomendations made by HPA (if HPA set size and then was restarted) or by user
(initial size should be treated as human-generated recommendation).
Automatic merge from submit-queue. If you want to cherry-pick this change to another branch, please follow the instructions here: https://github.com/kubernetes/community/blob/master/contributors/devel/cherry-picks.md.
Change CPU sample sanitization in HPA.
**What this PR does / why we need it**:
Change CPU sample sanitization in HPA.
Ignore samples if:
- Pod is beeing initalized - 5 minutes from start defined by flag
- pod is unready
- pod is ready but full window of metric hasn't been colected since
transition
- Pod is initialized - 5 minutes from start defined by flag:
- Pod has never been ready after initial readiness period.
**Release notes:**
```release-note
Improve CPU sample sanitization in HPA by taking metric's freshness into account.
```
Ignore samples if:
- Pod is beeing initalized - 5 minutes from start defined by flag
- pod is unready
- pod is ready but full window of metric hasn't been colected since
transition
- Pod is initialized - 5 minutes from start defined by flag:
- Pod has never been ready after initial readiness period.
Automatic merge from submit-queue (batch tested with PRs 67067, 67947). If you want to cherry-pick this change to another branch, please follow the instructions <a href="https://github.com/kubernetes/community/blob/master/contributors/devel/cherry-picks.md">here</a>.
Do not count soft-deleted pods for scaling purposes in HPA controller
**What this PR does / why we need it**:
The metrics of "soft-deleted" pods in general to be deleted should probably not matter for scaling purposes, since they'll be gone "soon", whether they're nodelost or just normally delete.
As long as soft-deleted pods still exist, they prevent normal scale up.
**Which issue(s) this PR fixes** *(optional, in `fixes #<issue number>(, fixes #<issue_number>, ...)` format, will close the issue(s) when PR gets merged)*:
Fixes https://github.com/kubernetes/kubernetes/issues/62845
**Special notes for your reviewer**:
**Release note**:
```release-note
Stop counting soft-deleted pods for scaling purposes in HPA controller to avoid soft-deleted pods incorrectly affecting scale up replica count calculation.
```
Duration of initialization taint on CPU and window of initial readiness
setting controlled by flags.
Adding API violation exceptions following example of e50340ee23
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.
Instead discard metric values for pods that are unready and have never
been ready (they may report misleading values, the original reason for
introducing scale up forbidden window).
Use per pod metric when pod is:
- Ready, or
- Not ready but creation timestamp and last readiness change are more
than 10s apart.
In the latter case we asume the pod was ready but later became unready.
We want to use metrics for such pods because sometimes such pods are
unready because they were getting too much load.
Automatic merge from submit-queue (batch tested with PRs 60373, 61098, 61352, 61359, 61362). If you want to cherry-pick this change to another branch, please follow the instructions <a href="https://github.com/kubernetes/community/blob/master/contributors/devel/cherry-picks.md">here</a>.
Add HPA test for FailedGetExternalMetric
**What this PR does / why we need it**:
Add a HPA test for missing external metrics.
**Release note**:
```
NONE
```
Previously, when `GetObjectMetricReplicas` calculated the desired
replica count, it multiplied the usage ratio by the current number of replicas.
This method caused over-scaling when there were pods that were not ready
for a long period of time. For example, if there were pods A, B, and C,
and only pod A was ready, and the usage ratio was 500%, we would
previously specify 15 pods as the desired replicas (even though really
only one pod was handling the load).
After this change, we now multiple the usage
ratio by the number of ready pods for `GetObjectMetricReplicas`.
In the example above, we'd only desire 5 replica pods.
This change gives `GetObjectMetricReplicas` the same behavior as the
other replica calculator methods. Only `GetExternalMetricReplicas` and
`GetExternalPerPodMetricRepliacs` still allow unready pods to impact the
number of desired replicas. I will fix this issue in the following
commit.
Currently, when performing a scale up, any failed pods (which can be present for example in case of evictions performed by kubelet) will be treated as unready. Unready pods are treated as if they had 0% utilization which will slow down or even block scale up.
After this change, failed pods are ignored in all calculations. This way they do not influence neither scale up nor scale down replica calculations.
There have been a couple of recent bugs in the "normalizing" part of the
`reconcileAutoscaler` method. This part of the code base is responsible
for, among other things, taking the suggested desired replicas based on
the metrics, ensuring it conforms to certain conditions, and updating it
if it does not. Isolate the part that converts the desired replicas
based on a given set of rules into its own function.
We are refactoring this part of the code base to make the logic simpler
and to make it easier to write unit tests.
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. If you want to cherry-pick this change to another branch, please follow the instructions <a href="https://github.com/kubernetes/community/blob/master/contributors/devel/cherry-picks.md">here</a>.
Make HPA tolerance a flag
**What this PR does / why we need it**:
Make HPA tolerance configurable as a flag. This change allows us to use
different tolerance values in production/testing.
**Which issue this PR fixes**:
Fixes#18155
**Release note:**
```release-note
Control HPA tolerance through the `horizontal-pod-autoscaler-tolerance` flag.
```
Signed-off-by: mattjmcnaughton <mattjmcnaughton@gmail.com>
Fix#53670
Fix a bug where `desiredReplicas` could be greater than `maxReplicas`
if the original value for `desiredReplicas > scaleUpLimit` and
`scaleUpLimit > maxReplicas`. Previously, when that happened, we would
scale up to `scaleUpLimit`, and then in the next auto-scaling run, scale
down to `maxReplicas`. Address this issue and introduce a regression
test.
Previously
`pkg.controller.podautoscaler.UnsafeConvertToVersion` was
exported. However, it was never used outside of the `podautoscaler`
package. Make it private to prevent confusion.
Additionally, move the two private functions in `horizontal.go` to be
with the other private functions at the bottom of the file - imho its
more readable than having them directly at the top of the file, before
the public type and function definitions.
Fix#18155
Make HPA tolerance configurable as a flag. This change allows us to use
different tolerance values in production/testing.
Signed-off-by: mattjmcnaughton <mattjmcnaughton@gmail.com>
Address `golint` errors in `pkg/controller/podautoscaler`. Note,
I did not address issues around exported types/functions missing
comments, because I'm not sure what the convention within the k8s project is.
Signed-off-by: mattjmcnaughton <mattjmcnaughton@gmail.com>
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.
This commit causes the HPA controller to set a variety of status
conditions using the new `Status.Conditions` field of
autoscaling/v2alpha1. These provide insight into the current state
of the HPA, and generally correspond to similar events being emitted.
The new fake client properly represents the resource of `PodMetrics` as
"pods" and the resource of `NodeMetrics` as "nodes". Previously, it
used "podmetricses" and "nodemetrics", respectively.
This fixes up `horizontal_test.go` and `replica_calc_test.go` to use the
new names.
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.
Joachim Bartosik