Automatic merge from submit-queue
test/kubemark/resources: configure custom etcd endpoints
We want to stress our own etcd cluster with Kubernetes
workloads, using kubemark e2e tests. This PR adds a new
environment variable 'ETCD_SERVERS' to configure custom
etcd endpoints.
/cc @xiang90 @hongchaodeng
Automatic merge from submit-queue (batch tested with PRs 47302, 47389, 47402, 47468, 47459)
Update to kube-addon-manager:v6.4-beta.2: kubectl v1.6.4 and refreshed base images
**What this PR does / why we need it**: refreshes base images for kube-addon-manager with fixes for CVE-2016-9841 and CVE-2016-9843.
x-ref https://github.com/kubernetes/kubernetes/issues/47386
**Special notes for your reviewer**: the updated images are not yet pushed, so tests will fail until that's done.
**Release note**:
```release-note
```
/assign @MrHohn
We want to stress our own etcd cluster with Kubernetes
workloads, using kubemark e2e tests. This PR adds a new
environment variable 'ETCD_SERVERS' to configure custom
etcd endpoints.
Signed-off-by: Gyu-Ho Lee <gyuhox@gmail.com>
Automatic merge from submit-queue
Avoid double printing output of gcloud commands in kubemark
Just noticed we were unnecessarily echoing the result again.
/cc @wojtek-t
Automatic merge from submit-queue (batch tested with PRs 46124, 46434, 46089, 45589, 46045)
Copy kubeconfig to kubemark master
This should save the effort of digging through jenkins agent and its container to get the kubeconfig.
Ideally we should have kubectl directly working on the kubemark master, but I'm facing some issues due to older version of kubectl present by default on the node.
cc @wojtek-t @gmarek
Automatic merge from submit-queue
Enable "kick the tires" support for Nvidia GPUs in COS
This PR provides an installation daemonset that will install Nvidia CUDA drivers on Google Container Optimized OS (COS).
User space libraries and debug utilities from the Nvidia driver installation are made available on the host in a special directory on the host -
* `/home/kubernetes/bin/nvidia/lib` for libraries
* `/home/kubernetes/bin/nvidia/bin` for debug utilities
Containers that run CUDA applications on COS are expected to consume the libraries and debug utilities (if necessary) from the host directories using `HostPath` volumes.
Note: This solution requires updating Pod Spec across distros. This is a known issue and will be addressed in the future. Until then CUDA workloads will not be portable.
This PR updates the COS base image version to m59. This is coupled with this PR for the following reasons:
1. Driver installation requires disabling a kernel feature in COS.
2. The kernel API for disabling this interface changed across COS versions
3. If the COS image update is not handled in this PR, then a subsequent COS image update will break GPU integration and will require an update to the installation scripts in this PR.
4. Instead of having to post `3` PRs, one each for adding the basic installer, updating COS to m59, and then updating the installer again, this PR combines all the changes to reduce review overhead and latency, and additional noise that will be created when GPU tests break.
**Try out this PR**
1. Get Quota for GPUs in any region
2. `export `KUBE_GCE_ZONE=<zone-with-gpus>` KUBE_NODE_OS_DISTRIBUTION=gci`
3. `NODE_ACCELERATORS="type=nvidia-tesla-k80,count=1" cluster/kube-up.sh`
4. `kubectl create -f cluster/gce/gci/nvidia-gpus/cos-installer-daemonset.yaml`
5. Run your CUDA app in a pod.
**Another option is to run a e2e manually to try out this PR**
1. Get Quota for GPUs in any region
2. export `KUBE_GCE_ZONE=<zone-with-gpus>` KUBE_NODE_OS_DISTRIBUTION=gci
3. `NODE_ACCELERATORS="type=nvidia-tesla-k80,count=1"`
4. `go run hack/e2e.go -- --up`
5. `hack/ginkgo-e2e.sh --ginkgo.focus="\[Feature:GPU\]"`
The e2e will install the drivers automatically using the daemonset and then run test workloads to validate driver integration.
TODO:
- [x] Update COS image version to m59 release.
- [x] Remove sleep from the install script and add it to the daemonset
- [x] Add an e2e that will run the daemonset and run a sample CUDA app on COS clusters.
- [x] Setup a test project with necessary quota to run GPU tests against HEAD to start with https://github.com/kubernetes/test-infra/pull/2759
- [x] Update node e2e serial configs to install nvidia drivers on COS by default
Automatic merge from submit-queue (batch tested with PRs 46133, 46211, 46224, 46205, 45910)
Make CPU request for heapster in kubemark scale with the number of Nodes
Automatic merge from submit-queue
Make real proxier in hollow-proxy optional (default=true)
Ref https://github.com/kubernetes/kubernetes/pull/45622
This allows using real proxier for hollow proxy, but we use the fake one by default.
cc @kubernetes/sig-scalability-misc @wojtek-t @gmarek
Automatic merge from submit-queue (batch tested with PRs 45569, 45602, 45604, 45478, 45550)
Minor bug fix in start-kubemark-master script
cc @wojtek-t @gmarek
Per Clayton's suggestion, move stuff from cluster/lib/util.sh to
hack/lib/util.sh. Also consolidate ensure-temp-dir and use the
hack/lib/util.sh implementation rather than cluster/common.sh.
Automatic merge from submit-queue (batch tested with PRs 42672, 42770, 42818, 42820, 40849)
kubemark test: Bump addon-manager to v6.4-beta.1
Follow up PR of #42760. This PR bumps addon-manager to v6.4-beta.1 for kubemark test.
**Release note**:
```release-note
NONE
```
Shyam Jeedigunta