Merge branch 'master' into hpa-doc-fix
This commit is contained in:
Jerzy Szczepkowski
@@ -27,7 +27,7 @@ $ kubectl config view
|
||||
```
|
||||
|
||||
Many of the [examples](https://github.com/kubernetes/kubernetes/tree/{{page.githubbranch}}/examples/) provide an introduction to using
|
||||
kubectl and complete documentation is found in the [kubectl manual](/docs/user-guide/kubectl/kubectl).
|
||||
kubectl and complete documentation is found in the [kubectl manual](/docs/user-guide/kubectl/index).
|
||||
|
||||
### Directly accessing the REST API
|
||||
|
||||
|
||||
@@ -9,7 +9,7 @@ assignees:
|
||||
* TOC
|
||||
{:toc}
|
||||
|
||||
# The Kubernetes model for connecting containers
|
||||
## The Kubernetes model for connecting containers
|
||||
|
||||
Now that you have a continuously running, replicated application you can expose it on a network. Before discussing the Kubernetes approach to networking, it is worthwhile to contrast it with the "normal" way networking works with Docker.
|
||||
|
||||
|
||||
@@ -1,50 +1,50 @@
|
||||
---
|
||||
assignees:
|
||||
- caesarxuchao
|
||||
- mikedanese
|
||||
|
||||
---
|
||||
|
||||
kubectl port-forward forwards connections to a local port to a port on a pod. Its man page is available [here](/docs/user-guide/kubectl/kubectl_port-forward). Compared to [kubectl proxy](/docs/user-guide/accessing-the-cluster/#using-kubectl-proxy), `kubectl port-forward` is more generic as it can forward TCP traffic while `kubectl proxy` can only forward HTTP traffic. This guide demonstrates how to use `kubectl port-forward` to connect to a Redis database, which may be useful for database debugging.
|
||||
|
||||
## Creating a Redis master
|
||||
|
||||
```shell
|
||||
$ kubectl create -f examples/redis/redis-master.yaml
|
||||
pods/redis-master
|
||||
```
|
||||
|
||||
wait until the Redis master pod is Running and Ready,
|
||||
|
||||
```shell
|
||||
$ kubectl get pods
|
||||
NAME READY STATUS RESTARTS AGE
|
||||
redis-master 2/2 Running 0 41s
|
||||
```
|
||||
|
||||
## Connecting to the Redis master[a]
|
||||
|
||||
The Redis master is listening on port 6379, to verify this,
|
||||
|
||||
```shell{% raw %}
|
||||
$ kubectl get pods redis-master --template='{{(index (index .spec.containers 0).ports 0).containerPort}}{{"\n"}}'
|
||||
6379{% endraw %}
|
||||
```
|
||||
|
||||
then we forward the port 6379 on the local workstation to the port 6379 of pod redis-master,
|
||||
|
||||
```shell
|
||||
$ kubectl port-forward redis-master 6379:6379
|
||||
I0710 14:43:38.274550 3655 portforward.go:225] Forwarding from 127.0.0.1:6379 -> 6379
|
||||
I0710 14:43:38.274797 3655 portforward.go:225] Forwarding from [::1]:6379 -> 6379
|
||||
```
|
||||
|
||||
To verify the connection is successful, we run a redis-cli on the local workstation,
|
||||
|
||||
```shell
|
||||
$ redis-cli
|
||||
127.0.0.1:6379> ping
|
||||
PONG
|
||||
```
|
||||
|
||||
Now one can debug the database from the local workstation.
|
||||
---
|
||||
assignees:
|
||||
- caesarxuchao
|
||||
- mikedanese
|
||||
|
||||
---
|
||||
|
||||
kubectl port-forward forwards connections to a local port to a port on a pod. Its man page is available [here](/docs/user-guide/kubectl/kubectl_port-forward). Compared to [kubectl proxy](/docs/user-guide/accessing-the-cluster/#using-kubectl-proxy), `kubectl port-forward` is more generic as it can forward TCP traffic while `kubectl proxy` can only forward HTTP traffic. This guide demonstrates how to use `kubectl port-forward` to connect to a Redis database, which may be useful for database debugging.
|
||||
|
||||
## Creating a Redis master
|
||||
|
||||
```shell
|
||||
$ kubectl create -f examples/redis/redis-master.yaml
|
||||
pods/redis-master
|
||||
```
|
||||
|
||||
wait until the Redis master pod is Running and Ready,
|
||||
|
||||
```shell
|
||||
$ kubectl get pods
|
||||
NAME READY STATUS RESTARTS AGE
|
||||
redis-master 2/2 Running 0 41s
|
||||
```
|
||||
|
||||
## Connecting to the Redis master[a]
|
||||
|
||||
The Redis master is listening on port 6379, to verify this,
|
||||
|
||||
```shell{% raw %}
|
||||
$ kubectl get pods redis-master --template='{{(index (index .spec.containers 0).ports 0).containerPort}}{{"\n"}}'
|
||||
6379{% endraw %}
|
||||
```
|
||||
|
||||
then we forward the port 6379 on the local workstation to the port 6379 of pod redis-master,
|
||||
|
||||
```shell
|
||||
$ kubectl port-forward redis-master 6379:6379
|
||||
I0710 14:43:38.274550 3655 portforward.go:225] Forwarding from 127.0.0.1:6379 -> 6379
|
||||
I0710 14:43:38.274797 3655 portforward.go:225] Forwarding from [::1]:6379 -> 6379
|
||||
```
|
||||
|
||||
To verify the connection is successful, we run a redis-cli on the local workstation,
|
||||
|
||||
```shell
|
||||
$ redis-cli
|
||||
127.0.0.1:6379> ping
|
||||
PONG
|
||||
```
|
||||
|
||||
Now one can debug the database from the local workstation.
|
||||
|
||||
@@ -1,32 +1,32 @@
|
||||
---
|
||||
assignees:
|
||||
- caesarxuchao
|
||||
- lavalamp
|
||||
|
||||
---
|
||||
|
||||
You have seen the [basics](/docs/user-guide/accessing-the-cluster) about `kubectl proxy` and `apiserver proxy`. This guide shows how to use them together to access a service([kube-ui](/docs/user-guide/ui)) running on the Kubernetes cluster from your workstation.
|
||||
|
||||
|
||||
## Getting the apiserver proxy URL of kube-ui
|
||||
|
||||
kube-ui is deployed as a cluster add-on. To find its apiserver proxy URL,
|
||||
|
||||
```shell
|
||||
$ kubectl cluster-info | grep "KubeUI"
|
||||
KubeUI is running at https://173.255.119.104/api/v1/proxy/namespaces/kube-system/services/kube-ui
|
||||
```
|
||||
|
||||
if this command does not find the URL, try the steps [here](/docs/user-guide/ui/#accessing-the-ui).
|
||||
|
||||
|
||||
## Connecting to the kube-ui service from your local workstation
|
||||
|
||||
The above proxy URL is an access to the kube-ui service provided by the apiserver. To access it, you still need to authenticate to the apiserver. `kubectl proxy` can handle the authentication.
|
||||
|
||||
```shell
|
||||
$ kubectl proxy --port=8001
|
||||
Starting to serve on localhost:8001
|
||||
```
|
||||
|
||||
---
|
||||
assignees:
|
||||
- caesarxuchao
|
||||
- lavalamp
|
||||
|
||||
---
|
||||
|
||||
You have seen the [basics](/docs/user-guide/accessing-the-cluster) about `kubectl proxy` and `apiserver proxy`. This guide shows how to use them together to access a service([kube-ui](/docs/user-guide/ui)) running on the Kubernetes cluster from your workstation.
|
||||
|
||||
|
||||
## Getting the apiserver proxy URL of kube-ui
|
||||
|
||||
kube-ui is deployed as a cluster add-on. To find its apiserver proxy URL,
|
||||
|
||||
```shell
|
||||
$ kubectl cluster-info | grep "KubeUI"
|
||||
KubeUI is running at https://173.255.119.104/api/v1/proxy/namespaces/kube-system/services/kube-ui
|
||||
```
|
||||
|
||||
if this command does not find the URL, try the steps [here](/docs/user-guide/ui/#accessing-the-ui).
|
||||
|
||||
|
||||
## Connecting to the kube-ui service from your local workstation
|
||||
|
||||
The above proxy URL is an access to the kube-ui service provided by the apiserver. To access it, you still need to authenticate to the apiserver. `kubectl proxy` can handle the authentication.
|
||||
|
||||
```shell
|
||||
$ kubectl proxy --port=8001
|
||||
Starting to serve on localhost:8001
|
||||
```
|
||||
|
||||
Now you can access the kube-ui service on your local workstation at [http://localhost:8001/api/v1/proxy/namespaces/kube-system/services/kube-ui](http://localhost:8001/api/v1/proxy/namespaces/kube-system/services/kube-ui)
|
||||
@@ -1,74 +1,74 @@
|
||||
---
|
||||
assignees:
|
||||
- caesarxuchao
|
||||
- mikedanese
|
||||
|
||||
---
|
||||
|
||||
Developers can use `kubectl exec` to run commands in a container. This guide demonstrates two use cases.
|
||||
|
||||
## Using kubectl exec to check the environment variables of a container
|
||||
|
||||
Kubernetes exposes [services](/docs/user-guide/services/#environment-variables) through environment variables. It is convenient to check these environment variables using `kubectl exec`.
|
||||
|
||||
We first create a pod and a service,
|
||||
|
||||
```shell
|
||||
$ kubectl create -f examples/guestbook/redis-master-controller.yaml
|
||||
$ kubectl create -f examples/guestbook/redis-master-service.yaml
|
||||
```
|
||||
wait until the pod is Running and Ready,
|
||||
|
||||
```shell
|
||||
$ kubectl get pod
|
||||
NAME READY REASON RESTARTS AGE
|
||||
redis-master-ft9ex 1/1 Running 0 12s
|
||||
```
|
||||
|
||||
then we can check the environment variables of the pod,
|
||||
|
||||
```shell
|
||||
$ kubectl exec redis-master-ft9ex env
|
||||
...
|
||||
REDIS_MASTER_SERVICE_PORT=6379
|
||||
REDIS_MASTER_SERVICE_HOST=10.0.0.219
|
||||
...
|
||||
```
|
||||
|
||||
We can use these environment variables in applications to find the service.
|
||||
|
||||
|
||||
## Using kubectl exec to check the mounted volumes
|
||||
|
||||
It is convenient to use `kubectl exec` to check if the volumes are mounted as expected.
|
||||
We first create a Pod with a volume mounted at /data/redis,
|
||||
|
||||
```shell
|
||||
kubectl create -f docs/user-guide/walkthrough/pod-redis.yaml
|
||||
```
|
||||
|
||||
wait until the pod is Running and Ready,
|
||||
|
||||
```shell
|
||||
$ kubectl get pods
|
||||
NAME READY REASON RESTARTS AGE
|
||||
storage 1/1 Running 0 1m
|
||||
```
|
||||
|
||||
we then use `kubectl exec` to verify that the volume is mounted at /data/redis,
|
||||
|
||||
```shell
|
||||
$ kubectl exec storage ls /data
|
||||
redis
|
||||
```
|
||||
|
||||
## Using kubectl exec to open a bash terminal in a pod
|
||||
|
||||
After all, open a terminal in a pod is the most direct way to introspect the pod. Assuming the pod/storage is still running, run
|
||||
|
||||
```shell
|
||||
$ kubectl exec -ti storage -- bash
|
||||
root@storage:/data#
|
||||
```
|
||||
|
||||
---
|
||||
assignees:
|
||||
- caesarxuchao
|
||||
- mikedanese
|
||||
|
||||
---
|
||||
|
||||
Developers can use `kubectl exec` to run commands in a container. This guide demonstrates two use cases.
|
||||
|
||||
## Using kubectl exec to check the environment variables of a container
|
||||
|
||||
Kubernetes exposes [services](/docs/user-guide/services/#environment-variables) through environment variables. It is convenient to check these environment variables using `kubectl exec`.
|
||||
|
||||
We first create a pod and a service,
|
||||
|
||||
```shell
|
||||
$ kubectl create -f examples/guestbook/redis-master-controller.yaml
|
||||
$ kubectl create -f examples/guestbook/redis-master-service.yaml
|
||||
```
|
||||
wait until the pod is Running and Ready,
|
||||
|
||||
```shell
|
||||
$ kubectl get pod
|
||||
NAME READY REASON RESTARTS AGE
|
||||
redis-master-ft9ex 1/1 Running 0 12s
|
||||
```
|
||||
|
||||
then we can check the environment variables of the pod,
|
||||
|
||||
```shell
|
||||
$ kubectl exec redis-master-ft9ex env
|
||||
...
|
||||
REDIS_MASTER_SERVICE_PORT=6379
|
||||
REDIS_MASTER_SERVICE_HOST=10.0.0.219
|
||||
...
|
||||
```
|
||||
|
||||
We can use these environment variables in applications to find the service.
|
||||
|
||||
|
||||
## Using kubectl exec to check the mounted volumes
|
||||
|
||||
It is convenient to use `kubectl exec` to check if the volumes are mounted as expected.
|
||||
We first create a Pod with a volume mounted at /data/redis,
|
||||
|
||||
```shell
|
||||
kubectl create -f docs/user-guide/walkthrough/pod-redis.yaml
|
||||
```
|
||||
|
||||
wait until the pod is Running and Ready,
|
||||
|
||||
```shell
|
||||
$ kubectl get pods
|
||||
NAME READY REASON RESTARTS AGE
|
||||
storage 1/1 Running 0 1m
|
||||
```
|
||||
|
||||
we then use `kubectl exec` to verify that the volume is mounted at /data/redis,
|
||||
|
||||
```shell
|
||||
$ kubectl exec storage ls /data
|
||||
redis
|
||||
```
|
||||
|
||||
## Using kubectl exec to open a bash terminal in a pod
|
||||
|
||||
After all, open a terminal in a pod is the most direct way to introspect the pod. Assuming the pod/storage is still running, run
|
||||
|
||||
```shell
|
||||
$ kubectl exec -ti storage -- bash
|
||||
root@storage:/data#
|
||||
```
|
||||
|
||||
This gets you a terminal.
|
||||
@@ -5,7 +5,7 @@ assignees:
|
||||
|
||||
---
|
||||
|
||||
Use this overview of the `kubectl` command line interface to help you start running commands against Kubernetes clusters. This overview quickly covers `kubectl` syntax, describes the command operations, and provides common examples. For details about each command, including all the supported flags and subcommands, see the [kubectl](/docs/user-guide/kubectl/kubectl) reference documentation.
|
||||
Use this overview of the `kubectl` command line interface to help you start running commands against Kubernetes clusters. This overview quickly covers `kubectl` syntax, describes the command operations, and provides common examples. For details about each command, including all the supported flags and subcommands, see the [kubectl](/docs/user-guide/kubectl) reference documentation.
|
||||
|
||||
TODO: Auto-generate this file to ensure it's always in sync with any `kubectl` changes, see [#14177](http://pr.k8s.io/14177).
|
||||
|
||||
@@ -85,25 +85,33 @@ The following table includes a list of all the supported resource types and thei
|
||||
|
||||
Resource type | Abbreviated alias
|
||||
-------------------- | --------------------
|
||||
`componentstatuses` | `cs`
|
||||
`daemonsets` | `ds`
|
||||
`deployments` |
|
||||
`events` | `ev`
|
||||
`endpoints` | `ep`
|
||||
`horizontalpodautoscalers` | `hpa`
|
||||
`ingresses` | `ing`
|
||||
`clusters` |
|
||||
`componentstatuses` |`cs`
|
||||
`configmaps` |`cm`
|
||||
`daemonsets` |`ds`
|
||||
`deployments` |`deploy`
|
||||
`endpoints` |`ep`
|
||||
`events` |`ev`
|
||||
`horizontalpodautoscalers` |`hpa`
|
||||
`ingresses` |`ing`
|
||||
`jobs` |
|
||||
`limitranges` | `limits`
|
||||
`nodes` | `no`
|
||||
`namespaces` | `ns`
|
||||
`pods` | `po`
|
||||
`persistentvolumes` | `pv`
|
||||
`persistentvolumeclaims` | `pvc`
|
||||
`resourcequotas` | `quota`
|
||||
`replicationcontrollers` | `rc`
|
||||
`limitranges` |`limits`
|
||||
`namespaces` |`ns`
|
||||
`networkpolicies` |
|
||||
`nodes` |`no`
|
||||
`persistentvolumeclaims` |`pvc`
|
||||
`persistentvolumes` |`pv`
|
||||
`pods` |`po`
|
||||
`podsecuritypolicies` |`psp`
|
||||
`podtemplates` |
|
||||
`replicasets` |`rs`
|
||||
`replicationcontrollers` |`rc`
|
||||
`resourcequotas` |`quota`
|
||||
`secrets` |
|
||||
`serviceaccounts` |
|
||||
`services` | `svc`
|
||||
`serviceaccounts` |`sa`
|
||||
`services` |`svc`
|
||||
`storageclasses` |
|
||||
`thirdpartyresources` |
|
||||
|
||||
## Output options
|
||||
|
||||
|
||||
+79
-79
@@ -1,80 +1,80 @@
|
||||
---
|
||||
assignees:
|
||||
- mikedanese
|
||||
|
||||
---
|
||||
|
||||
This page is designed to help you use logs to troubleshoot issues with your Kubernetes solution.
|
||||
|
||||
## Logging by Kubernetes Components
|
||||
|
||||
Kubernetes components, such as kubelet and apiserver, use the [glog](https://godoc.org/github.com/golang/glog) logging library. Developer conventions for logging severity are described in [docs/devel/logging.md](https://github.com/kubernetes/kubernetes/tree/{{page.githubbranch}}/docs/devel/logging.md).
|
||||
|
||||
## Examining the logs of running containers
|
||||
|
||||
The logs of a running container may be fetched using the command `kubectl logs`. For example, given
|
||||
this pod specification [counter-pod.yaml](https://github.com/kubernetes/kubernetes/tree/{{page.githubbranch}}/examples/blog-logging/counter-pod.yaml), which has a container which writes out some text to standard
|
||||
output every second. (You can find different pod specifications [here](https://github.com/kubernetes/kubernetes.github.io/tree/{{page.docsbranch}}/docs/user-guide/logging-demo/).)
|
||||
|
||||
{% include code.html language="yaml" file="counter-pod.yaml" k8slink="/examples/blog-logging/counter-pod.yaml" %}
|
||||
|
||||
we can run the pod:
|
||||
|
||||
```shell
|
||||
$ kubectl create -f ./counter-pod.yaml
|
||||
pods/counter
|
||||
```
|
||||
|
||||
and then fetch the logs:
|
||||
|
||||
```shell
|
||||
$ kubectl logs counter
|
||||
0: Tue Jun 2 21:37:31 UTC 2015
|
||||
1: Tue Jun 2 21:37:32 UTC 2015
|
||||
2: Tue Jun 2 21:37:33 UTC 2015
|
||||
3: Tue Jun 2 21:37:34 UTC 2015
|
||||
4: Tue Jun 2 21:37:35 UTC 2015
|
||||
5: Tue Jun 2 21:37:36 UTC 2015
|
||||
...
|
||||
```
|
||||
|
||||
If a pod has more than one container then you need to specify which container's log files should
|
||||
be fetched e.g.
|
||||
|
||||
```shell
|
||||
$ kubectl logs kube-dns-v3-7r1l9 etcd
|
||||
2015/06/23 00:43:10 etcdserver: start to snapshot (applied: 30003, lastsnap: 20002)
|
||||
2015/06/23 00:43:10 etcdserver: compacted log at index 30003
|
||||
2015/06/23 00:43:10 etcdserver: saved snapshot at index 30003
|
||||
2015/06/23 02:05:42 etcdserver: start to snapshot (applied: 40004, lastsnap: 30003)
|
||||
2015/06/23 02:05:42 etcdserver: compacted log at index 40004
|
||||
2015/06/23 02:05:42 etcdserver: saved snapshot at index 40004
|
||||
2015/06/23 03:28:31 etcdserver: start to snapshot (applied: 50005, lastsnap: 40004)
|
||||
2015/06/23 03:28:31 etcdserver: compacted log at index 50005
|
||||
2015/06/23 03:28:31 etcdserver: saved snapshot at index 50005
|
||||
2015/06/23 03:28:56 filePurge: successfully removed file default.etcd/member/wal/0000000000000000-0000000000000000.wal
|
||||
2015/06/23 04:51:03 etcdserver: start to snapshot (applied: 60006, lastsnap: 50005)
|
||||
2015/06/23 04:51:03 etcdserver: compacted log at index 60006
|
||||
2015/06/23 04:51:03 etcdserver: saved snapshot at index 60006
|
||||
...
|
||||
```
|
||||
|
||||
## Cluster level logging to Google Cloud Logging
|
||||
|
||||
The getting started guide [Cluster Level Logging to Google Cloud Logging](/docs/getting-started-guides/logging)
|
||||
explains how container logs are ingested into [Google Cloud Logging](https://cloud.google.com/logging/docs/)
|
||||
and shows how to query the ingested logs.
|
||||
|
||||
## Cluster level logging with Elasticsearch and Kibana
|
||||
|
||||
The getting started guide [Cluster Level Logging with Elasticsearch and Kibana](/docs/getting-started-guides/logging-elasticsearch)
|
||||
describes how to ingest cluster level logs into Elasticsearch and view them using Kibana.
|
||||
|
||||
## Ingesting Application Log Files
|
||||
|
||||
Cluster level logging only collects the standard output and standard error output of the applications
|
||||
running in containers. The guide [Collecting log files from within containers with Fluentd and sending them to the Google Cloud Logging service](https://github.com/kubernetes/contrib/blob/master/logging/fluentd-sidecar-gcp/README.md) explains how the log files of applications can also be ingested into Google Cloud logging.
|
||||
|
||||
## Known issues
|
||||
|
||||
---
|
||||
assignees:
|
||||
- mikedanese
|
||||
|
||||
---
|
||||
|
||||
This page is designed to help you use logs to troubleshoot issues with your Kubernetes solution.
|
||||
|
||||
## Logging by Kubernetes Components
|
||||
|
||||
Kubernetes components, such as kubelet and apiserver, use the [glog](https://godoc.org/github.com/golang/glog) logging library. Developer conventions for logging severity are described in [docs/devel/logging.md](https://github.com/kubernetes/kubernetes/tree/{{page.githubbranch}}/docs/devel/logging.md).
|
||||
|
||||
## Examining the logs of running containers
|
||||
|
||||
The logs of a running container may be fetched using the command `kubectl logs`. For example, given
|
||||
this pod specification [counter-pod.yaml](https://github.com/kubernetes/kubernetes/tree/{{page.githubbranch}}/examples/blog-logging/counter-pod.yaml), which has a container which writes out some text to standard
|
||||
output every second. (You can find different pod specifications [here](https://github.com/kubernetes/kubernetes.github.io/tree/{{page.docsbranch}}/docs/user-guide/logging-demo/).)
|
||||
|
||||
{% include code.html language="yaml" file="counter-pod.yaml" k8slink="/examples/blog-logging/counter-pod.yaml" %}
|
||||
|
||||
we can run the pod:
|
||||
|
||||
```shell
|
||||
$ kubectl create -f ./counter-pod.yaml
|
||||
pods/counter
|
||||
```
|
||||
|
||||
and then fetch the logs:
|
||||
|
||||
```shell
|
||||
$ kubectl logs counter
|
||||
0: Tue Jun 2 21:37:31 UTC 2015
|
||||
1: Tue Jun 2 21:37:32 UTC 2015
|
||||
2: Tue Jun 2 21:37:33 UTC 2015
|
||||
3: Tue Jun 2 21:37:34 UTC 2015
|
||||
4: Tue Jun 2 21:37:35 UTC 2015
|
||||
5: Tue Jun 2 21:37:36 UTC 2015
|
||||
...
|
||||
```
|
||||
|
||||
If a pod has more than one container then you need to specify which container's log files should
|
||||
be fetched e.g.
|
||||
|
||||
```shell
|
||||
$ kubectl logs kube-dns-v3-7r1l9 etcd
|
||||
2015/06/23 00:43:10 etcdserver: start to snapshot (applied: 30003, lastsnap: 20002)
|
||||
2015/06/23 00:43:10 etcdserver: compacted log at index 30003
|
||||
2015/06/23 00:43:10 etcdserver: saved snapshot at index 30003
|
||||
2015/06/23 02:05:42 etcdserver: start to snapshot (applied: 40004, lastsnap: 30003)
|
||||
2015/06/23 02:05:42 etcdserver: compacted log at index 40004
|
||||
2015/06/23 02:05:42 etcdserver: saved snapshot at index 40004
|
||||
2015/06/23 03:28:31 etcdserver: start to snapshot (applied: 50005, lastsnap: 40004)
|
||||
2015/06/23 03:28:31 etcdserver: compacted log at index 50005
|
||||
2015/06/23 03:28:31 etcdserver: saved snapshot at index 50005
|
||||
2015/06/23 03:28:56 filePurge: successfully removed file default.etcd/member/wal/0000000000000000-0000000000000000.wal
|
||||
2015/06/23 04:51:03 etcdserver: start to snapshot (applied: 60006, lastsnap: 50005)
|
||||
2015/06/23 04:51:03 etcdserver: compacted log at index 60006
|
||||
2015/06/23 04:51:03 etcdserver: saved snapshot at index 60006
|
||||
...
|
||||
```
|
||||
|
||||
## Cluster level logging to Google Cloud Logging
|
||||
|
||||
The getting started guide [Cluster Level Logging to Google Cloud Logging](/docs/getting-started-guides/logging)
|
||||
explains how container logs are ingested into [Google Cloud Logging](https://cloud.google.com/logging/docs/)
|
||||
and shows how to query the ingested logs.
|
||||
|
||||
## Cluster level logging with Elasticsearch and Kibana
|
||||
|
||||
The getting started guide [Cluster Level Logging with Elasticsearch and Kibana](/docs/getting-started-guides/logging-elasticsearch)
|
||||
describes how to ingest cluster level logs into Elasticsearch and view them using Kibana.
|
||||
|
||||
## Ingesting Application Log Files
|
||||
|
||||
Cluster level logging only collects the standard output and standard error output of the applications
|
||||
running in containers. The guide [Collecting log files from within containers with Fluentd and sending them to the Google Cloud Logging service](https://github.com/kubernetes/contrib/blob/master/logging/fluentd-sidecar-gcp/README.md) explains how the log files of applications can also be ingested into Google Cloud logging.
|
||||
|
||||
## Known issues
|
||||
|
||||
Kubernetes does log rotation for Kubernetes components and docker containers. The command `kubectl logs` currently only read the latest logs, not all historical ones.
|
||||
@@ -6,7 +6,7 @@ assignees:
|
||||
|
||||
Understanding how an application behaves when deployed is crucial to scaling the application and providing a reliable service. In a Kubernetes cluster, application performance can be examined at many different levels: containers, [pods](/docs/user-guide/pods), [services](/docs/user-guide/services), and whole clusters. As part of Kubernetes we want to provide users with detailed resource usage information about their running applications at all these levels. This will give users deep insights into how their applications are performing and where possible application bottlenecks may be found. In comes [Heapster](https://github.com/kubernetes/heapster), a project meant to provide a base monitoring platform on Kubernetes.
|
||||
|
||||
### Overview
|
||||
## Overview
|
||||
|
||||
Heapster is a cluster-wide aggregator of monitoring and event data. It currently supports Kubernetes natively and works on all Kubernetes setups. Heapster runs as a pod in the cluster, similar to how any Kubernetes application would run. The Heapster pod discovers all nodes in the cluster and queries usage information from the nodes' [Kubelet](https://releases.k8s.io/{{page.githubbranch}}/DESIGN.md#kubelet)s, the on-machine Kubernetes agent. The Kubelet itself fetches the data from [cAdvisor](https://github.com/google/cadvisor). Heapster groups the information by pod along with the relevant labels. This data is then pushed to a configurable backend for storage and visualization. Currently supported backends include [InfluxDB](http://influxdb.com/) (with [Grafana](http://grafana.org/) for visualization), [Google Cloud Monitoring](https://cloud.google.com/monitoring/) and many others described in more details [here](https://github.com/kubernetes/heapster/blob/master/docs/sink-configuration.md). The overall architecture of the service can be seen below:
|
||||
|
||||
|
||||
@@ -150,7 +150,9 @@ Pod is exposed as a primitive in order to facilitate:
|
||||
* clean composition of Kubelet-level functionality with cluster-level functionality — Kubelet is effectively the "pod controller"
|
||||
* high-availability applications, which will expect pods to be replaced in advance of their termination and certainly in advance of deletion, such as in the case of planned evictions, image prefetching, or live pod migration [#3949](http://issue.k8s.io/3949)
|
||||
|
||||
The current best practice for pets is to create a replication controller with `replicas` equal to `1` and a corresponding service. If you find this cumbersome, please comment on [issue #260](http://issue.k8s.io/260).
|
||||
There is new first-class support for pet-like pods with the [PetSet](/docs/user-guide/petset/) feature (currently in alpha).
|
||||
For prior versions of Kubernetes, best practice for pets is to create a replication controller with `replicas` equal to `1` and a corresponding service.
|
||||
|
||||
|
||||
## Termination of Pods
|
||||
|
||||
|
||||
@@ -12,7 +12,7 @@ assignees:
|
||||
To update a service without an outage, `kubectl` supports what is called ['rolling update'](/docs/user-guide/kubectl/kubectl_rolling-update), which updates one pod at a time, rather than taking down the entire service at the same time. See the [rolling update design document](https://github.com/kubernetes/kubernetes/blob/{{page.githubbranch}}/docs/design/simple-rolling-update.md) and the [example of rolling update](/docs/user-guide/update-demo/) for more information.
|
||||
|
||||
Note that `kubectl rolling-update` only supports Replication Controllers. However, if you deploy applications with Replication Controllers,
|
||||
consider switching them to [Deployments](/docs/user-guide/deployments/). A Deployments is a higher-level controller that automates rolling updates
|
||||
consider switching them to [Deployments](/docs/user-guide/deployments/). A Deployment is a higher-level controller that automates rolling updates
|
||||
of applications declaratively, and therefore is recommended. If you still want to keep your Replication Controllers and use `kubectl rolling-update`, keep reading:
|
||||
|
||||
A rolling update applies changes to the configuration of pods being managed by
|
||||
|
||||
@@ -377,7 +377,7 @@ To use a secret in an environment variable in a pod:
|
||||
1. Modify your Pod definition in each container that you wish to consume the value of a secret key to add an environment variable for each secret key you wish to consume. The environment variable that consumes the secret key should populate the secret's name and key in `env[x].valueFrom.secretKeyRef`.
|
||||
1. Modify your image and/or command line so that the program looks for values in the specified environment variables
|
||||
|
||||
This is an example of a pod that mounts a secret in a volume:
|
||||
This is an example of a pod that uses secrets from environment variables:
|
||||
|
||||
```yaml
|
||||
apiVersion: v1
|
||||
@@ -543,9 +543,9 @@ credentials.
|
||||
Make the secrets:
|
||||
|
||||
```shell
|
||||
$ kubectl create secret generic prod-db-secret --from-literal=user=produser --from-literal=password=Y4nys7f11
|
||||
$ kubectl create secret generic prod-db-secret --from-literal=username=produser --from-literal=password=Y4nys7f11
|
||||
secret "prod-db-secret" created
|
||||
$ kubectl create secret generic test-db-secret --from-literal=user=testuser --from-literal=password=iluvtests
|
||||
$ kubectl create secret generic test-db-secret --from-literal=username=testuser --from-literal=password=iluvtests
|
||||
secret "test-db-secret" created
|
||||
```
|
||||
|
||||
|
||||
@@ -0,0 +1,118 @@
|
||||
---
|
||||
assignees:
|
||||
- IanLewis
|
||||
|
||||
---
|
||||
|
||||
* TOC
|
||||
{:toc}
|
||||
|
||||
## What is ThirdPartyResource?
|
||||
|
||||
Kubernetes comes with many built-in API objects. However, there are often times when you might need to extend Kubernetes with their own API objects in order to do custom automation.
|
||||
|
||||
`ThirdPartyResource` objects are a way to extend the Kubernetes API with a new API object type. The new API object type will be given an API endpoint URL and support CRUD operations, and watch API. You can then create custom objects using this API endpoint. You can think of `ThirdPartyResources` as being much like the schema for a database table. Once you have created the table, you can then start storing rows in the table. Once created, `ThirdPartyResources` can act as the data model behind custom controllers or automation programs.
|
||||
|
||||
## Structure of a ThirdPartyResource
|
||||
|
||||
Each `ThirdPartyResource` has the following:
|
||||
|
||||
* `metadata` - Standard Kubernetes object metadata.
|
||||
* `kind` - The kind of the resources described by this third party resource.
|
||||
* `description` - A free text description of the resource.
|
||||
* `versions` - A list of the versions of the resource.
|
||||
|
||||
The `kind` for a `ThirdPartyResource` takes the form `<kind name>.<domain>`. You are expected to provide a unique kind and domain name in order to avoid conflicts with other `ThirdPartyResource` objects. Kind names will be converted to CamelCase when creating instances of the `ThirdPartyResource`. Hypens in the `kind` are assumed to be word breaks. For instance the kind `camel-case` would be converted to `CamelCase` but `camelcase` would be converted to `Camelcase`.
|
||||
|
||||
Other fields on the `ThirdPartyResource` are treated as custom data fields. These fields can hold arbitrary JSON data and have any structure.
|
||||
|
||||
You can view the full documentation about `ThirdPartyResources` using the `explain` command in kubectl.
|
||||
|
||||
```
|
||||
$ kubectl explain thirdpartyresource
|
||||
```
|
||||
|
||||
## Creating a ThirdPartyResource
|
||||
|
||||
When you user create a new `ThirdPartyResource`, the Kubernetes API Server reacts by creating a new, namespaced RESTful resource path. For now, non-namespaced objects are not supported. As with existing built-in objects, deleting a namespace deletes all custom objects in that namespace. `ThirdPartyResources` themselves are non-namespaced and are available to all namespaces.
|
||||
|
||||
For example, if a save the following `ThirdPartyResource` to `resource.yaml`:
|
||||
|
||||
```yaml
|
||||
apiVersion: extensions/v1beta1
|
||||
kind: ThirdPartyResource
|
||||
metadata:
|
||||
name: cron-tab.stable.example.com
|
||||
description: "A specification of a Pod to run on a cron style schedule"
|
||||
versions:
|
||||
- name: v1
|
||||
```
|
||||
|
||||
And create it:
|
||||
|
||||
```shell
|
||||
$ kubectl create -f resource.yaml
|
||||
thirdpartyresource "cron-tab.stable.example.com" created
|
||||
```
|
||||
|
||||
Then a new RESTful API endpoint is created at:
|
||||
|
||||
`/apis/stable.example.com/v1/namespaces/<namespace>/crontabs/...`
|
||||
|
||||
This endpoint URL can then be used to create and manage custom objects.
|
||||
|
||||
## Creating Custom Objects
|
||||
|
||||
After the `ThirdPartyResource` object has been created you can create custom objects. Custom objects can contain custom fields. These fields can contain arbitrary JSON.
|
||||
In the following example, a `cronSpec` and `image` custom fields are set to the custom `CronTab` object. If you save the following YAML to `my-crontab.yaml`:
|
||||
|
||||
```yaml
|
||||
apiVersion: "stable.example.com/v1"
|
||||
kind: CronTab
|
||||
metadata:
|
||||
name: my-new-cron-object
|
||||
cronSpec: "* * * * /5"
|
||||
image: my-awesome-cron-image
|
||||
```
|
||||
|
||||
and create it:
|
||||
|
||||
```shell
|
||||
$ kubectl create -f my-crontab.yaml
|
||||
crontab "my-new-cron-object" created
|
||||
```
|
||||
|
||||
You can then manage our `CronTab` objects using kubectl. Note that resource names are not case-sensitive when using kubectl:
|
||||
|
||||
```shell
|
||||
$ kubectl get crontab
|
||||
NAME LABELS DATA
|
||||
my-new-cron-object <none> {"apiVersion":"stable.example.com/v1","cronSpec":"...
|
||||
```
|
||||
|
||||
You can also view the raw JSON data. Here you can see that it contains the custom `cronSpec` and `image` fields from the yaml you used to create it:
|
||||
|
||||
```yaml
|
||||
$ kubectl get crontab -o json
|
||||
{
|
||||
"kind": "List",
|
||||
"apiVersion": "v1",
|
||||
"metadata": {},
|
||||
"items": [
|
||||
{
|
||||
"apiVersion": "stable.example.com/v1",
|
||||
"cronSpec": "* * * * /5",
|
||||
"image": "my-awesome-cron-image",
|
||||
"kind": "CronTab",
|
||||
"metadata": {
|
||||
"creationTimestamp": "2016-09-29T04:59:00Z",
|
||||
"name": "my-new-cron-object",
|
||||
"namespace": "default",
|
||||
"resourceVersion": "12601503",
|
||||
"selfLink": "/apis/stable.example.com/v1/namespaces/default/crontabs/my-new-cron-object",
|
||||
"uid": "6f65e7a3-8601-11e6-a23e-42010af0000c"
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
Reference in New Issue
Block a user