whentimeslows/website
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Merge remote-tracking branch 'upstream/master' into release-1.6

Browse Source
This commit is contained in:
Devin Donnelly
2017-02-28 14:33:19 -08:00
parent 86df553c4b 4bb9a3a6af
commit 9a96256e49
15 changed files with 497 additions and 547 deletions
Download Patch File Download Diff File Expand all files Collapse all files
_data/concepts.yml
+1
View File
@@ -35,6 +35,7 @@ toc:
- title: Configuration
section:
- docs/concepts/configuration/container-command-args.md
- docs/concepts/configuration/manage-compute-resources-container.md
- title: Policies
section:
_data/tasks.yml
+1 -1
View File
@@ -3,7 +3,7 @@ abstract: "Step-by-step instructions for performing operations with Kubernetes."
toc:
- docs/tasks/index.md
- title: Using the Kubectl Command-Line
- title: Using the kubectl Command-Line
section:
- docs/tasks/kubectl/list-all-running-container-images.md
- docs/tasks/kubectl/get-shell-running-container.md
docs/admin/kube-scheduler.md
-1
View File
@@ -36,7 +36,6 @@ DynamicKubeletConfig=true|false (ALPHA - default=false)
DynamicVolumeProvisioning=true|false (ALPHA - default=true)
ExperimentalHostUserNamespaceDefaulting=true|false (ALPHA - default=false)
StreamingProxyRedirects=true|false (ALPHA - default=false)
--google-json-key string The Google Cloud Platform Service Account JSON Key to use for authentication.
--hard-pod-affinity-symmetric-weight int RequiredDuringScheduling affinity is not symmetric, but there is an implicit PreferredDuringScheduling affinity rule corresponding to every RequiredDuringScheduling affinity rule. --hard-pod-affinity-symmetric-weight represents the weight of implicit PreferredDuringScheduling affinity rule. (default 1)
--kube-api-burst int32 Burst to use while talking with Kubernetes apiserver (default 100)
--kube-api-content-type string Content type of requests sent to apiserver. (default "application/vnd.kubernetes.protobuf")
docs/admin/kubeadm.md
+3 -1
View File
@@ -31,7 +31,7 @@ server, as well as an additional kubeconfig file for administration.
controller manager and scheduler, and placing them in
`/etc/kubernetes/manifests`. The kubelet watches this directory for static
resources to create on startup. These are the core components of Kubernetes, and
once they are up and running we can use `kubectl` to set up/manage any
once they are up and running we can use `kubectl` to set up or manage any
additional components.
1. kubeadm installs any add-on components, such as DNS or discovery, via the API
@@ -259,6 +259,8 @@ These environment variables are a short-term solution, eventually they will be i
| `KUBE_ETCD_IMAGE` | `gcr.io/google_containers/etcd-<arch>:2.2.5` | The etcd container image to use. |
| `KUBE_REPO_PREFIX` | `gcr.io/google_containers` | The image prefix for all images that are used. |
If you want to use kubeadm with an http proxy, you may need to configure it to support http_proxy, https_proxy, or no_proxy.
## Releases and release notes
If you already have kubeadm installed and want to upgrade, run `apt-get update && apt-get upgrade` or `yum update` to get the latest version of kubeadm.
docs/concepts/configuration/manage-compute-resources-container.md
+430
View File
@@ -0,0 +1,430 @@
---
title: Managing Compute Resources for Containers
---
{% capture overview %}
When you specify a [Pod](/docs/user-guide/pods), you can optionally specify how
much CPU and memory (RAM) each Container needs. When Containers have resource
requests specified, the scheduler can make better decisions about which nodes to
place Pods on. And when Containers have their limits specified, contention for
resources on a node can be handled in a specified manner. For more details about
the difference between requests and limits, see
[Resource QoS](https://github.com/kubernetes/community/blob/master/contributors/design-proposals/resource-qos.md).
{% endcapture %}
{% capture body %}
## Resource types
*CPU* and *memory* are each a *resource type*. A resource type has a base unit.
CPU is specified in units of cores, and memory is specified in units of bytes.
CPU and memory are collectively referred to as *compute resources*, or just
*resources*. Compute
resources are measurable quantities that can be requested, allocated, and
consumed. They are distinct from
[API resources](/docs/api/). API resources, such as Pods and
[Services](/docs/user-guide/services) are objects that can be read and modified
through the Kubernetes API server.
## Resource requests and limits of Pod and Container
Each Container of a Pod can specify one or more of the following:
* `spec.containers[].resources.limits.cpu`
* `spec.containers[].resources.limits.memory`
* `spec.containers[].resources.requests.cpu`
* `spec.containers[].resources.requests.memory`
Although requests and limits can only be specified on individual Containers, it
is convenient to talk about Pod resource requests and limits. A
*Pod resource request/limit* for a particular resource type is the sum of the
resource requests/limits of that type for each Container in the Pod.
## Meaning of CPU
Limits and requests for CPU resources are measured in *cpu* units.
One cpu, in Kubernetes, is equivalent to:
- 1 AWS vCPU
- 1 GCP Core
- 1 Azure vCore
- 1 *Hyperthread* on a bare-metal Intel processor with Hyperthreading
Fractional requests are allowed. A Container with
`spec.containers[].resources.requests.cpu` of `0.5` is guaranteed half as much
CPU as one that asks for 1 CPU. The expression `0.1` is equivalent to the
expression `100m`, which can be read as "one hundred millicpu". Some people say
"one hundred millicores", and this is understood to mean the same thing. A
request with a decimal point, like `0.1`, is converted to `100m` by the API, and
precision finer than `1m` is not allowed. For this reason, the form `100m` might
be preferred.
CPU is always requested as an absolute quantity, never as a relative quantity;
0.1 is the same amount of CPU on a single-core, dual-core, or 48-core machine.
## Meaning of memory
Limits and requests for `memory` are measured in bytes. You can express memory as
a plain integer or as a fixed-point integer using one of these SI suffixes:
E, P, T, G, M, K. You can also use the power-of-two equivalents: Ei, Pi, Ti, Gi,
Mi, Ki. For example, the following represent roughly the same value:
```shell
128974848, 129e6, 129M, 123Mi
```
Here's an example.
The following Pod has two Containers. Each Container has a request of 0.25 cpu
and 64MiB (2<sup>26</sup> bytes) of memory Each Container has a limit of 0.5
cpu and 128MiB of memory. You can say the Pod has a request of 0.5 cpu and 128
MiB of memory, and a limit of 1 core and 256MiB of memory.
```yaml
apiVersion: v1
kind: Pod
metadata:
name: frontend
spec:
containers:
- name: db
image: mysql
resources:
requests:
memory: "64Mi"
cpu: "250m"
limits:
memory: "128Mi"
cpu: "500m"
- name: wp
image: wordpress
resources:
requests:
memory: "64Mi"
cpu: "250m"
limits:
memory: "128Mi"
cpu: "500m"
```
## How Pods with resource requests are scheduled
When you create a Pod, the Kubernetes scheduler selects a node for the Pod to
run on. Each node has a maximum capacity for each of the resource types: the
amount of CPU and memory it can provide for Pods. The scheduler ensures that,
for each resource type, the sum of the resource requests of the scheduled
Containers is less than the capacity of the node. Note that although actual memory
or CPU resource usage on nodes is very low, the scheduler still refuses to place
a Pod on a node if the capacity check fails. This protects against a resource
shortage on a node when resource usage later increases, for example, during a
daily peak in request rate.
## How Pods with resource limits are run
When the kubelet starts a Container of a Pod, it passes the CPU and memory limits
to the container runtime.
When using Docker:
- The `spec.containers[].resources.requests.cpu` is converted to its core value,
which is potentially fractional, and multiplied by 1024. This number is used
as the value of the
[`--cpu-shares`](https://docs.docker.com/engine/reference/run/#/cpu-share-constraint)
flag in the `docker run` command.
- The `spec.containers[].resources.limits.cpu` is converted to its millicore value,
multiplied by 100000, and then divided by 1000. This number is used as the value
of the [`--cpu-quota`](https://docs.docker.com/engine/reference/run/#/cpu-quota-constraint)
flag in the `docker run` command. he [`--cpu-period`] flag is set to 100000,
which represents the default 100ms period for measuring quota usage. The
kubelet enforces cpu limits if it is started with the
[`--cpu-cfs-quota`] flag set to true. As of Kubernetes version 1.2, this flag
defaults to true.
- The `spec.containers[].resources.limits.memory` is converted to an integer, and
used as the value of the
[`--memory`](https://docs.docker.com/engine/reference/run/#/user-memory-constraints)
flag in the `docker run` command.
If a Container exceeds its memory limit, it might be terminated. If it is
restartable, the kubelet will restart it, as with any other type of runtime
failure.
If a Container exceeds its memory request, it is likely that its Pod will
be evicted whenever the node runs out of memory.
A Container might or might not be allowed to exceed its CPU limit for extended
periods of time. However, it will not be killed for excessive CPU usage.
To determine whether a Container cannot be scheduled or is being killed due to
resource limits, see the
[Troubleshooting](#troubleshooting) section.
## Monitoring compute resource usage
The resource usage of a Pod is reported as part of the Pod status.
If [optional monitoring](http://releases.k8s.io/{{page.githubbranch}}/cluster/addons/cluster-monitoring/README.md)
is configured for your cluster, then Pod resource usage can be retrieved from
the monitoring system.
## Troubleshooting
### My Pods are pending with event message failedScheduling
If the scheduler cannot find any node where a Pod can fit, the Pod remains
unscheduled until a place can be found. An event is produced each time the
scheduler fails to find a place for the Pod, like this:
```shell
$ kubectl describe pod frontend | grep -A 3 Events
Events:
FirstSeen LastSeen Count From Subobject PathReason Message
36s 5s 6 {scheduler } FailedScheduling Failed for reason PodExceedsFreeCPU and possibly others
```
In the preceding example, the Pod named "frontend" fails to be scheduled due to
insufficient CPU resource on the node. Similar error messages can also suggest
failure due to insufficient memory (PodExceedsFreeMemory). In general, if a Pod
is pending with a message of this type, there are several things to try:
- Add more nodes to the cluster.
- Terminate unneeded Pods to make room for pending Pods.
- Check that the Pod is not larger than all the nodes. For example, if all the
nodes have a capacity of `cpu: 1`, then a Pod with a limit of `cpu: 1.1` will
never be scheduled.
You can check node capacities and amounts allocated with the
`kubectl describe nodes` command. For example:
```shell
$ kubectl.sh describe nodes e2e-test-minion-group-4lw4
Name: e2e-test-minion-group-4lw4
[ ... lines removed for clarity ...]
Capacity:
alpha.kubernetes.io/nvidia-gpu: 0
cpu: 2
memory: 7679792Ki
pods: 110
Allocatable:
alpha.kubernetes.io/nvidia-gpu: 0
cpu: 1800m
memory: 7474992Ki
pods: 110
[ ... lines removed for clarity ...]
Non-terminated Pods: (5 in total)
Namespace Name CPU Requests CPU Limits Memory Requests Memory Limits
--------- ---- ------------ ---------- --------------- -------------
kube-system fluentd-gcp-v1.38-28bv1 100m (5%) 0 (0%) 200Mi (2%) 200Mi (2%)
kube-system kube-dns-3297075139-61lj3 260m (13%) 0 (0%) 100Mi (1%) 170Mi (2%)
kube-system kube-proxy-e2e-test-... 100m (5%) 0 (0%) 0 (0%) 0 (0%)
kube-system monitoring-influxdb-grafana-v4-z1m12 200m (10%) 200m (10%) 600Mi (8%) 600Mi (8%)
kube-system node-problem-detector-v0.1-fj7m3 20m (1%) 200m (10%) 20Mi (0%) 100Mi (1%)
Allocated resources:
(Total limits may be over 100 percent, i.e., overcommitted.)
CPU Requests CPU Limits Memory Requests Memory Limits
------------ ---------- --------------- -------------
680m (34%) 400m (20%) 920Mi (12%) 1070Mi (14%)
```
In the preceding output, you can see that if a Pod requests more than 1120m
CPUs or 6.23Gi of memory, it will not fit on the node.
By looking at the `Pods` section, you can see which Pods are taking up space on
the node.
The amount of resources available to Pods is less than the node capacity, because
system daemons use a portion of the available resources. The `allocatable` field
[NodeStatus](/docs/resources-reference/v1.5/#nodestatus-v1)
gives the amount of resources that are available to Pods. For more information, see
[Node Allocatable Resources](https://github.com/kubernetes/community/blob/master/contributors/design-proposals/node-allocatable.md).
The [resource quota](/docs/admin/resourcequota/) feature can be configured
to limit the total amount of resources that can be consumed. If used in conjunction
with namespaces, it can prevent one team from hogging all the resources.
### My Container is terminated
Your Container might get terminated because it is resource-starved. To check
whether a Container is being killed because it is hitting a resource limit, call
`kubectl describe pod` on the Pod of interest:
```shell
[12:54:41] $ ./cluster/kubectl.sh describe pod simmemleak-hra99
Name: simmemleak-hra99
Namespace: default
Image(s): saadali/simmemleak
Node: kubernetes-node-tf0f/10.240.216.66
Labels: name=simmemleak
Status: Running
Reason:
Message:
IP: 10.244.2.75
Replication Controllers: simmemleak (1/1 replicas created)
Containers:
simmemleak:
Image: saadali/simmemleak
Limits:
cpu: 100m
memory: 50Mi
State: Running
Started: Tue, 07 Jul 2015 12:54:41 -0700
Last Termination State: Terminated
Exit Code: 1
Started: Fri, 07 Jul 2015 12:54:30 -0700
Finished: Fri, 07 Jul 2015 12:54:33 -0700
Ready: False
Restart Count: 5
Conditions:
Type Status
Ready False
Events:
FirstSeen LastSeen Count From SubobjectPath Reason Message
Tue, 07 Jul 2015 12:53:51 -0700 Tue, 07 Jul 2015 12:53:51 -0700 1 {scheduler } scheduled Successfully assigned simmemleak-hra99 to kubernetes-node-tf0f
Tue, 07 Jul 2015 12:53:51 -0700 Tue, 07 Jul 2015 12:53:51 -0700 1 {kubelet kubernetes-node-tf0f} implicitly required container POD pulled Pod container image "gcr.io/google_containers/pause:0.8.0" already present on machine
Tue, 07 Jul 2015 12:53:51 -0700 Tue, 07 Jul 2015 12:53:51 -0700 1 {kubelet kubernetes-node-tf0f} implicitly required container POD created Created with docker id 6a41280f516d
Tue, 07 Jul 2015 12:53:51 -0700 Tue, 07 Jul 2015 12:53:51 -0700 1 {kubelet kubernetes-node-tf0f} implicitly required container POD started Started with docker id 6a41280f516d
Tue, 07 Jul 2015 12:53:51 -0700 Tue, 07 Jul 2015 12:53:51 -0700 1 {kubelet kubernetes-node-tf0f} spec.containers{simmemleak} created Created with docker id 87348f12526a
```
In the preceding example, the `Restart Count: 5` indicates that the `simmemleak`
Container in the Pod was terminated and restarted five times.
You can call `get pod` with the `-o go-template=...` option to fetch the status
of previously terminated Containers:
```shell{% raw %}
[13:59:01] $ ./cluster/kubectl.sh get pod -o go-template='{{range.status.containerStatuses}}{{"Container Name: "}}{{.name}}{{"\r\nLastState: "}}{{.lastState}}{{end}}' simmemleak-60xbc
Container Name: simmemleak
LastState: map[terminated:map[exitCode:137 reason:OOM Killed startedAt:2015-07-07T20:58:43Z finishedAt:2015-07-07T20:58:43Z containerID:docker://0e4095bba1feccdfe7ef9fb6ebffe972b4b14285d5acdec6f0d3ae8a22fad8b2]]{% endraw %}
```
You can see that the Container was terminated because of `reason:OOM Killed`,
where `OOM` stands for Out Of Memory.
## Opaque integer resources (Alpha feature)
Kubernetes version 1.5 introduces Opaque integer resources. Opaque
integer resources allow cluster operators to advertise new node-level
resources that would be otherwise unknown to the system.
Users can consume these resources in Pod specs just like CPU and memory.
The scheduler takes care of the resource accounting so that no more than the
available amount is simultaneously allocated to Pods.
**Note:** Opaque integer resources are Alpha in Kubernetes version 1.5.
Only resource accounting is implemented; node-level isolation is still
under active development.
Opaque integer resources are resources that begin with the prefix
`pod.alpha.kubernetes.io/opaque-int-resource-`. The API server
restricts quantities of these resources to whole numbers. Examples of
_valid_ quantities are `3`, `3000m` and `3Ki`. Examples of _invalid_
quantities are `0.5` and `1500m`.
There are two steps required to use opaque integer resources. First, the
cluster operator must advertise a per-node opaque resource on one or more
nodes. Second, users must request the opaque resource in Pods.
To advertise a new opaque integer resource, the cluster operator should
submit a `PATCH` HTTP request to the API server to specify the available
quantity in the `status.capacity` for a node in the cluster. After this
operation, the node's `status.capacity` will include a new resource. The
`status.allocatable` field is updated automatically with the new resource
asynchronously by the kubelet. Note that because the scheduler uses the
node `status.allocatable` value when evaluating Pod fitness, there may
be a short delay between patching the node capacity with a new resource and the
first pod that requests the resource to be scheduled on that node.
**Example:**
Here is an HTTP request that advertises five "foo" resources on node `k8s-node-1`.
```http
PATCH /api/v1/nodes/k8s-node-1/status HTTP/1.1
Accept: application/json
Content-Type: application/json-patch+json
Host: k8s-master:8080
[
{
"op": "add",
"path": "/status/capacity/pod.alpha.kubernetes.io~1opaque-int-resource-foo",
"value": "5"
}
]
```
**Note**: In the preceding request, `~1` is the encoding for the character `/`
in the patch path. The operation path value in JSON-Patch is interpreted as a
JSON-Pointer. For more details, see
[IETF RFC 6901, section 3](https://tools.ietf.org/html/rfc6901#section-3).
To consume an opaque resource in a Pod, include the name of the opaque
resource as a key in the `spec.containers[].resources.requests` map.
The Pod is scheduled only if all of the resource requests are
satisfied, including cpu, memory and any opaque resources. The Pod will
remain in the `PENDING` state as long as the resource request cannot be met by
any node.
**Example:**
The Pod below requests 2 cpus and 1 "foo" (an opaque resource.)
```yaml
apiVersion: v1
kind: Pod
metadata:
name: my-pod
spec:
containers:
- name: my-container
image: myimage
resources:
requests:
cpu: 2
pod.alpha.kubernetes.io/opaque-int-resource-foo: 1
```
## Planned Improvements
Kubernetes version 1.5 only allows resource quantities to be specified on a
Container. It is planned to improve accounting for resources that are shared by
all Containers in a Pod, such as
[emptyDir volumes](/docs/user-guide/volumes/#emptydir).
Kubernetes version 1.5 only supports Container requests and limits for CPU and
memory. It is planned to add new resource types, including a node disk space
resource, and a framework for adding custom
[resource types](https://github.com/kubernetes/community/blob/{{page.githubbranch}}/contributors/design-proposals/resources.md).
Kubernetes supports overcommitment of resources by supporting multiple levels of
[Quality of Service](http://issue.k8s.io/168).
In Kubernetes version 1.5, one unit of CPU means different things on different
cloud providers, and on different machine types within the same cloud providers.
For example, on AWS, the capacity of a node is reported in
[ECUs](http://aws.amazon.com/ec2/faqs/), while in GCE it is reported in logical
cores. We plan to revise the definition of the cpu resource to allow for more
consistency across providers and platforms.
{% endcapture %}
{% capture whatsnext %}
* Get hands-on experience
[assigning CPU and RAM resources to a container](/docs/tasks/configure-pod-container/assign-cpu-ram-container/).
* [Container](/docs/api-reference/v1/definitions/#_v1_container)
* [ResourceRequirements](/docs/resources-reference/v1.5/#resourcerequirements-v1)
{% endcapture %}
{% include templates/concept.md %}
docs/getting-started-guides/centos/centos_manual_config.md
+3 -3
View File
@@ -61,9 +61,6 @@ echo "192.168.121.9 centos-master
* Edit /etc/kubernetes/config which will be the same on all hosts to contain:
```shell
# Comma separated list of nodes in the etcd cluster
KUBE_ETCD_SERVERS="--etcd-servers=http://centos-master:2379"
# logging to stderr means we get it in the systemd journal
KUBE_LOGTOSTDERR="--logtostderr=true"
@@ -111,6 +108,9 @@ KUBE_API_PORT="--port=8080"
# Port kubelets listen on
KUBELET_PORT="--kubelet-port=10250"
# Comma separated list of nodes in the etcd cluster
KUBE_ETCD_SERVERS="--etcd-servers=http://centos-master:2379"
# Address range to use for services
KUBE_SERVICE_ADDRESSES="--service-cluster-ip-range=10.254.0.0/16"
docs/getting-started-guides/gce.md
+4 -4
View File
@@ -134,10 +134,10 @@ $ kubectl get --all-namespaces services
should show a set of [services](/docs/user-guide/services) that look something like this:
```shell
NAMESPACE NAME CLUSTER_IP EXTERNAL_IP PORT(S) SELECTOR AGE
default kubernetes 10.0.0.1 <none> 443/TCP <none> 1d
kube-system kube-dns 10.0.0.2 <none> 53/TCP,53/UDP k8s-app=kube-dns 1d
kube-system kube-ui 10.0.0.3 <none> 80/TCP k8s-app=kube-ui 1d
NAMESPACE NAME CLUSTER_IP EXTERNAL_IP PORT(S) AGE
default kubernetes 10.0.0.1 <none> 443/TCP 1d
kube-system kube-dns 10.0.0.2 <none> 53/TCP,53/UDP 1d
kube-system kube-ui 10.0.0.3 <none> 80/TCP 1d
...
```
docs/getting-started-guides/kubeadm.md
+40
View File
@@ -195,6 +195,46 @@ Once a pod network has been installed, you can confirm that it is working by che
And once the `kube-dns` pod is up and running, you can continue by joining your nodes.
You may have trouble in the configuration if you see the following statuses
```
NAMESPACE NAME READY STATUS RESTARTS AGE
kube-system canal-node-f0lqp 2/3 RunContainerError 2 48s
kube-system canal-node-77d0h 2/3 CrashLoopBackOff 3 3m
kube-system kube-dns-2924299975-7q1vq 0/4 ContainerCreating 0 15m
```
The three statuses ```RunContainerError``` and ```CrashLoopBackOff``` and ```ContainerCreating``` are very common.
To help diagnose what happened, you can use the following command to check what is in the logs:
```bash
kubectl describe -n kube-system po {YOUR_POD_NAME}
```
Do not using kubectl logs. You will got the following error:
```
# kubectl logs -n kube-system canal-node-f0lqp
Error from server (BadRequest): the server rejected our request for an unknown reason (get pods canal-node-f0lqp)
```
The ```kubectl describe``` comand gives you more details about the logs
```
# kubectl describe -n kube-system po kube-dns-2924299975-1l2t7
2m 2m 1 {kubelet nac} spec.containers{flannel} Warning Failed Failed to start container with docker id 927e7ccdc32b with error: Error response from daemon: {"message":"chown /etc/resolv.conf: operation not permitted"}
```
Or
```
6m 1m 191 {kubelet nac} Warning FailedSync Error syncing pod, skipping: failed to "SetupNetwork" for "kube-dns-2924299975-1l2t7_kube-system" with SetupNetworkError: "Failed to setup network for pod \"kube-dns-2924299975-1l2t7_kube-system(dee8ef21-fbcb-11e6-ba19-38d547e0006a)\" using network plugins \"cni\": open /run/flannel/subnet.env: no such file or directory; Skipping pod"
```
You can then do some Google searches on the error messages, which may help you to find some solutions.
### (4/4) Joining your nodes
The nodes are where your workloads (containers and pods, etc) run.
docs/tasks/configure-pod-container/configure-liveness-readiness-probes.md
+1 -1
View File
@@ -255,7 +255,7 @@ In addition to command probes and HTTP probes, Kubernetes supports
{% capture whatsnext %}
* Learn more about
[Container Probes](/docs/user-guide/pod-states/#container-probes).
[Container Probes](/docs/concepts/workloads/pods/pod-lifecycle/#container-probes).
* Learn more about
[Health Checking section](/docs/user-guide/walkthrough/k8s201/#health-checking).
docs/tasks/index.md
+6
View File
@@ -6,12 +6,18 @@ This section of the Kubernetes documentation contains pages that
show how to do individual tasks. A task page shows how to do a
single thing, typically by giving a short sequence of steps.
#### Using the kubectl Command Line
* [Listing Alll Container Images Running in a Cluster](/docs/tasks/kubectl/list-all-running-container-images/)
* [Getting a Shell to a Running Container](/docs/tasks/kubectl/get-shell-running-container/)
#### Configuring Pods and Containers
* [Defining Environment Variables for a Container](/docs/tasks/configure-pod-container/define-environment-variable-container/)
* [Defining a Command and Arguments for a Container](/docs/tasks/configure-pod-container/define-command-argument-container/)
* [Assigning CPU and RAM Resources to a Container](/docs/tasks/configure-pod-container/assign-cpu-ram-container/)
* [Configuring a Pod to Use a Volume for Storage](/docs/tasks/configure-pod-container/configure-volume-storage/)
* [Configuring a Pod to Use a PersistentVolume for Storage](/docs/tasks/configure-pod-container/configure-persistent-volume-storage/)
* [Exposing Pod Information to Containers Through Environment Variables](/docs/tasks/configure-pod-container/environment-variable-expose-pod-information/)
* [Exposing Pod Information to Containers Using a DownwardAPIVolumeFile](/docs/tasks/configure-pod-container/downward-api-volume-expose-pod-information/)
* [Distributing Credentials Securely](/docs/tasks/configure-pod-container/distribute-credentials-secure/)
docs/tasks/kubectl/list-all-running-container-images.md
+1 -1
View File
@@ -1,5 +1,5 @@
---
title: Listing all Container images running in the cluster
title: Listing All Container Images Running in a Cluster
---
{% capture overview %}
docs/tutorials/index.md
+3 -3
View File
@@ -7,14 +7,14 @@ A tutorial shows how to accomplish a goal that is larger than a single
[task](/docs/tasks/). Typically a tutorial has several sections,
each of which has a sequence of steps.
#### Kubernetes Basics
* [Kubernetes Basics](/docs/tutorials/kubernetes-basics/) is an in-depth interactive tutorial that helps you understand the Kubernetes system and try out some basic Kubernetes features.
#### Stateless Applications
* [Online Training Course](https://www.udacity.com/course/scalable-microservices-with-kubernetes--ud615)
* [Hello Minikube](/docs/tutorials/stateless-application/hello-minikube/)
#### Stateless Applications
* [Running a Stateless Application Using a Deployment](/docs/tutorials/stateless-application/run-stateless-application-deployment/)
* [Using a Service to Access an Application in a Cluster](/docs/tutorials/stateless-application/expose-external-ip-address-service/)
docs/user-guide/compute-resources.md
+2 -364
View File
@@ -5,368 +5,6 @@ assignees:
title: Managing Compute Resources
---
* TOC
{:toc}
{% include user-guide-content-moved.md %}
When specifying a [pod](/docs/user-guide/pods), you can optionally specify how much CPU and memory (RAM) each
container needs. When containers have their resource requests specified, the scheduler is
able to make better decisions about which nodes to place pods on; and when containers have their
limits specified, contention for resources on a node can be handled in a specified manner. For
more details about the difference between requests and limits, please refer to
[Resource QoS](https://github.com/kubernetes/kubernetes/blob/{{page.githubbranch}}/docs/design/resource-qos.md).
*CPU* and *memory* are each a *resource type*. A resource type has a base unit. CPU is specified
in units of cores. Memory is specified in units of bytes.
CPU and RAM are collectively referred to as *compute resources*, or just *resources*. Compute
resources are measureable quantities which can be requested, allocated, and consumed. They are
distinct from [API resources](/docs/user-guide/working-with-resources). API resources, such as pods and
[services](/docs/user-guide/services) are objects that can be written to and retrieved from the Kubernetes API
server.
## Resource Requests and Limits of Pod and Container
Each container of a pod can optionally specify one or more of the following:
* `spec.containers[].resources.limits.cpu`
* `spec.containers[].resources.limits.memory`
* `spec.containers[].resources.requests.cpu`
* `spec.containers[].resources.requests.memory`.
Specifying resource requests and/or limits is optional. In some clusters, unset limits or requests
may be replaced with default values when a pod is created or updated. The default value depends on
how the cluster is configured. If the requests values are not specified, they are set to be equal
to the limits values by default. Please note that limits must always be greater than or equal to
requests.
Although requests/limits can only be specified on individual containers, it is convenient to talk
about pod resource requests/limits. A *pod resource request/limit* for a particular resource
type is the sum of the resource requests/limits of that type for each container in the pod, with
unset values treated as zero (or equal to default values in some cluster configurations).
### Meaning of CPU
Limits and requests for `cpu` are measured in cpus.
One cpu, in Kubernetes, is equivalent to:
- 1 AWS vCPU
- 1 GCP Core
- 1 Azure vCore
- 1 *Hyperthread* on a bare-metal Intel processor with Hyperthreading
Fractional requests are allowed. A container with `spec.containers[].resources.requests.cpu` of `0.5` will
be guaranteed half as much CPU as one that asks for `1`. The expression `0.1` is equivalent to the expression
`100m`, which can be read as "one hundred millicpu" (some may say "one hundred millicores", and this is understood
to mean the same thing when talking about Kubernetes). A request with a decimal point, like `0.1` is converted to
`100m` by the API, and precision finer than `1m` is not allowed. For this reason, the form `100m` may be preferred.
CPU is always requested as an absolute quantity, never as a relative quantity; 0.1 is the same amount of cpu on a single
core, dual core, or 48 core machine.
# Meaning of Memory
Limits and requests for `memory` are measured in bytes.
Memory can be expressed a plain integer or as fixed-point integers with one of these SI suffixes (E, P, T, G, M, K)
or their power-of-two equivalents (Ei, Pi, Ti, Gi, Mi, Ki). For example, the following represent roughly the same value:
`128974848`, `129e6`, `129M` , `123Mi`.
### Example
The following pod has two containers. Each has a request of 0.25 core of cpu and 64MiB
(2<sup>26</sup> bytes) of memory and a limit of 0.5 core of cpu and 128MiB of memory. The pod can
be said to have a request of 0.5 core and 128 MiB of memory and a limit of 1 core and 256MiB of
memory.
```yaml
apiVersion: v1
kind: Pod
metadata:
name: frontend
spec:
containers:
- name: db
image: mysql
resources:
requests:
memory: "64Mi"
cpu: "250m"
limits:
memory: "128Mi"
cpu: "500m"
- name: wp
image: wordpress
resources:
requests:
memory: "64Mi"
cpu: "250m"
limits:
memory: "128Mi"
cpu: "500m"
```
## How Pods with Resource Requests are Scheduled
When a pod is created, the Kubernetes scheduler selects a node for the pod to
run on. Each node has a maximum capacity for each of the resource types: the
amount of CPU and memory it can provide for pods. The scheduler ensures that,
for each resource type (CPU and memory), the sum of the resource requests of the
containers scheduled to the node is less than the capacity of the node. Note
that although actual memory or CPU resource usage on nodes is very low, the
scheduler will still refuse to place pods onto nodes if the capacity check
fails. This protects against a resource shortage on a node when resource usage
later increases, such as due to a daily peak in request rate.
## How Pods with Resource Limits are Run
When kubelet starts a container of a pod, it passes the CPU and memory limits to the container
runner (Docker or rkt).
When using Docker:
- The `spec.containers[].resources.requests.cpu` is converted to its core value (potentially fractional),
and multiplied by 1024, and used as the value of the [`--cpu-shares`](https://docs.docker.com/engine/reference/run/#/cpu-share-constraint)
flag to the `docker run` command.
- The `spec.containers[].resources.limits.cpu` is converted to its millicore value,
multiplied by 100000, and then divided by 1000, and used as the value of the [`--cpu-quota`](
https://docs.docker.com/engine/reference/run/#/cpu-quota-constraint) flag to the `docker run`
command. The [`--cpu-period`] flag is set to 100000 which represents the default 100ms period
for measuring quota usage. The kubelet enforces cpu limits if it was started with the
[`--cpu-cfs-quota`] flag set to true. As of version 1.2, this flag will now default to true.
- The `spec.containers[].resources.limits.memory` is converted to an integer, and used as the value
of the [`--memory`](https://docs.docker.com/engine/reference/run/#/user-memory-constraints) flag
to the `docker run` command.
**TODO: document behavior for rkt**
If a container exceeds its memory limit, it may be terminated. If it is restartable, it will be
restarted by kubelet, as will any other type of runtime failure.
A container may or may not be allowed to exceed its CPU limit for extended periods of time.
However, it will not be killed for excessive CPU usage.
To determine if a container cannot be scheduled or is being killed due to resource limits, see the
"Troubleshooting" section below.
## Monitoring Compute Resource Usage
The resource usage of a pod is reported as part of the Pod status.
If [optional monitoring](http://releases.k8s.io/{{page.githubbranch}}/cluster/addons/cluster-monitoring/README.md) is configured for your cluster,
then pod resource usage can be retrieved from the monitoring system.
## Troubleshooting
### My pods are pending with event message failedScheduling
If the scheduler cannot find any node where a pod can fit, then the pod will remain unscheduled
until a place can be found. An event will be produced each time the scheduler fails to find a
place for the pod, like this:
```shell
$ kubectl describe pod frontend | grep -A 3 Events
Events:
FirstSeen LastSeen Count From Subobject PathReason Message
36s 5s 6 {scheduler } FailedScheduling Failed for reason PodExceedsFreeCPU and possibly others
```
In the case shown above, the pod "frontend" fails to be scheduled due to insufficient
CPU resource on the node. Similar error messages can also suggest failure due to insufficient
memory (PodExceedsFreeMemory). In general, if a pod or pods are pending with this message and
alike, then there are several things to try:
- Add more nodes to the cluster.
- Terminate unneeded pods to make room for pending pods.
- Check that the pod is not larger than all the nodes. For example, if all the nodes
have a capacity of `cpu: 1`, then a pod with a limit of `cpu: 1.1` will never be scheduled.
You can check node capacities and amounts allocated with the `kubectl describe nodes` command.
For example:
```shell
$ kubectl describe nodes gke-cluster-4-386701dd-node-ww4p
Name: gke-cluster-4-386701dd-node-ww4p
[ ... lines removed for clarity ...]
Capacity:
cpu: 1
memory: 464Mi
pods: 40
Allocated resources (total requests):
cpu: 910m
memory: 2370Mi
pods: 4
[ ... lines removed for clarity ...]
Pods: (4 in total)
Namespace Name CPU(milliCPU) Memory(bytes)
frontend webserver-ffj8j 500 (50% of total) 2097152000 (50% of total)
kube-system fluentd-cloud-logging-gke-cluster-4-386701dd-node-ww4p 100 (10% of total) 209715200 (5% of total)
kube-system kube-dns-v8-qopgw 310 (31% of total) 178257920 (4% of total)
TotalResourceLimits:
CPU(milliCPU): 910 (91% of total)
Memory(bytes): 2485125120 (59% of total)
[ ... lines removed for clarity ...]
```
Here you can see from the `Allocated resources` section that that a pod which ask for more than
90 millicpus or more than 1341MiB of memory will not be able to fit on this node.
Looking at the `Pods` section, you can see which pods are taking up space on the node.
The [resource quota](/docs/admin/resourcequota/) feature can be configured
to limit the total amount of resources that can be consumed. If used in conjunction
with namespaces, it can prevent one team from hogging all the resources.
### My container is terminated
Your container may be terminated because it's resource-starved. To check if a container is being killed because it is hitting a resource limit, call `kubectl describe pod`
on the pod you are interested in:
```shell
[12:54:41] $ ./cluster/kubectl.sh describe pod simmemleak-hra99
Name: simmemleak-hra99
Namespace: default
Image(s): saadali/simmemleak
Node: kubernetes-node-tf0f/10.240.216.66
Labels: name=simmemleak
Status: Running
Reason:
Message:
IP: 10.244.2.75
Replication Controllers: simmemleak (1/1 replicas created)
Containers:
simmemleak:
Image: saadali/simmemleak
Limits:
cpu: 100m
memory: 50Mi
State: Running
Started: Tue, 07 Jul 2015 12:54:41 -0700
Last Termination State: Terminated
Exit Code: 1
Started: Fri, 07 Jul 2015 12:54:30 -0700
Finished: Fri, 07 Jul 2015 12:54:33 -0700
Ready: False
Restart Count: 5
Conditions:
Type Status
Ready False
Events:
FirstSeen LastSeen Count From SubobjectPath Reason Message
Tue, 07 Jul 2015 12:53:51 -0700 Tue, 07 Jul 2015 12:53:51 -0700 1 {scheduler } scheduled Successfully assigned simmemleak-hra99 to kubernetes-node-tf0f
Tue, 07 Jul 2015 12:53:51 -0700 Tue, 07 Jul 2015 12:53:51 -0700 1 {kubelet kubernetes-node-tf0f} implicitly required container POD pulled Pod container image "gcr.io/google_containers/pause:0.8.0" already present on machine
Tue, 07 Jul 2015 12:53:51 -0700 Tue, 07 Jul 2015 12:53:51 -0700 1 {kubelet kubernetes-node-tf0f} implicitly required container POD created Created with docker id 6a41280f516d
Tue, 07 Jul 2015 12:53:51 -0700 Tue, 07 Jul 2015 12:53:51 -0700 1 {kubelet kubernetes-node-tf0f} implicitly required container POD started Started with docker id 6a41280f516d
Tue, 07 Jul 2015 12:53:51 -0700 Tue, 07 Jul 2015 12:53:51 -0700 1 {kubelet kubernetes-node-tf0f} spec.containers{simmemleak} created Created with docker id 87348f12526a
```
The `Restart Count: 5` indicates that the `simmemleak` container in this pod was terminated and restarted 5 times.
You can call `get pod` with the `-o go-template=...` option to fetch the status of previously terminated containers:
```shell{% raw %}
[13:59:01] $ ./cluster/kubectl.sh get pod -o go-template='{{range.status.containerStatuses}}{{"Container Name: "}}{{.name}}{{"\r\nLastState: "}}{{.lastState}}{{end}}' simmemleak-60xbc
Container Name: simmemleak
LastState: map[terminated:map[exitCode:137 reason:OOM Killed startedAt:2015-07-07T20:58:43Z finishedAt:2015-07-07T20:58:43Z containerID:docker://0e4095bba1feccdfe7ef9fb6ebffe972b4b14285d5acdec6f0d3ae8a22fad8b2]]{% endraw %}
```
We can see that this container was terminated because `reason:OOM Killed`, where *OOM* stands for Out Of Memory.
## Opaque Integer Resources (Alpha Feature)
Kubernetes version 1.5 introduces Opaque integer resources. Opaque
integer resources allow cluster operators to advertise new node-level
resources that would be otherwise unknown to the system.
Users can consume these resources in pod specs just like CPU and memory.
The scheduler takes care of the resource accounting so that no more than the
available amount is simultaneously allocated to pods.
**Note:** Opaque integer resources are Alpha in Kubernetes version 1.5.
Only resource accounting is implemented; node-level isolation is still
under active development.
Opaque integer resources are resources that begin with the prefix
`pod.alpha.kubernetes.io/opaque-int-resource-`. The API server
restricts quantities of these resources to whole numbers. Examples of
_valid_ quantities are `3`, `3000m` and `3Ki`. Examples of _invalid_
quantities are `0.5` and `1500m`.
There are two steps required to use opaque integer resources. First, the
cluster operator must advertise a per-node opaque resource on one or more
nodes. Second, users must request the opaque resource in pods.
To advertise a new opaque integer resource, the cluster operator should
submit a `PATCH` HTTP request to the API server to specify the available
quantity in the `status.capacity` for a node in the cluster. After this
operation, the node's `status.capacity` will include a new resource. The
`status.allocatable` field is updated automatically with the new resource
asychronously by the Kubelet. Note that since the scheduler uses the
node `status.allocatable` value when evaluating pod fitness, there may
be a short delay between patching the node capacity with a new resource and the
first pod that requests the resource to be scheduled on that node.
**Example:**
The HTTP request below advertises 5 "foo" resources on node `k8s-node-1`.
_NOTE: `~1` is the encoding for the character `/` in the patch path.
The operation path value in JSON-Patch is interpreted as a JSON-Pointer.
For more details, please refer to
[IETF RFC 6901, section 3](https://tools.ietf.org/html/rfc6901#section-3)._
```http
PATCH /api/v1/nodes/k8s-node-1/status HTTP/1.1
Accept: application/json
Content-Type: application/json-patch+json
Host: k8s-master:8080
[
{
"op": "add",
"path": "/status/capacity/pod.alpha.kubernetes.io~1opaque-int-resource-foo",
"value": "5"
}
]
```
To consume opaque resources in pods, include the name of the opaque
resource as a key in the `spec.containers[].resources.requests` map.
The pod will be scheduled only if all of the resource requests are
satisfied (including cpu, memory and any opaque resources.) The pod will
remain in the `PENDING` state while the resource request cannot be met by any
node.
**Example:**
The pod below requests 2 cpus and 1 "foo" (an opaque resource.)
```yaml
apiVersion: v1
kind: Pod
metadata:
name: my-pod
spec:
containers:
- name: my-container
image: myimage
resources:
requests:
cpu: 2
pod.alpha.kubernetes.io/opaque-int-resource-foo: 1
```
## Planned Improvements
The current system only allows resource quantities to be specified on a container.
It is planned to improve accounting for resources which are shared by all containers in a pod,
such as [EmptyDir volumes](/docs/user-guide/volumes/#emptydir).
The current system only supports container requests and limits for CPU and Memory.
It is planned to add new resource types, including a node disk space
resource, and a framework for adding custom [resource types](https://github.com/kubernetes/community/blob/{{page.githubbranch}}/contributors/design-proposals/resources.md).
Kubernetes supports overcommitment of resources by supporting multiple levels of [Quality of Service](http://issue.k8s.io/168).
Currently, one unit of CPU means different things on different cloud providers, and on different
machine types within the same cloud providers. For example, on AWS, the capacity of a node
is reported in [ECUs](http://aws.amazon.com/ec2/faqs/), while in GCE it is reported in logical
cores. We plan to revise the definition of the cpu resource to allow for more consistency
across providers and platforms.
[Managing Compute Resources for Containers](/docs/concepts/configuration/manage-compute-resources-container/)
docs/user-guide/pods/multi-container.md
+2 -168
View File
@@ -4,172 +4,6 @@ assignees:
title: Creating Multi-Container Pods
---
* TOC
{:toc}
{% include user-guide-content-moved.md %}
A pod is a group of containers that are scheduled
onto the same host. Pods serve as units of scheduling, deployment, and
horizontal scaling/replication. Pods share fate, and share some resources, such
as storage volumes and IP addresses.
## Creating a pod
Multi-container pods must be created with the `create` command. Properties
are passed to the command as a YAML- or JSON-formatted configuration file.
The `create` command can be used to create a pod directly, or it can create
a pod or pods through a `Deployment`. It is highly recommended that
you use a
[Deployment](/docs/user-guide/deployments/)
to create your pods. It watches for failed pods and will start up
new pods as required to maintain the specified number.
If you don't want a Deployment to monitor your pod (e.g. your pod
is writing non-persistent data which won't survive a restart, or your pod is
intended to be very short-lived), you can create a pod directly with the
`create` command.
### Using `create`
Note: We recommend using a
[Deployment](/docs/user-guide/deployments/)
to create pods. You should use the instructions below only if you don't want
to create a Deployment.
If your pod will contain more than one container, or if you don't want to
create a Deployment to manage your pod, use the
`kubectl create` command and pass a pod specification as a JSON- or
YAML-formatted configuration file.
```shell
$ kubectl create -f FILE
```
Where:
* `-f FILE` or `--filename FILE` is the name of a
[pod configuration file](#pod-configuration-file) in either JSON or YAML
format.
A successful create request returns the pod name. Use the
[`kubectl get`](#viewing_a_pod) command to view status after creation.
### Pod configuration file
A pod configuration file specifies required information about the pod.
It can be formatted as YAML or as JSON, and supports the following fields:
{% capture tabspec %}configfiles
JSON,json,pod-config.json,/docs/user-guide/pods/pod-config.json
YAML,yaml,pod-config.yaml,/docs/user-guide/pods/pod-config.yaml{% endcapture %}
{% include tabs.html %}
Required fields are:
* `kind`: Always `Pod`.
* `apiVersion`: Currently `v1`.
* `metadata`: An object containing:
* `name`: Required if `generateName` is not specified. The name of this pod.
It must be an
[RFC1035](https://www.ietf.org/rfc/rfc1035.txt) compatible value and be
unique within the namespace.
* `labels`: Optional. Labels are arbitrary key:value pairs that can be used
by
[Deployment](/docs/user-guide/deployments/)
and [services](/docs/user-guide/services/) for grouping and targeting
pods.
* `generateName`: Required if `name` is not set. A prefix to use to generate
a unique name. Has the same validation rules as `name`.
* `namespace`: Required. The namespace of the pod.
* `annotations`: Optional. A map of string keys and values that can be used
by external tooling to store and retrieve arbitrary metadata about
objects.
* `spec`: The pod specification. See [The `spec` schema](#the_spec_schema) for
details.
### The `spec` schema
A full description of the `spec` schema is contained in the
[Kubernetes API reference](/docs/api-reference/v1/definitions/#_v1_podspec).
The following fields are required or commonly used in the `spec` schema:
{% capture tabspec %}specfiles
JSON,json,pod-spec-common.json,/docs/user-guide/pods/pod-spec-common.json
YAML,yaml,pod-spec-common.yaml,/docs/user-guide/pods/pod-spec-common.yaml{% endcapture %}
{% include tabs.html %}
#### `containers[]`
A list of containers belonging to the pod. Containers cannot be added or removed once the pod is created, and there must be at least one container in a pod.
The `containers` object **must contain**:
* `name`: Name of the container. It must be a DNS_LABEL and be unique within the pod. Cannot be updated.
* `image`: Docker image name.
The `containers` object **commonly contains** the following optional properties:
* `command[]`: The entrypoint array. Commands are not executed within a shell. The docker image's entrypoint is used if this is not provided. Cannot be updated.
* `args[]`: A command array containing arguments to the entrypoint. The docker image's `cmd` is used if this is not provided. Cannot be updated.
* `env[]`: A list of environment variables in key:value format to set in the container. Cannot be updated.
* `name`: The name of the environment variable; must be a `C_IDENTIFIER`.
* `value`: The value of the environment variable. Defaults to empty string.
* `imagePullPolicy`: The image pull policy. Accepted values are:
* `Always`
* `Never`
* `IfNotPresent`Defaults to `Always` if `:latest` tag is specified, or `IfNotPresent` otherwise. Cannot be updated.
* `ports[]`: A list of ports to expose from the container. Cannot be updated.
* `containerPort`: The port number to expose on the pod's IP address.
* `name`: The name for the port that can be referred to by services. Must be a `DNS_LABEL` and be unique without the pod.
* `protocol`: Protocol for the port. Must be UDP or TCP. Default is TCP.
* `resources`: The Compute resources required by this container. Contains:
* `cpu`: CPUs to reserve for each container. Default is whole CPUs; scale suffixes (e.g. `100m` for one hundred milli-CPUs) are supported. If the host does not have enough available resources, your pod will not be scheduled.
* `memory`: Memory to reserve for each container. Default is bytes; [binary scale suffixes](http://en.wikipedia.org/wiki/Binary_prefix) (e.g. `100Mi` for one hundred mebibytes) are supported. If the host does not have enough available resources, your pod will not be scheduled.Cannot be updated.
#### `restartPolicy`
Restart policy for all containers within the pod. Options are:
* `Always`
* `OnFailure`
* `Never`
#### `volumes[]`
A list of volumes that can be mounted by containers belonging to the pod. You must specify a `name` and a source for each volume. The container must also include a `volumeMount` with matching `name`. Source is one of:
* `emptyDir`: A temporary directory that shares a pod's lifetime. Contains:
* `medium`: The type of storage used to back the volume. Must be an empty string (default) or `Memory`.
* `hostPath`: A pre-existing host file or directory. This is generally used for privileged system daemons or other agents tied to the host. Contains:
* `path`: The path of the directory on the host.
* `secret`: Secret to populate volume. Secrets are used to hold sensitive information, such as passwords, OAuth tokens, and SSH keys. Learn more from [the docs on secrets](/docs/user-guide/secrets/). Contains:
* `secretName`: The name of a secret in the pod's namespace.
The `name` must be a DNS_LABEL and unique within the pod.
### Sample file
For example, the following configuration file creates two containers: a
`redis` key-value store image, and a `django` frontend image.
{% capture tabspec %}samplefiles
JSON,json,pod-sample.json,/docs/user-guide/pods/pod-sample.json
YAML,yaml,pod-sample.yaml,/docs/user-guide/pods/pod-sample.yaml{% endcapture %}
{% include tabs.html %}
## Viewing a pod
{% include_relative _viewing-a-pod.md %}
## Deleting a pod
If you created your pod directly with `kubectl create`, use `kubectl delete`:
```shell
$ kubectl delete pod NAME
```
A successful delete request returns the name of the deleted pod.
[Communicating Between Containers Running in the Same Pod](/docs/tasks/configure-pod-container/communicate-containers-same-pod/)
images/community_logos/mirantis_logo.png
BIN
View File
Binary file not shown.
Side by Side Swipe Overlay

Before

Width:  |  Height:  |  Size: 11 KiB

After

Width:  |  Height:  |  Size: 8.4 KiB