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Merge remote-tracking branch 'upstream/main' into dev-1.24

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Nate W
2022-03-28 08:48:23 -07:00
parent 6da9c34b2e df12f23ec4
commit 7c67921f3f
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content/en/docs/concepts/configuration/organize-cluster-access-kubeconfig.md
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@@ -148,7 +148,28 @@ File references on the command line are relative to the current working director
In `$HOME/.kube/config`, relative paths are stored relatively, and absolute paths
are stored absolutely.
## Proxy
You can configure `kubectl` to use proxy by setting `proxy-url` in the kubeconfig file, like:
```yaml
apiVersion: v1
kind: Config
proxy-url: https://proxy.host:3128
clusters:
- cluster:
name: development
users:
- name: developer
contexts:
- context:
name: development
```
## {{% heading "whatsnext" %}}
content/en/docs/concepts/containers/images.md
+12 -97
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@@ -29,8 +29,7 @@ and possibly a port number as well; for example: `fictional.registry.example:104
If you don't specify a registry hostname, Kubernetes assumes that you mean the Docker public registry.
After the image name part you can add a _tag_ (as also using with commands such
as `docker` and `podman`).
After the image name part you can add a _tag_ (in the same way you would when using with commands like `docker` or `podman`).
Tags let you identify different versions of the same series of images.
Image tags consist of lowercase and uppercase letters, digits, underscores (`_`),
@@ -91,7 +90,7 @@ the image's digest;
replace `<image-name>:<tag>` with `<image-name>@<digest>`
(for example, `image@sha256:45b23dee08af5e43a7fea6c4cf9c25ccf269ee113168c19722f87876677c5cb2`).
When using image tags, if the image registry were to change the code that the tag on that image represents, you might end up with a mix of Pods running the old and new code. An image digest uniquely identifies a specific version of the image, so Kubernetes runs the same code every time it starts a container with that image name and digest specified. Specifying an image fixes the code that you run so that a change at the registry cannot lead to that mix of versions.
When using image tags, if the image registry were to change the code that the tag on that image represents, you might end up with a mix of Pods running the old and new code. An image digest uniquely identifies a specific version of the image, so Kubernetes runs the same code every time it starts a container with that image name and digest specified. Specifying an image by digest fixes the code that you run so that a change at the registry cannot lead to that mix of versions.
There are third-party [admission controllers](/docs/reference/access-authn-authz/admission-controllers/)
that mutate Pods (and pod templates) when they are created, so that the
@@ -175,95 +174,11 @@ These options are explained in more detail below.
### Configuring nodes to authenticate to a private registry
If you run Docker on your nodes, you can configure the Docker container
runtime to authenticate to a private container registry.
Specific instructions for setting credentials depends on the container runtime and registry you chose to use. You should refer to your solution's documentation for the most accurate information.
This approach is suitable if you can control node configuration.
{{< note >}}
Default Kubernetes only supports the `auths` and `HttpHeaders` section in Docker configuration.
Docker credential helpers (`credHelpers` or `credsStore`) are not supported.
{{< /note >}}
Docker stores keys for private registries in the `$HOME/.dockercfg` or `$HOME/.docker/config.json` file. If you put the same file
in the search paths list below, kubelet uses it as the credential provider when pulling images.
* `{--root-dir:-/var/lib/kubelet}/config.json`
* `{cwd of kubelet}/config.json`
* `${HOME}/.docker/config.json`
* `/.docker/config.json`
* `{--root-dir:-/var/lib/kubelet}/.dockercfg`
* `{cwd of kubelet}/.dockercfg`
* `${HOME}/.dockercfg`
* `/.dockercfg`
{{< note >}}
You may have to set `HOME=/root` explicitly in the environment of the kubelet process.
{{< /note >}}
Here are the recommended steps to configuring your nodes to use a private registry. In this
example, run these on your desktop/laptop:
1. Run `docker login [server]` for each set of credentials you want to use. This updates `$HOME/.docker/config.json` on your PC.
1. View `$HOME/.docker/config.json` in an editor to ensure it contains only the credentials you want to use.
1. Get a list of your nodes; for example:
- if you want the names: `nodes=$( kubectl get nodes -o jsonpath='{range.items[*].metadata}{.name} {end}' )`
- if you want to get the IP addresses: `nodes=$( kubectl get nodes -o jsonpath='{range .items[*].status.addresses[?(@.type=="ExternalIP")]}{.address} {end}' )`
1. Copy your local `.docker/config.json` to one of the search paths list above.
- for example, to test this out: `for n in $nodes; do scp ~/.docker/config.json root@"$n":/var/lib/kubelet/config.json; done`
{{< note >}}
For production clusters, use a configuration management tool so that you can apply this
setting to all the nodes where you need it.
{{< /note >}}
Verify by creating a Pod that uses a private image; for example:
```shell
kubectl apply -f - <<EOF
apiVersion: v1
kind: Pod
metadata:
name: private-image-test-1
spec:
containers:
- name: uses-private-image
image: $PRIVATE_IMAGE_NAME
imagePullPolicy: Always
command: [ "echo", "SUCCESS" ]
EOF
```
```
pod/private-image-test-1 created
```
If everything is working, then, after a few moments, you can run:
```shell
kubectl logs private-image-test-1
```
and see that the command outputs:
```
SUCCESS
```
If you suspect that the command failed, you can run:
```shell
kubectl describe pods/private-image-test-1 | grep 'Failed'
```
In case of failure, the output is similar to:
```
Fri, 26 Jun 2015 15:36:13 -0700 Fri, 26 Jun 2015 15:39:13 -0700 19 {kubelet node-i2hq} spec.containers{uses-private-image} failed Failed to pull image "user/privaterepo:v1": Error: image user/privaterepo:v1 not found
```
You must ensure all nodes in the cluster have the same `.docker/config.json`. Otherwise, pods will run on
some nodes and fail to run on others. For example, if you use node autoscaling, then each instance
template needs to include the `.docker/config.json` or mount a drive that contains it.
All pods will have read access to images in any private registry once private
registry keys are added to the `.docker/config.json`.
For an example of configuring a private container image registry, see the
[Pull an Image from a Private Registry](/docs/tasks/configure-pod-container/pull-image-private-registry)
task. That example uses a private registry in Docker Hub.
### Interpretation of config.json {#config-json}
@@ -332,6 +247,7 @@ If now a container specifies an image `my-registry.io/images/subpath/my-image`
to be pulled, then the kubelet will try to download them from both
authentication sources if one of them fails.
### Pre-pulled images
{{< note >}}
@@ -362,6 +278,8 @@ Kubernetes supports specifying container image registry keys on a Pod.
#### Creating a Secret with a Docker config
You need to know the username, registry password and client email address for authenticating
to the registry, as well as its hostname.
Run the following command, substituting the appropriate uppercase values:
```shell
@@ -426,14 +344,13 @@ There are a number of solutions for configuring private registries. Here are so
common use cases and suggested solutions.
1. Cluster running only non-proprietary (e.g. open-source) images. No need to hide images.
- Use public images on the Docker hub.
- Use public images from a public registry
- No configuration required.
- Some cloud providers automatically cache or mirror public images, which improves availability and reduces the time to pull images.
1. Cluster running some proprietary images which should be hidden to those outside the company, but
visible to all cluster users.
- Use a hosted private [Docker registry](https://docs.docker.com/registry/).
- It may be hosted on the [Docker Hub](https://hub.docker.com/signup), or elsewhere.
- Manually configure .docker/config.json on each node as described above.
- Use a hosted private registry
- Manual configuration may be required on the nodes that need to access to private registry
- Or, run an internal private registry behind your firewall with open read access.
- No Kubernetes configuration is required.
- Use a hosted container image registry service that controls image access
@@ -450,8 +367,6 @@ common use cases and suggested solutions.
If you need access to multiple registries, you can create one secret for each registry.
Kubelet will merge any `imagePullSecrets` into a single virtual `.docker/config.json`
## {{% heading "whatsnext" %}}
content/en/docs/concepts/scheduling-eviction/assign-pod-node.md
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@@ -12,158 +12,181 @@ weight: 20
<!-- overview -->
You can constrain a {{< glossary_tooltip text="Pod" term_id="pod" >}} so that it can only run on particular set of
{{< glossary_tooltip text="Node(s)" term_id="node" >}}.
{{< glossary_tooltip text="node(s)" term_id="node" >}}.
There are several ways to do this and the recommended approaches all use
[label selectors](/docs/concepts/overview/working-with-objects/labels/) to facilitate the selection.
Generally such constraints are unnecessary, as the scheduler will automatically do a reasonable placement
(e.g. spread your pods across nodes so as not place the pod on a node with insufficient free resources, etc.)
but there are some circumstances where you may want to control which node the pod deploys to - for example to ensure
that a pod ends up on a machine with an SSD attached to it, or to co-locate pods from two different
(for example, spreading your Pods across nodes so as not place Pods on a node with insufficient free resources).
However, there are some circumstances where you may want to control which node
the Pod deploys to, for example, to ensure that a Pod ends up on a node with an SSD attached to it, or to co-locate Pods from two different
services that communicate a lot into the same availability zone.
<!-- body -->
You can use any of the following methods to choose where Kubernetes schedules
specific Pods:
* [nodeSelector](#nodeselector) field matching against [node labels](#built-in-node-labels)
* [Affinity and anti-affinity](#affinity-and-anti-affinity)
* [nodeName](#nodename) field
## Node labels {#built-in-node-labels}
Like many other Kubernetes objects, nodes have
[labels](/docs/concepts/overview/working-with-objects/labels/). You can [attach labels manually](/docs/tasks/configure-pod-container/assign-pods-nodes/#add-a-label-to-a-node).
Kubernetes also populates a standard set of labels on all nodes in a cluster. See [Well-Known Labels, Annotations and Taints](/docs/reference/labels-annotations-taints/)
for a list of common node labels.
{{<note>}}
The value of these labels is cloud provider specific and is not guaranteed to be reliable.
For example, the value of `kubernetes.io/hostname` may be the same as the node name in some environments
and a different value in other environments.
{{</note>}}
### Node isolation/restriction
Adding labels to nodes allows you to target Pods for scheduling on specific
nodes or groups of nodes. You can use this functionality to ensure that specific
Pods only run on nodes with certain isolation, security, or regulatory
properties.
If you use labels for node isolation, choose label keys that the {{<glossary_tooltip text="kubelet" term_id="kubelet">}}
cannot modify. This prevents a compromised node from setting those labels on
itself so that the scheduler schedules workloads onto the compromised node.
The [`NodeRestriction` admission plugin](/docs/reference/access-authn-authz/admission-controllers/#noderestriction)
prevents the kubelet from setting or modifying labels with a
`node-restriction.kubernetes.io/` prefix.
To make use of that label prefix for node isolation:
1. Ensure you are using the [Node authorizer](/docs/reference/access-authn-authz/node/) and have _enabled_ the `NodeRestriction` admission plugin.
2. Add labels with the `node-restriction.kubernetes.io/` prefix to your nodes, and use those labels in your [node selectors](#nodeselector).
For example, `example.com.node-restriction.kubernetes.io/fips=true` or `example.com.node-restriction.kubernetes.io/pci-dss=true`.
## nodeSelector
`nodeSelector` is the simplest recommended form of node selection constraint.
`nodeSelector` is a field of PodSpec. It specifies a map of key-value pairs. For the pod to be eligible
to run on a node, the node must have each of the indicated key-value pairs as labels (it can have
additional labels as well). The most common usage is one key-value pair.
You can add the `nodeSelector` field to your Pod specification and specify the
[node labels](#built-in-node-labels) you want the target node to have.
Kubernetes only schedules the Pod onto nodes that have each of the labels you
specify.
Let's walk through an example of how to use `nodeSelector`.
### Step Zero: Prerequisites
This example assumes that you have a basic understanding of Kubernetes pods and that you have [set up a Kubernetes cluster](/docs/setup/).
### Step One: Attach label to the node
Run `kubectl get nodes` to get the names of your cluster's nodes. Pick out the one that you want to add a label to, and then run `kubectl label nodes <node-name> <label-key>=<label-value>` to add a label to the node you've chosen. For example, if my node name is 'kubernetes-foo-node-1.c.a-robinson.internal' and my desired label is 'disktype=ssd', then I can run `kubectl label nodes kubernetes-foo-node-1.c.a-robinson.internal disktype=ssd`.
You can verify that it worked by re-running `kubectl get nodes --show-labels` and checking that the node now has a label. You can also use `kubectl describe node "nodename"` to see the full list of labels of the given node.
### Step Two: Add a nodeSelector field to your pod configuration
Take whatever pod config file you want to run, and add a nodeSelector section to it, like this. For example, if this is my pod config:
```yaml
apiVersion: v1
kind: Pod
metadata:
name: nginx
labels:
env: test
spec:
containers:
- name: nginx
image: nginx
```
Then add a nodeSelector like so:
{{< codenew file="pods/pod-nginx.yaml" >}}
When you then run `kubectl apply -f https://k8s.io/examples/pods/pod-nginx.yaml`,
the Pod will get scheduled on the node that you attached the label to. You can
verify that it worked by running `kubectl get pods -o wide` and looking at the
"NODE" that the Pod was assigned to.
## Interlude: built-in node labels {#built-in-node-labels}
In addition to labels you [attach](#step-one-attach-label-to-the-node), nodes come pre-populated
with a standard set of labels. See [Well-Known Labels, Annotations and Taints](/docs/reference/labels-annotations-taints/) for a list of these.
{{< note >}}
The value of these labels is cloud provider specific and is not guaranteed to be reliable.
For example, the value of `kubernetes.io/hostname` may be the same as the Node name in some environments
and a different value in other environments.
{{< /note >}}
## Node isolation/restriction
Adding labels to Node objects allows targeting pods to specific nodes or groups of nodes.
This can be used to ensure specific pods only run on nodes with certain isolation, security, or regulatory properties.
When using labels for this purpose, choosing label keys that cannot be modified by the kubelet process on the node is strongly recommended.
This prevents a compromised node from using its kubelet credential to set those labels on its own Node object,
and influencing the scheduler to schedule workloads to the compromised node.
The `NodeRestriction` admission plugin prevents kubelets from setting or modifying labels with a `node-restriction.kubernetes.io/` prefix.
To make use of that label prefix for node isolation:
1. Ensure you are using the [Node authorizer](/docs/reference/access-authn-authz/node/) and have _enabled_ the [NodeRestriction admission plugin](/docs/reference/access-authn-authz/admission-controllers/#noderestriction).
2. Add labels under the `node-restriction.kubernetes.io/` prefix to your Node objects, and use those labels in your node selectors.
For example, `example.com.node-restriction.kubernetes.io/fips=true` or `example.com.node-restriction.kubernetes.io/pci-dss=true`.
See [Assign Pods to Nodes](/docs/tasks/configure-pod-container/assign-pods-nodes) for more
information.
## Affinity and anti-affinity
`nodeSelector` provides a very simple way to constrain pods to nodes with particular labels. The affinity/anti-affinity
feature, greatly expands the types of constraints you can express. The key enhancements are
`nodeSelector` is the simplest way to constrain Pods to nodes with specific
labels. Affinity and anti-affinity expands the types of constraints you can
define. Some of the benefits of affinity and anti-affinity include:
1. The affinity/anti-affinity language is more expressive. The language offers more matching rules
besides exact matches created with a logical AND operation;
2. you can indicate that the rule is "soft"/"preference" rather than a hard requirement, so if the scheduler
can't satisfy it, the pod will still be scheduled;
3. you can constrain against labels on other pods running on the node (or other topological domain),
rather than against labels on the node itself, which allows rules about which pods can and cannot be co-located
* The affinity/anti-affinity language is more expressive. `nodeSelector` only
selects nodes with all the specified labels. Affinity/anti-affinity gives you
more control over the selection logic.
* You can indicate that a rule is *soft* or *preferred*, so that the scheduler
still schedules the Pod even if it can't find a matching node.
* You can constrain a Pod using labels on other Pods running on the node (or other topological domain),
instead of just node labels, which allows you to define rules for which Pods
can be co-located on a node.
The affinity feature consists of two types of affinity, "node affinity" and "inter-pod affinity/anti-affinity".
Node affinity is like the existing `nodeSelector` (but with the first two benefits listed above),
while inter-pod affinity/anti-affinity constrains against pod labels rather than node labels, as
described in the third item listed above, in addition to having the first and second properties listed above.
The affinity feature consists of two types of affinity:
* *Node affinity* functions like the `nodeSelector` field but is more expressive and
allows you to specify soft rules.
* *Inter-pod affinity/anti-affinity* allows you to constrain Pods against labels
on other Pods.
### Node affinity
Node affinity is conceptually similar to `nodeSelector` -- it allows you to constrain which nodes your
pod is eligible to be scheduled on, based on labels on the node.
Node affinity is conceptually similar to `nodeSelector`, allowing you to constrain which nodes your
Pod can be scheduled on based on node labels. There are two types of node
affinity:
There are currently two types of node affinity, called `requiredDuringSchedulingIgnoredDuringExecution` and
`preferredDuringSchedulingIgnoredDuringExecution`. You can think of them as "hard" and "soft" respectively,
in the sense that the former specifies rules that *must* be met for a pod to be scheduled onto a node (similar to
`nodeSelector` but using a more expressive syntax), while the latter specifies *preferences* that the scheduler
will try to enforce but will not guarantee. The "IgnoredDuringExecution" part of the names means that, similar
to how `nodeSelector` works, if labels on a node change at runtime such that the affinity rules on a pod are no longer
met, the pod continues to run on the node. In the future we plan to offer
`requiredDuringSchedulingRequiredDuringExecution` which will be identical to `requiredDuringSchedulingIgnoredDuringExecution`
except that it will evict pods from nodes that cease to satisfy the pods' node affinity requirements.
* `requiredDuringSchedulingIgnoredDuringExecution`: The scheduler can't
schedule the Pod unless the rule is met. This functions like `nodeSelector`,
but with a more expressive syntax.
* `preferredDuringSchedulingIgnoredDuringExecution`: The scheduler tries to
find a node that meets the rule. If a matching node is not available, the
scheduler still schedules the Pod.
Thus an example of `requiredDuringSchedulingIgnoredDuringExecution` would be "only run the pod on nodes with Intel CPUs"
and an example `preferredDuringSchedulingIgnoredDuringExecution` would be "try to run this set of pods in failure
zone XYZ, but if it's not possible, then allow some to run elsewhere".
{{<note>}}
In the preceding types, `IgnoredDuringExecution` means that if the node labels
change after Kubernetes schedules the Pod, the Pod continues to run.
{{</note>}}
Node affinity is specified as field `nodeAffinity` of field `affinity` in the PodSpec.
You can specify node affinities using the `.spec.affinity.nodeAffinity` field in
your Pod spec.
Here's an example of a pod that uses node affinity:
For example, consider the following Pod spec:
{{< codenew file="pods/pod-with-node-affinity.yaml" >}}
{{<codenew file="pods/pod-with-node-affinity.yaml">}}
This node affinity rule says the pod can only be placed on a node with a label whose key is
`kubernetes.io/e2e-az-name` and whose value is either `e2e-az1` or `e2e-az2`. In addition,
among nodes that meet that criteria, nodes with a label whose key is `another-node-label-key` and whose
value is `another-node-label-value` should be preferred.
In this example, the following rules apply:
You can see the operator `In` being used in the example. The new node affinity syntax supports the following operators: `In`, `NotIn`, `Exists`, `DoesNotExist`, `Gt`, `Lt`.
You can use `NotIn` and `DoesNotExist` to achieve node anti-affinity behavior, or use
[node taints](/docs/concepts/scheduling-eviction/taint-and-toleration/) to repel pods from specific nodes.
* The node *must* have a label with the key `kubernetes.io/e2e-az-name` and
the value is either `e2e-az1` or `e2e-az2`.
* The node *preferably* has a label with the key `another-node-label-key` and
the value `another-node-label-value`.
If you specify both `nodeSelector` and `nodeAffinity`, *both* must be satisfied for the pod
to be scheduled onto a candidate node.
You can use the `operator` field to specify a logical operator for Kubernetes to use when
interpreting the rules. You can use `In`, `NotIn`, `Exists`, `DoesNotExist`,
`Gt` and `Lt`.
If you specify multiple `nodeSelectorTerms` associated with `nodeAffinity` types, then the pod can be scheduled onto a node **if one of the** `nodeSelectorTerms` can be satisfied.
`NotIn` and `DoesNotExist` allow you to define node anti-affinity behavior.
Alternatively, you can use [node taints](/docs/concepts/scheduling-eviction/taint-and-toleration/)
to repel Pods from specific nodes.
If you specify multiple `matchExpressions` associated with `nodeSelectorTerms`, then the pod can be scheduled onto a node **only if all** `matchExpressions` is satisfied.
{{<note>}}
If you specify both `nodeSelector` and `nodeAffinity`, *both* must be satisfied
for the Pod to be scheduled onto a node.
If you remove or change the label of the node where the pod is scheduled, the pod won't be removed. In other words, the affinity selection works only at the time of scheduling the pod.
If you specify multiple `nodeSelectorTerms` associated with `nodeAffinity`
types, then the Pod can be scheduled onto a node if one of the specified `nodeSelectorTerms` can be
satisfied.
The `weight` field in `preferredDuringSchedulingIgnoredDuringExecution` is in the range 1-100. For each node that meets all of the scheduling requirements (resource request, RequiredDuringScheduling affinity expressions, etc.), the scheduler will compute a sum by iterating through the elements of this field and adding "weight" to the sum if the node matches the corresponding MatchExpressions. This score is then combined with the scores of other priority functions for the node. The node(s) with the highest total score are the most preferred.
If you specify multiple `matchExpressions` associated with a single `nodeSelectorTerms`,
then the Pod can be scheduled onto a node only if all the `matchExpressions` are
satisfied.
{{</note>}}
See [Assign Pods to Nodes using Node Affinity](/docs/tasks/configure-pod-container/assign-pods-nodes-using-node-affinity/)
for more information.
#### Node affinity weight
You can specify a `weight` between 1 and 100 for each instance of the
`preferredDuringSchedulingIgnoredDuringExecution` affinity type. When the
scheduler finds nodes that meet all the other scheduling requirements of the Pod, the
scheduler iterates through every preferred rule that the node satisfies and adds the
value of the `weight` for that expression to a sum.
The final sum is added to the score of other priority functions for the node.
Nodes with the highest total score are prioritized when the scheduler makes a
scheduling decision for the Pod.
For example, consider the following Pod spec:
{{<codenew file="pods/pod-with-affinity-anti-affinity.yaml">}}
If there are two possible nodes that match the
`requiredDuringSchedulingIgnoredDuringExecution` rule, one with the
`label-1:key-1` label and another with the `label-2:key-2` label, the scheduler
considers the `weight` of each node and adds the weight to the other scores for
that node, and schedules the Pod onto the node with the highest final score.
{{<note>}}
If you want Kubernetes to successfully schedule the Pods in this example, you
must have existing nodes with the `kubernetes.io/os=linux` label.
{{</note>}}
#### Node affinity per scheduling profile
{{< feature-state for_k8s_version="v1.20" state="beta" >}}
When configuring multiple [scheduling profiles](/docs/reference/scheduling/config/#multiple-profiles), you can associate
a profile with a Node affinity, which is useful if a profile only applies to a specific set of Nodes.
To do so, add an `addedAffinity` to the args of the [`NodeAffinity` plugin](/docs/reference/scheduling/config/#scheduling-plugins)
a profile with a node affinity, which is useful if a profile only applies to a specific set of nodes.
To do so, add an `addedAffinity` to the `args` field of the [`NodeAffinity` plugin](/docs/reference/scheduling/config/#scheduling-plugins)
in the [scheduler configuration](/docs/reference/scheduling/config/). For example:
```yaml
@@ -188,29 +211,41 @@ profiles:
The `addedAffinity` is applied to all Pods that set `.spec.schedulerName` to `foo-scheduler`, in addition to the
NodeAffinity specified in the PodSpec.
That is, in order to match the Pod, Nodes need to satisfy `addedAffinity` and the Pod's `.spec.NodeAffinity`.
That is, in order to match the Pod, nodes need to satisfy `addedAffinity` and
the Pod's `.spec.NodeAffinity`.
Since the `addedAffinity` is not visible to end users, its behavior might be unexpected to them. We
recommend to use node labels that have clear correlation with the profile's scheduler name.
Since the `addedAffinity` is not visible to end users, its behavior might be
unexpected to them. Use node labels that have a clear correlation to the
scheduler profile name.
{{< note >}}
The DaemonSet controller, which [creates Pods for DaemonSets](/docs/concepts/workloads/controllers/daemonset/#scheduled-by-default-scheduler)
is not aware of scheduling profiles. For this reason, it is recommended that you keep a scheduler profile, such as the
`default-scheduler`, without any `addedAffinity`. Then, the Daemonset's Pod template should use this scheduler name.
Otherwise, some Pods created by the Daemonset controller might remain unschedulable.
The DaemonSet controller, which [creates Pods for DaemonSets](/docs/concepts/workloads/controllers/daemonset/#scheduled-by-default-scheduler),
does not support scheduling profiles. When the DaemonSet controller creates
Pods, the default Kubernetes scheduler places those Pods and honors any
`nodeAffinity` rules in the DaemonSet controller.
{{< /note >}}
### Inter-pod affinity and anti-affinity
Inter-pod affinity and anti-affinity allow you to constrain which nodes your pod is eligible to be scheduled *based on
labels on pods that are already running on the node* rather than based on labels on nodes. The rules are of the form
"this pod should (or, in the case of anti-affinity, should not) run in an X if that X is already running one or more pods that meet rule Y".
Y is expressed as a LabelSelector with an optional associated list of namespaces; unlike nodes, because pods are namespaced
(and therefore the labels on pods are implicitly namespaced),
a label selector over pod labels must specify which namespaces the selector should apply to. Conceptually X is a topology domain
like node, rack, cloud provider zone, cloud provider region, etc. You express it using a `topologyKey` which is the
key for the node label that the system uses to denote such a topology domain; for example, see the label keys listed above
in the section [Interlude: built-in node labels](#built-in-node-labels).
Inter-pod affinity and anti-affinity allow you to constrain which nodes your
Pods can be scheduled on based on the labels of **Pods** already running on that
node, instead of the node labels.
Inter-pod affinity and anti-affinity rules take the form "this
Pod should (or, in the case of anti-affinity, should not) run in an X if that X
is already running one or more Pods that meet rule Y", where X is a topology
domain like node, rack, cloud provider zone or region, or similar and Y is the
rule Kubernetes tries to satisfy.
You express these rules (Y) as [label selectors](/docs/concepts/overview/working-with-objects/labels/#label-selectors)
with an optional associated list of namespaces. Pods are namespaced objects in
Kubernetes, so Pod labels also implicitly have namespaces. Any label selectors
for Pod labels should specify the namespaces in which Kubernetes should look for those
labels.
You express the topology domain (X) using a `topologyKey`, which is the key for
the node label that the system uses to denote the domain. For examples, see
[Well-Known Labels, Annotations and Taints](/docs/reference/labels-annotations-taints/).
{{< note >}}
Inter-pod affinity and anti-affinity require substantial amount of
@@ -219,76 +254,100 @@ not recommend using them in clusters larger than several hundred nodes.
{{< /note >}}
{{< note >}}
Pod anti-affinity requires nodes to be consistently labelled, in other words every node in the cluster must have an appropriate label matching `topologyKey`. If some or all nodes are missing the specified `topologyKey` label, it can lead to unintended behavior.
Pod anti-affinity requires nodes to be consistently labelled, in other words,
every node in the cluster must have an appropriate label matching `topologyKey`.
If some or all nodes are missing the specified `topologyKey` label, it can lead
to unintended behavior.
{{< /note >}}
As with node affinity, there are currently two types of pod affinity and anti-affinity, called `requiredDuringSchedulingIgnoredDuringExecution` and
`preferredDuringSchedulingIgnoredDuringExecution` which denote "hard" vs. "soft" requirements.
See the description in the node affinity section earlier.
An example of `requiredDuringSchedulingIgnoredDuringExecution` affinity would be "co-locate the pods of service A and service B
in the same zone, since they communicate a lot with each other"
and an example `preferredDuringSchedulingIgnoredDuringExecution` anti-affinity would be "spread the pods from this service across zones"
(a hard requirement wouldn't make sense, since you probably have more pods than zones).
#### Types of inter-pod affinity and anti-affinity
Inter-pod affinity is specified as field `podAffinity` of field `affinity` in the PodSpec.
And inter-pod anti-affinity is specified as field `podAntiAffinity` of field `affinity` in the PodSpec.
Similar to [node affinity](#node-affinity) are two types of Pod affinity and
anti-affinity as follows:
#### An example of a pod that uses pod affinity:
* `requiredDuringSchedulingIgnoredDuringExecution`
* `preferredDuringSchedulingIgnoredDuringExecution`
For example, you could use
`requiredDuringSchedulingIgnoredDuringExecution` affinity to tell the scheduler to
co-locate Pods of two services in the same cloud provider zone because they
communicate with each other a lot. Similarly, you could use
`preferredDuringSchedulingIgnoredDuringExecution` anti-affinity to spread Pods
from a service across multiple cloud provider zones.
To use inter-pod affinity, use the `affinity.podAffinity` field in the Pod spec.
For inter-pod anti-affinity, use the `affinity.podAntiAffinity` field in the Pod
spec.
#### Pod affinity example {#an-example-of-a-pod-that-uses-pod-affinity}
Consider the following Pod spec:
{{< codenew file="pods/pod-with-pod-affinity.yaml" >}}
The affinity on this pod defines one pod affinity rule and one pod anti-affinity rule. In this example, the
`podAffinity` is `requiredDuringSchedulingIgnoredDuringExecution`
while the `podAntiAffinity` is `preferredDuringSchedulingIgnoredDuringExecution`. The
pod affinity rule says that the pod can be scheduled onto a node only if that node is in the same zone
as at least one already-running pod that has a label with key "security" and value "S1". (More precisely, the pod is eligible to run
on node N if node N has a label with key `topology.kubernetes.io/zone` and some value V
such that there is at least one node in the cluster with key `topology.kubernetes.io/zone` and
value V that is running a pod that has a label with key "security" and value "S1".) The pod anti-affinity
rule says that the pod should not be scheduled onto a node if that node is in the same zone as a pod with
label having key "security" and value "S2". See the
This example defines one Pod affinity rule and one Pod anti-affinity rule. The
Pod affinity rule uses the "hard"
`requiredDuringSchedulingIgnoredDuringExecution`, while the anti-affinity rule
uses the "soft" `preferredDuringSchedulingIgnoredDuringExecution`.
The affinity rule says that the scheduler can only schedule a Pod onto a node if
the node is in the same zone as one or more existing Pods with the label
`security=S1`. More precisely, the scheduler must place the Pod on a node that has the
`topology.kubernetes.io/zone=V` label, as long as there is at least one node in
that zone that currently has one or more Pods with the Pod label `security=S1`.
The anti-affinity rule says that the scheduler should try to avoid scheduling
the Pod onto a node that is in the same zone as one or more Pods with the label
`security=S2`. More precisely, the scheduler should try to avoid placing the Pod on a node that has the
`topology.kubernetes.io/zone=R` label if there are other nodes in the
same zone currently running Pods with the `Security=S2` Pod label.
See the
[design doc](https://git.k8s.io/community/contributors/design-proposals/scheduling/podaffinity.md)
for many more examples of pod affinity and anti-affinity, both the `requiredDuringSchedulingIgnoredDuringExecution`
flavor and the `preferredDuringSchedulingIgnoredDuringExecution` flavor.
for many more examples of Pod affinity and anti-affinity.
The legal operators for pod affinity and anti-affinity are `In`, `NotIn`, `Exists`, `DoesNotExist`.
You can use the `In`, `NotIn`, `Exists` and `DoesNotExist` values in the
`operator` field for Pod affinity and anti-affinity.
In principle, the `topologyKey` can be any legal label-key. However,
for performance and security reasons, there are some constraints on topologyKey:
In principle, the `topologyKey` can be any allowed label key with the following
exceptions for performance and security reasons:
1. For pod affinity, empty `topologyKey` is not allowed in both `requiredDuringSchedulingIgnoredDuringExecution`
and `preferredDuringSchedulingIgnoredDuringExecution`.
2. For pod anti-affinity, empty `topologyKey` is also not allowed in both `requiredDuringSchedulingIgnoredDuringExecution`
and `preferredDuringSchedulingIgnoredDuringExecution`.
3. For `requiredDuringSchedulingIgnoredDuringExecution` pod anti-affinity, the admission controller `LimitPodHardAntiAffinityTopology` was introduced to limit `topologyKey` to `kubernetes.io/hostname`. If you want to make it available for custom topologies, you may modify the admission controller, or disable it.
4. Except for the above cases, the `topologyKey` can be any legal label-key.
* For Pod affinity and anti-affinity, an empty `topologyKey` field is not allowed in both `requiredDuringSchedulingIgnoredDuringExecution`
and `preferredDuringSchedulingIgnoredDuringExecution`.
* For `requiredDuringSchedulingIgnoredDuringExecution` Pod anti-affinity rules,
the admission controller `LimitPodHardAntiAffinityTopology` limits
`topologyKey` to `kubernetes.io/hostname`. You can modify or disable the
admission controller if you want to allow custom topologies.
In addition to `labelSelector` and `topologyKey`, you can optionally specify a list `namespaces`
of namespaces which the `labelSelector` should match against (this goes at the same level of the definition as `labelSelector` and `topologyKey`).
If omitted or empty, it defaults to the namespace of the pod where the affinity/anti-affinity definition appears.
All `matchExpressions` associated with `requiredDuringSchedulingIgnoredDuringExecution` affinity and anti-affinity
must be satisfied for the pod to be scheduled onto a node.
In addition to `labelSelector` and `topologyKey`, you can optionally specify a list
of namespaces which the `labelSelector` should match against using the
`namespaces` field at the same level as `labelSelector` and `topologyKey`.
If omitted or empty, `namespaces` defaults to the namespace of the Pod where the
affinity/anti-affinity definition appears.
#### Namespace selector
{{< feature-state for_k8s_version="v1.24" state="stable" >}}
Users can also select matching namespaces using `namespaceSelector`, which is a label query over the set of namespaces.
The affinity term is applied to the union of the namespaces selected by `namespaceSelector` and the ones listed in the `namespaces` field.
You can also select matching namespaces using `namespaceSelector`, which is a label query over the set of namespaces.
The affinity term is applied to namespaces selected by both `namespaceSelector` and the `namespaces` field.
Note that an empty `namespaceSelector` ({}) matches all namespaces, while a null or empty `namespaces` list and
null `namespaceSelector` means "this pod's namespace".
null `namespaceSelector` matches the namespace of the Pod where the rule is defined.
#### More Practical Use-cases
#### More practical use-cases
Interpod Affinity and AntiAffinity can be even more useful when they are used with higher
level collections such as ReplicaSets, StatefulSets, Deployments, etc. One can easily configure that a set of workloads should
Inter-pod affinity and anti-affinity can be even more useful when they are used with higher
level collections such as ReplicaSets, StatefulSets, Deployments, etc. These
rules allow you to configure that a set of workloads should
be co-located in the same defined topology, eg., the same node.
##### Always co-located in the same node
Take, for example, a three-node cluster running a web application with an
in-memory cache like redis. You could use inter-pod affinity and anti-affinity
to co-locate the web servers with the cache as much as possible.
In a three node cluster, a web application has in-memory cache such as redis. We want the web-servers to be co-located with the cache as much as possible.
Here is the yaml snippet of a simple redis deployment with three replicas and selector label `app=store`. The deployment has `PodAntiAffinity` configured to ensure the scheduler does not co-locate replicas on a single node.
In the following example Deployment for the redis cache, the replicas get the label `app=store`. The
`podAntiAffinity` rule tells the scheduler to avoid placing multiple replicas
with the `app=store` label on a single node. This creates each cache in a
separate node.
```yaml
apiVersion: apps/v1
@@ -320,7 +379,10 @@ spec:
image: redis:3.2-alpine
```
The below yaml snippet of the webserver deployment has `podAntiAffinity` and `podAffinity` configured. This informs the scheduler that all its replicas are to be co-located with pods that have selector label `app=store`. This will also ensure that each web-server replica does not co-locate on a single node.
The following Deployment for the web servers creates replicas with the label `app=web-store`. The
Pod affinity rule tells the scheduler to place each replica on a node that has a
Pod with the label `app=store`. The Pod anti-affinity rule tells the scheduler
to avoid placing multiple `app=web-store` servers on a single node.
```yaml
apiVersion: apps/v1
@@ -361,56 +423,37 @@ spec:
image: nginx:1.16-alpine
```
If we create the above two deployments, our three node cluster should look like below.
Creating the two preceding Deployments results in the following cluster layout,
where each web server is co-located with a cache, on three separate nodes.
| node-1 | node-2 | node-3 |
|:--------------------:|:-------------------:|:------------------:|
| *webserver-1* | *webserver-2* | *webserver-3* |
| *cache-1* | *cache-2* | *cache-3* |
As you can see, all the 3 replicas of the `web-server` are automatically co-located with the cache as expected.
```
kubectl get pods -o wide
```
The output is similar to this:
```
NAME READY STATUS RESTARTS AGE IP NODE
redis-cache-1450370735-6dzlj 1/1 Running 0 8m 10.192.4.2 kube-node-3
redis-cache-1450370735-j2j96 1/1 Running 0 8m 10.192.2.2 kube-node-1
redis-cache-1450370735-z73mh 1/1 Running 0 8m 10.192.3.1 kube-node-2
web-server-1287567482-5d4dz 1/1 Running 0 7m 10.192.2.3 kube-node-1
web-server-1287567482-6f7v5 1/1 Running 0 7m 10.192.4.3 kube-node-3
web-server-1287567482-s330j 1/1 Running 0 7m 10.192.3.2 kube-node-2
```
##### Never co-located in the same node
The above example uses `PodAntiAffinity` rule with `topologyKey: "kubernetes.io/hostname"` to deploy the redis cluster so that
no two instances are located on the same host.
See [ZooKeeper tutorial](/docs/tutorials/stateful-application/zookeeper/#tolerating-node-failure)
for an example of a StatefulSet configured with anti-affinity for high availability, using the same technique.
See the [ZooKeeper tutorial](/docs/tutorials/stateful-application/zookeeper/#tolerating-node-failure)
for an example of a StatefulSet configured with anti-affinity for high
availability, using the same technique as this example.
## nodeName
`nodeName` is the simplest form of node selection constraint, but due
to its limitations it is typically not used. `nodeName` is a field of
PodSpec. If it is non-empty, the scheduler ignores the pod and the
kubelet running on the named node tries to run the pod. Thus, if
`nodeName` is provided in the PodSpec, it takes precedence over the
above methods for node selection.
`nodeName` is a more direct form of node selection than affinity or
`nodeSelector`. `nodeName` is a field in the Pod spec. If the `nodeName` field
is not empty, the scheduler ignores the Pod and the kubelet on the named node
tries to place the Pod on that node. Using `nodeName` overrules using
`nodeSelector` or affinity and anti-affinity rules.
Some of the limitations of using `nodeName` to select nodes are:
- If the named node does not exist, the pod will not be run, and in
- If the named node does not exist, the Pod will not run, and in
some cases may be automatically deleted.
- If the named node does not have the resources to accommodate the
pod, the pod will fail and its reason will indicate why,
Pod, the Pod will fail and its reason will indicate why,
for example OutOfmemory or OutOfcpu.
- Node names in cloud environments are not always predictable or
stable.
Here is an example of a pod config file using the `nodeName` field:
Here is an example of a Pod spec using the `nodeName` field:
```yaml
apiVersion: v1
@@ -424,21 +467,16 @@ spec:
nodeName: kube-01
```
The above pod will run on the node kube-01.
The above Pod will only run on the node `kube-01`.
## {{% heading "whatsnext" %}}
[Taints](/docs/concepts/scheduling-eviction/taint-and-toleration/) allow a Node to *repel* a set of Pods.
The design documents for
[node affinity](https://git.k8s.io/community/contributors/design-proposals/scheduling/nodeaffinity.md)
and for [inter-pod affinity/anti-affinity](https://git.k8s.io/community/contributors/design-proposals/scheduling/podaffinity.md) contain extra background information about these features.
Once a Pod is assigned to a Node, the kubelet runs the Pod and allocates node-local resources.
The [topology manager](/docs/tasks/administer-cluster/topology-manager/) can take part in node-level
resource allocation decisions.
* Read more about [taints and tolerations](/docs/concepts/scheduling-eviction/taint-and-toleration/) .
* Read the design docs for [node affinity](https://git.k8s.io/community/contributors/design-proposals/scheduling/nodeaffinity.md)
and for [inter-pod affinity/anti-affinity](https://git.k8s.io/community/contributors/design-proposals/scheduling/podaffinity.md).
* Learn about how the [topology manager](/docs/tasks/administer-cluster/topology-manager/) takes part in node-level
resource allocation decisions.
* Learn how to use [nodeSelector](/docs/tasks/configure-pod-container/assign-pods-nodes/).
* Learn how to use [affinity and anti-affinity](/docs/tasks/configure-pod-container/assign-pods-nodes-using-node-affinity/).
content/en/docs/concepts/scheduling-eviction/pod-overhead.md
+1 -1
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@@ -72,7 +72,7 @@ spec:
runtimeClassName: kata-fc
containers:
- name: busybox-ctr
image: busybox
image: busybox:1.28
stdin: true
tty: true
resources:
content/en/docs/concepts/services-networking/ingress-controllers.md
+1 -1
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@@ -23,7 +23,7 @@ Kubernetes as a project supports and maintains [AWS](https://github.com/kubernet
{{% thirdparty-content %}}
* [AKS Application Gateway Ingress Controller](https://azure.github.io/application-gateway-kubernetes-ingress/) is an ingress controller that configures the [Azure Application Gateway](https://docs.microsoft.com/azure/application-gateway/overview).
* [AKS Application Gateway Ingress Controller](https://docs.microsoft.com/azure/application-gateway/tutorial-ingress-controller-add-on-existing?toc=https%3A%2F%2Fdocs.microsoft.com%2Fen-us%2Fazure%2Faks%2Ftoc.json&bc=https%3A%2F%2Fdocs.microsoft.com%2Fen-us%2Fazure%2Fbread%2Ftoc.json) is an ingress controller that configures the [Azure Application Gateway](https://docs.microsoft.com/azure/application-gateway/overview).
* [Ambassador](https://www.getambassador.io/) API Gateway is an [Envoy](https://www.envoyproxy.io)-based ingress
controller.
* [Apache APISIX ingress controller](https://github.com/apache/apisix-ingress-controller) is an [Apache APISIX](https://github.com/apache/apisix)-based ingress controller.
content/en/docs/concepts/services-networking/service.md
+39 -6
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@@ -109,12 +109,45 @@ field.
{{< /note >}}
Port definitions in Pods have names, and you can reference these names in the
`targetPort` attribute of a Service. This works even if there is a mixture
of Pods in the Service using a single configured name, with the same network
protocol available via different port numbers.
This offers a lot of flexibility for deploying and evolving your Services.
For example, you can change the port numbers that Pods expose in the next
version of your backend software, without breaking clients.
`targetPort` attribute of a Service. For example, we can bind the `targetPort`
of the Service to the Pod port in the following way:
```yaml
apiVersion: v1
kind: Pod
metadata:
name: nginx
labels:
app.kubernetes.io/name: proxy
spec:
containers:
- name: nginx
image: nginx:11.14.2
ports:
- containerPort: 80
name: http-web-svc
---
apiVersion: v1
kind: Service
metadata:
name: nginx-service
spec:
selector:
app.kubernetes.io/name: proxy
ports:
- name: name-of-service-port
protocol: TCP
port: 80
targetPort: http-web-svc
```
This works even if there is a mixture of Pods in the Service using a single
configured name, with the same network protocol available via different
port numbers. This offers a lot of flexibility for deploying and evolving
your Services. For example, you can change the port numbers that Pods expose
in the next version of your backend software, without breaking clients.
The default protocol for Services is TCP; you can also use any other
[supported protocol](#protocol-support).
content/en/docs/concepts/services-networking/topology-aware-hints.md
+6
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@@ -19,6 +19,12 @@ those network endpoints can be routed closer to where it originated.
For example, you can route traffic within a locality to reduce
costs, or to improve network performance.
{{< note >}}
The "topology-aware hints" feature is at Beta stage and it is **NOT** enabled
by default. To try out this feature, you have to enable the `TopologyAwareHints`
[feature gate](/docs/reference/command-line-tools-reference/feature-gates/).
{{< /note >}}
<!-- body -->
## Motivation
content/en/docs/concepts/storage/ephemeral-volumes.md
+10 -2
View File
@@ -107,7 +107,7 @@ metadata:
spec:
containers:
- name: my-frontend
image: busybox
image: busybox:1.28
volumeMounts:
- mountPath: "/data"
name: my-csi-inline-vol
@@ -125,9 +125,17 @@ driver. These attributes are specific to each driver and not
standardized. See the documentation of each CSI driver for further
instructions.
### CSI driver restrictions
{{< feature-state for_k8s_version="v1.21" state="deprecated" >}}
As a cluster administrator, you can use a [PodSecurityPolicy](/docs/concepts/policy/pod-security-policy/) to control which CSI drivers can be used in a Pod, specified with the
[`allowedCSIDrivers` field](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#podsecuritypolicyspec-v1beta1-policy).
{{< note >}}
PodSecurityPolicy is deprecated and will be removed in the Kubernetes v1.25 release.
{{< /note >}}
### Generic ephemeral volumes
{{< feature-state for_k8s_version="v1.23" state="stable" >}}
@@ -158,7 +166,7 @@ metadata:
spec:
containers:
- name: my-frontend
image: busybox
image: busybox:1.28
volumeMounts:
- mountPath: "/scratch"
name: scratch-volume
content/en/docs/concepts/storage/projected-volumes.md
+6 -3
View File
@@ -23,7 +23,7 @@ Currently, the following types of volume sources can be projected:
* [`secret`](/docs/concepts/storage/volumes/#secret)
* [`downwardAPI`](/docs/concepts/storage/volumes/#downwardapi)
* [`configMap`](/docs/concepts/storage/volumes/#configmap)
* `serviceAccountToken`
* [`serviceAccountToken`](#serviceaccounttoken)
All sources are required to be in the same namespace as the Pod. For more details,
see the [all-in-one volume](https://github.com/kubernetes/design-proposals-archive/blob/main/node/all-in-one-volume.md) design document.
@@ -45,6 +45,7 @@ parameters are nearly the same with two exceptions:
volume source. However, as illustrated above, you can explicitly set the `mode`
for each individual projection.
## serviceAccountToken projected volumes {#serviceaccounttoken}
When the `TokenRequestProjection` feature is enabled, you can inject the token
for the current [service account](/docs/reference/access-authn-authz/authentication/#service-account-tokens)
into a Pod at a specified path. For example:
@@ -52,8 +53,10 @@ into a Pod at a specified path. For example:
{{< codenew file="pods/storage/projected-service-account-token.yaml" >}}
The example Pod has a projected volume containing the injected service account
token. This token can be used by a Pod's containers to access the Kubernetes API
server. The `audience` field contains the intended audience of the
token. Containers in this Pod can use that token to access the Kubernetes API
server, authenticating with the identity of [the pod's ServiceAccount]
(/docs/tasks/configure-pod-container/configure-service-account/).
The `audience` field contains the intended audience of the
token. A recipient of the token must identify itself with an identifier specified
in the audience of the token, and otherwise should reject the token. This field
is optional and it defaults to the identifier of the API server.
content/en/docs/concepts/storage/storage-classes.md
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@@ -87,7 +87,7 @@ for provisioning PVs. This field must be specified.
You are not restricted to specifying the "internal" provisioners
listed here (whose names are prefixed with "kubernetes.io" and shipped
alongside Kubernetes). You can also run and specify external provisioners,
which are independent programs that follow a [specification](https://git.k8s.io/community/contributors/design-proposals/storage/volume-provisioning.md)
which are independent programs that follow a [specification](https://github.com/kubernetes/design-proposals-archive/blob/main/storage/volume-provisioning.md)
defined by Kubernetes. Authors of external provisioners have full discretion
over where their code lives, how the provisioner is shipped, how it needs to be
run, what volume plugin it uses (including Flex), etc. The repository
@@ -241,8 +241,8 @@ allowedTopologies:
- matchLabelExpressions:
- key: failure-domain.beta.kubernetes.io/zone
values:
- us-central1-a
- us-central1-b
- us-central-1a
- us-central-1b
```
## Parameters
content/en/docs/concepts/storage/volumes.md
+2 -2
View File
@@ -251,7 +251,7 @@ metadata:
spec:
containers:
- name: test
image: busybox
image: busybox:1.28
volumeMounts:
- name: config-vol
mountPath: /etc/config
@@ -1128,7 +1128,7 @@ spec:
fieldRef:
apiVersion: v1
fieldPath: metadata.name
image: busybox
image: busybox:1.28
command: [ "sh", "-c", "while [ true ]; do echo 'Hello'; sleep 10; done | tee -a /logs/hello.txt" ]
volumeMounts:
- name: workdir1
content/en/docs/concepts/workloads/controllers/cron-jobs.md
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@@ -69,7 +69,7 @@ takes you through this example in more detail).
# │ │ │ ┌───────────── month (1 - 12)
# │ │ │ │ ┌───────────── day of the week (0 - 6) (Sunday to Saturday;
# │ │ │ │ │ 7 is also Sunday on some systems)
# │ │ │ │ │
# │ │ │ │ │ OR sun, mon, tue, wed, thu, fri, sat
# │ │ │ │ │
# * * * * *
```
content/en/docs/concepts/workloads/controllers/daemonset.md
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@@ -107,7 +107,7 @@ If you do not specify either, then the DaemonSet controller will create Pods on
### Scheduled by default scheduler
{{< feature-state state="stable" for-kubernetes-version="1.17" >}}
{{< feature-state for_kubernetes_version="1.17" state="stable" >}}
A DaemonSet ensures that all eligible nodes run a copy of a Pod. Normally, the
node that a Pod runs on is selected by the Kubernetes scheduler. However,
content/en/docs/concepts/workloads/pods/_index.md
+1 -1
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@@ -180,7 +180,7 @@ spec:
spec:
containers:
- name: hello
image: busybox
image: busybox:1.28
command: ['sh', '-c', 'echo "Hello, Kubernetes!" && sleep 3600']
restartPolicy: OnFailure
# The pod template ends here
content/en/docs/reference/command-line-tools-reference/feature-gates.md
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@@ -63,7 +63,8 @@ different Kubernetes components.
| `AllowInsecureBackendProxy` | `true` | Beta | 1.17 | |
| `AnyVolumeDataSource` | `false` | Alpha | 1.18 | |
| `AppArmor` | `true` | Beta | 1.4 | |
| `ControllerManagerLeaderMigration` | `false` | Alpha | 1.21 | |
| `ControllerManagerLeaderMigration` | `false` | Alpha | 1.21 | 1.21 |
| `ControllerManagerLeaderMigration` | `true` | Beta | 1.22 | |
| `CPUManager` | `false` | Alpha | 1.8 | 1.9 |
| `CPUManager` | `true` | Beta | 1.10 | |
| `CPUManagerPolicyAlphaOptions` | `false` | Alpha | 1.23 | |
content/en/docs/reference/config-api/kubeadm-config.v1beta3.md
+108 -108
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@@ -156,15 +156,15 @@ configuration types to be used during a <code>kubeadm init</code> run.</p>
</span><span style="color:#bbb"> </span><span style="color:#000;font-weight:bold">effect</span>:<span style="color:#bbb"> </span><span style="color:#d14">&#34;NoSchedule&#34;</span><span style="color:#bbb">
</span><span style="color:#bbb"> </span><span style="color:#000;font-weight:bold">kubeletExtraArgs</span>:<span style="color:#bbb">
</span><span style="color:#bbb"> </span><span style="color:#000;font-weight:bold">v</span>:<span style="color:#bbb"> </span><span style="color:#099">4</span><span style="color:#bbb">
</span><span style="color:#bbb"></span><span style="color:#000;font-weight:bold">ignorePreflightErrors</span>:<span style="color:#bbb">
</span><span style="color:#bbb"></span>- IsPrivilegedUser<span style="color:#bbb">
</span><span style="color:#bbb"> </span><span style="color:#000;font-weight:bold">imagePullPolicy</span>:<span style="color:#bbb"> </span><span style="color:#d14">&#34;IfNotPresent&#34;</span><span style="color:#bbb">
</span><span style="color:#bbb"> </span><span style="color:#000;font-weight:bold">ignorePreflightErrors</span>:<span style="color:#bbb">
</span><span style="color:#bbb"> </span>- IsPrivilegedUser<span style="color:#bbb">
</span><span style="color:#bbb"> </span><span style="color:#000;font-weight:bold">imagePullPolicy</span>:<span style="color:#bbb"> </span><span style="color:#d14">&#34;IfNotPresent&#34;</span><span style="color:#bbb">
</span><span style="color:#bbb"></span><span style="color:#000;font-weight:bold">localAPIEndpoint</span>:<span style="color:#bbb">
</span><span style="color:#bbb"> </span><span style="color:#000;font-weight:bold">advertiseAddress</span>:<span style="color:#bbb"> </span><span style="color:#d14">&#34;10.100.0.1&#34;</span><span style="color:#bbb">
</span><span style="color:#bbb"> </span><span style="color:#000;font-weight:bold">bindPort</span>:<span style="color:#bbb"> </span><span style="color:#099">6443</span><span style="color:#bbb">
</span><span style="color:#bbb"></span><span style="color:#000;font-weight:bold">certificateKey</span>:<span style="color:#bbb"> </span><span style="color:#d14">&#34;e6a2eb8581237ab72a4f494f30285ec12a9694d750b9785706a83bfcbbbd2204&#34;</span><span style="color:#bbb">
</span><span style="color:#bbb"> </span><span style="color:#000;font-weight:bold">skipPhases</span>:<span style="color:#bbb">
</span><span style="color:#bbb"> </span>- addon/kube-proxy<span style="color:#bbb">
</span><span style="color:#bbb"></span><span style="color:#000;font-weight:bold">skipPhases</span>:<span style="color:#bbb">
</span><span style="color:#bbb"> </span>- addon/kube-proxy<span style="color:#bbb">
</span><span style="color:#bbb"></span>---<span style="color:#bbb">
</span><span style="color:#bbb"></span><span style="color:#000;font-weight:bold">apiVersion</span>:<span style="color:#bbb"> </span>kubeadm.k8s.io/v1beta3<span style="color:#bbb">
</span><span style="color:#bbb"></span><span style="color:#000;font-weight:bold">kind</span>:<span style="color:#bbb"> </span>ClusterConfiguration<span style="color:#bbb">
@@ -264,6 +264,109 @@ node only (e.g. the node ip).</p>
## `BootstrapToken` {#BootstrapToken}
**Appears in:**
- [InitConfiguration](#kubeadm-k8s-io-v1beta3-InitConfiguration)
<p>BootstrapToken describes one bootstrap token, stored as a Secret in the cluster</p>
<table class="table">
<thead><tr><th width="30%">Field</th><th>Description</th></tr></thead>
<tbody>
<tr><td><code>token</code> <B>[Required]</B><br/>
<a href="#BootstrapTokenString"><code>BootstrapTokenString</code></a>
</td>
<td>
<p><code>token</code> is used for establishing bidirectional trust between nodes and control-planes.
Used for joining nodes in the cluster.</p>
</td>
</tr>
<tr><td><code>description</code><br/>
<code>string</code>
</td>
<td>
<p><code>description</code> sets a human-friendly message why this token exists and what it's used
for, so other administrators can know its purpose.</p>
</td>
</tr>
<tr><td><code>ttl</code><br/>
<a href="https://pkg.go.dev/k8s.io/apimachinery/pkg/apis/meta/v1#Duration"><code>meta/v1.Duration</code></a>
</td>
<td>
<p><code>ttl</code> defines the time to live for this token. Defaults to <code>24h</code>.
<code>expires</code> and <code>ttl</code> are mutually exclusive.</p>
</td>
</tr>
<tr><td><code>expires</code><br/>
<a href="https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#time-v1-meta"><code>meta/v1.Time</code></a>
</td>
<td>
<p><code>expires</code> specifies the timestamp when this token expires. Defaults to being set
dynamically at runtime based on the <code>ttl</code>. <code>expires</code> and <code>ttl</code> are mutually exclusive.</p>
</td>
</tr>
<tr><td><code>usages</code><br/>
<code>[]string</code>
</td>
<td>
<p><code>usages</code> describes the ways in which this token can be used. Can by default be used
for establishing bidirectional trust, but that can be changed here.</p>
</td>
</tr>
<tr><td><code>groups</code><br/>
<code>[]string</code>
</td>
<td>
<p><code>groups</code> specifies the extra groups that this token will authenticate as when/if
used for authentication</p>
</td>
</tr>
</tbody>
</table>
## `BootstrapTokenString` {#BootstrapTokenString}
**Appears in:**
- [BootstrapToken](#BootstrapToken)
<p>BootstrapTokenString is a token of the format <code>abcdef.abcdef0123456789</code> that is used
for both validation of the practically of the API server from a joining node's point
of view and as an authentication method for the node in the bootstrap phase of
&quot;kubeadm join&quot;. This token is and should be short-lived.</p>
<table class="table">
<thead><tr><th width="30%">Field</th><th>Description</th></tr></thead>
<tbody>
<tr><td><code>-</code> <B>[Required]</B><br/>
<code>string</code>
</td>
<td>
<span class="text-muted">No description provided.</span></td>
</tr>
<tr><td><code>-</code> <B>[Required]</B><br/>
<code>string</code>
</td>
<td>
<span class="text-muted">No description provided.</span></td>
</tr>
</tbody>
</table>
## `ClusterConfiguration` {#kubeadm-k8s-io-v1beta3-ClusterConfiguration}
@@ -1237,106 +1340,3 @@ first alpha-numerically.</p>
</tbody>
</table>
## `BootstrapToken` {#BootstrapToken}
**Appears in:**
- [InitConfiguration](#kubeadm-k8s-io-v1beta3-InitConfiguration)
<p>BootstrapToken describes one bootstrap token, stored as a Secret in the cluster</p>
<table class="table">
<thead><tr><th width="30%">Field</th><th>Description</th></tr></thead>
<tbody>
<tr><td><code>token</code> <B>[Required]</B><br/>
<a href="#BootstrapTokenString"><code>BootstrapTokenString</code></a>
</td>
<td>
<p><code>token</code> is used for establishing bidirectional trust between nodes and control-planes.
Used for joining nodes in the cluster.</p>
</td>
</tr>
<tr><td><code>description</code><br/>
<code>string</code>
</td>
<td>
<p><code>description</code> sets a human-friendly message why this token exists and what it's used
for, so other administrators can know its purpose.</p>
</td>
</tr>
<tr><td><code>ttl</code><br/>
<a href="https://pkg.go.dev/k8s.io/apimachinery/pkg/apis/meta/v1#Duration"><code>meta/v1.Duration</code></a>
</td>
<td>
<p><code>ttl</code> defines the time to live for this token. Defaults to <code>24h</code>.
<code>expires</code> and <code>ttl</code> are mutually exclusive.</p>
</td>
</tr>
<tr><td><code>expires</code><br/>
<a href="https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#time-v1-meta"><code>meta/v1.Time</code></a>
</td>
<td>
<p><code>expires</code> specifies the timestamp when this token expires. Defaults to being set
dynamically at runtime based on the <code>ttl</code>. <code>expires</code> and <code>ttl</code> are mutually exclusive.</p>
</td>
</tr>
<tr><td><code>usages</code><br/>
<code>[]string</code>
</td>
<td>
<p><code>usages</code> describes the ways in which this token can be used. Can by default be used
for establishing bidirectional trust, but that can be changed here.</p>
</td>
</tr>
<tr><td><code>groups</code><br/>
<code>[]string</code>
</td>
<td>
<p><code>groups</code> specifies the extra groups that this token will authenticate as when/if
used for authentication</p>
</td>
</tr>
</tbody>
</table>
## `BootstrapTokenString` {#BootstrapTokenString}
**Appears in:**
- [BootstrapToken](#BootstrapToken)
<p>BootstrapTokenString is a token of the format <code>abcdef.abcdef0123456789</code> that is used
for both validation of the practically of the API server from a joining node's point
of view and as an authentication method for the node in the bootstrap phase of
&quot;kubeadm join&quot;. This token is and should be short-lived.</p>
<table class="table">
<thead><tr><th width="30%">Field</th><th>Description</th></tr></thead>
<tbody>
<tr><td><code>-</code> <B>[Required]</B><br/>
<code>string</code>
</td>
<td>
<span class="text-muted">No description provided.</span></td>
</tr>
<tr><td><code>-</code> <B>[Required]</B><br/>
<code>string</code>
</td>
<td>
<span class="text-muted">No description provided.</span></td>
</tr>
</tbody>
</table>
content/en/docs/reference/glossary/namespace.md
+1 -1
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@@ -4,7 +4,7 @@ id: namespace
date: 2018-04-12
full_link: /docs/concepts/overview/working-with-objects/namespaces
short_description: >
An abstraction used by Kubernetes to support multiple virtual clusters on the same physical cluster.
An abstraction used by Kubernetes to support isolation of groups of resources within a single cluster.
aka:
tags:
content/en/docs/reference/kubectl/cheatsheet.md
+10 -5
View File
@@ -39,6 +39,11 @@ complete -F __start_kubectl k
source <(kubectl completion zsh) # setup autocomplete in zsh into the current shell
echo "[[ $commands[kubectl] ]] && source <(kubectl completion zsh)" >> ~/.zshrc # add autocomplete permanently to your zsh shell
```
### A Note on --all-namespaces
Appending `--all-namespaces` happens frequently enough where you should be aware of the shorthand for `--all-namespaces`:
```kubectl -A```
## Kubectl context and configuration
@@ -97,10 +102,10 @@ kubectl apply -f https://git.io/vPieo # create resource(s) from url
kubectl create deployment nginx --image=nginx # start a single instance of nginx
# create a Job which prints "Hello World"
kubectl create job hello --image=busybox -- echo "Hello World"
kubectl create job hello --image=busybox:1.28 -- echo "Hello World"
# create a CronJob that prints "Hello World" every minute
kubectl create cronjob hello --image=busybox --schedule="*/1 * * * *" -- echo "Hello World"
kubectl create cronjob hello --image=busybox:1.28 --schedule="*/1 * * * *" -- echo "Hello World"
kubectl explain pods # get the documentation for pod manifests
@@ -113,7 +118,7 @@ metadata:
spec:
containers:
- name: busybox
image: busybox
image: busybox:1.28
args:
- sleep
- "1000000"
@@ -125,7 +130,7 @@ metadata:
spec:
containers:
- name: busybox
image: busybox
image: busybox:1.28
args:
- sleep
- "1000"
@@ -315,7 +320,7 @@ kubectl logs my-pod -c my-container --previous # dump pod container logs (s
kubectl logs -f my-pod # stream pod logs (stdout)
kubectl logs -f my-pod -c my-container # stream pod container logs (stdout, multi-container case)
kubectl logs -f -l name=myLabel --all-containers # stream all pods logs with label name=myLabel (stdout)
kubectl run -i --tty busybox --image=busybox -- sh # Run pod as interactive shell
kubectl run -i --tty busybox --image=busybox:1.28 -- sh # Run pod as interactive shell
kubectl run nginx --image=nginx -n mynamespace # Start a single instance of nginx pod in the namespace of mynamespace
kubectl run nginx --image=nginx # Run pod nginx and write its spec into a file called pod.yaml
--dry-run=client -o yaml > pod.yaml
content/en/docs/reference/labels-annotations-taints/_index.md
+4 -2
View File
@@ -495,9 +495,11 @@ based on setting `securityContext` within the Pod's `.spec`.
## Annotations used for audit
- [`pod-security.kubernetes.io/exempt`](/docs/reference/labels-annotations-taints/audit-annotations/#pod-security-kubernetes-io-exempt)
- [`pod-security.kubernetes.io/enforce-policy`](/docs/reference/labels-annotations-taints/audit-annotations/#pod-security-kubernetes-io-enforce-policy)
- [`authorization.k8s.io/decision`](/docs/reference/labels-annotations-taints/audit-annotations/#authorization-k8s-io-decision)
- [`authorization.k8s.io/reason`](/docs/reference/labels-annotations-taints/audit-annotations/#authorization-k8s-io-reason)
- [`pod-security.kubernetes.io/audit-violations`](/docs/reference/labels-annotations-taints/audit-annotations/#pod-security-kubernetes-io-audit-violations)
- [`pod-security.kubernetes.io/enforce-policy`](/docs/reference/labels-annotations-taints/audit-annotations/#pod-security-kubernetes-io-enforce-policy)
- [`pod-security.kubernetes.io/exempt`](/docs/reference/labels-annotations-taints/audit-annotations/#pod-security-kubernetes-io-exempt)
See more details on the [Audit Annotations](/docs/reference/labels-annotations-taints/audit-annotations/) page.
content/en/docs/reference/labels-annotations-taints/audit-annotations.md
+17 -1
View File
@@ -56,4 +56,20 @@ that was transgressed as well as the specific policies on the fields that were
violated from the PodSecurity enforcement.
See [Pod Security Standards](/docs/concepts/security/pod-security-standards/)
for more information.
for more information.
## authorization.k8s.io/decision
Example: `authorization.k8s.io/decision: "forbid"`
This annotation indicates whether or not a request was authorized in Kubernetes audit logs.
See [Auditing](/docs/tasks/debug-application-cluster/audit/) for more information.
## authorization.k8s.io/reason
Example: `authorization.k8s.io/decision: "Human-readable reason for the decision"`
This annotation gives reason for the [decision](#authorization-k8s-io-decision) in Kubernetes audit logs.
See [Auditing](/docs/tasks/debug-application-cluster/audit/) for more information.
content/en/docs/setup/best-practices/certificates.md
+2
View File
@@ -22,6 +22,8 @@ This page explains the certificates that your cluster requires.
Kubernetes requires PKI for the following operations:
* Client certificates for the kubelet to authenticate to the API server
* Kubelet [server certificates](/docs/reference/command-line-tools-reference/kubelet-tls-bootstrapping/#client-and-serving-certificates)
for the the API server to talk to the kubelets
* Server certificate for the API server endpoint
* Client certificates for administrators of the cluster to authenticate to the API server
* Client certificates for the API server to talk to the kubelets
content/en/docs/setup/production-environment/tools/kubeadm/kubelet-integration.md
+2 -1
View File
@@ -203,6 +203,7 @@ The DEB and RPM packages shipped with the Kubernetes releases are:
| Package name | Description |
|--------------|-------------|
| `kubeadm` | Installs the `/usr/bin/kubeadm` CLI tool and the [kubelet drop-in file](#the-kubelet-drop-in-file-for-systemd) for the kubelet. |
| `kubelet` | Installs the kubelet binary in `/usr/bin` and CNI binaries in `/opt/cni/bin`. |
| `kubelet` | Installs the `/usr/bin/kubelet` binary. |
| `kubectl` | Installs the `/usr/bin/kubectl` binary. |
| `cri-tools` | Installs the `/usr/bin/crictl` binary from the [cri-tools git repository](https://github.com/kubernetes-sigs/cri-tools). |
| `kubernetes-cni` | Installs the `/opt/cni/bin` binaries from the [plugins git repository](https://github.com/containernetworking/plugins). |
content/en/docs/tasks/access-application-cluster/access-cluster.md
+3 -28
View File
@@ -205,35 +205,10 @@ See documentation for other libraries for how they authenticate.
## Accessing the API from a Pod
When accessing the API from a pod, locating and authenticating
to the apiserver are somewhat different.
to the API server are somewhat different.
The recommended way to locate the apiserver within the pod is with
the `kubernetes.default.svc` DNS name, which resolves to a Service IP which in turn
will be routed to an apiserver.
The recommended way to authenticate to the apiserver is with a
[service account](/docs/tasks/configure-pod-container/configure-service-account/) credential. By kube-system, a pod
is associated with a service account, and a credential (token) for that
service account is placed into the filesystem tree of each container in that pod,
at `/var/run/secrets/kubernetes.io/serviceaccount/token`.
If available, a certificate bundle is placed into the filesystem tree of each
container at `/var/run/secrets/kubernetes.io/serviceaccount/ca.crt`, and should be
used to verify the serving certificate of the apiserver.
Finally, the default namespace to be used for namespaced API operations is placed in a file
at `/var/run/secrets/kubernetes.io/serviceaccount/namespace` in each container.
From within a pod the recommended ways to connect to API are:
- Run `kubectl proxy` in a sidecar container in the pod, or as a background
process within the container. This proxies the
Kubernetes API to the localhost interface of the pod, so that other processes
in any container of the pod can access it.
- Use the Go client library, and create a client using the `rest.InClusterConfig()` and `kubernetes.NewForConfig()` functions.
They handle locating and authenticating to the apiserver. [example](https://git.k8s.io/client-go/examples/in-cluster-client-configuration/main.go)
In each case, the credentials of the pod are used to communicate securely with the apiserver.
Please check [Accessing the API from within a Pod](/docs/tasks/run-application/access-api-from-pod/)
for more details.
## Accessing services running on the cluster
content/en/docs/tasks/access-application-cluster/ingress-minikube.md
+7 -7
View File
@@ -240,13 +240,13 @@ The following manifest defines an Ingress that sends traffic to your Service via
following lines at the end:
```yaml
- path: /v2
pathType: Prefix
backend:
service:
name: web2
port:
number: 8080
- path: /v2
pathType: Prefix
backend:
service:
name: web2
port:
number: 8080
```
1. Apply the changes:
content/en/docs/tasks/administer-cluster/change-pv-reclaim-policy.md
+39 -40
View File
@@ -7,14 +7,10 @@ content_type: task
This page shows how to change the reclaim policy of a Kubernetes
PersistentVolume.
## {{% heading "prerequisites" %}}
{{< include "task-tutorial-prereqs.md" >}} {{< version-check >}}
<!-- steps -->
## Why change reclaim policy of a PersistentVolume
@@ -33,55 +29,58 @@ Released phase, where all of its data can be manually recovered.
1. List the PersistentVolumes in your cluster:
```shell
kubectl get pv
```
```shell
kubectl get pv
```
The output is similar to this:
The output is similar to this:
NAME CAPACITY ACCESSMODES RECLAIMPOLICY STATUS CLAIM STORAGECLASS REASON AGE
pvc-b6efd8da-b7b5-11e6-9d58-0ed433a7dd94 4Gi RWO Delete Bound default/claim1 manual 10s
pvc-b95650f8-b7b5-11e6-9d58-0ed433a7dd94 4Gi RWO Delete Bound default/claim2 manual 6s
pvc-bb3ca71d-b7b5-11e6-9d58-0ed433a7dd94 4Gi RWO Delete Bound default/claim3 manual 3s
```none
NAME CAPACITY ACCESSMODES RECLAIMPOLICY STATUS CLAIM STORAGECLASS REASON AGE
pvc-b6efd8da-b7b5-11e6-9d58-0ed433a7dd94 4Gi RWO Delete Bound default/claim1 manual 10s
pvc-b95650f8-b7b5-11e6-9d58-0ed433a7dd94 4Gi RWO Delete Bound default/claim2 manual 6s
pvc-bb3ca71d-b7b5-11e6-9d58-0ed433a7dd94 4Gi RWO Delete Bound default/claim3 manual 3s
```
This list also includes the name of the claims that are bound to each volume
This list also includes the name of the claims that are bound to each volume
for easier identification of dynamically provisioned volumes.
1. Choose one of your PersistentVolumes and change its reclaim policy:
```shell
kubectl patch pv <your-pv-name> -p '{"spec":{"persistentVolumeReclaimPolicy":"Retain"}}'
```
```shell
kubectl patch pv <your-pv-name> -p '{"spec":{"persistentVolumeReclaimPolicy":"Retain"}}'
```
where `<your-pv-name>` is the name of your chosen PersistentVolume.
where `<your-pv-name>` is the name of your chosen PersistentVolume.
{{< note >}}
On Windows, you must _double_ quote any JSONPath template that contains spaces (not single quote as shown above for bash). This in turn means that you must use a single quote or escaped double quote around any literals in the template. For example:
{{< note >}}
On Windows, you must _double_ quote any JSONPath template that contains spaces (not single
quote as shown above for bash). This in turn means that you must use a single quote or escaped
double quote around any literals in the template. For example:
```cmd
kubectl patch pv <your-pv-name> -p "{\"spec\":{\"persistentVolumeReclaimPolicy\":\"Retain\"}}"
```
{{< /note >}}
```cmd
kubectl patch pv <your-pv-name> -p "{\"spec\":{\"persistentVolumeReclaimPolicy\":\"Retain\"}}"
```
{{< /note >}}
1. Verify that your chosen PersistentVolume has the right policy:
```shell
kubectl get pv
```
```shell
kubectl get pv
```
The output is similar to this:
NAME CAPACITY ACCESSMODES RECLAIMPOLICY STATUS CLAIM STORAGECLASS REASON AGE
pvc-b6efd8da-b7b5-11e6-9d58-0ed433a7dd94 4Gi RWO Delete Bound default/claim1 manual 40s
pvc-b95650f8-b7b5-11e6-9d58-0ed433a7dd94 4Gi RWO Delete Bound default/claim2 manual 36s
pvc-bb3ca71d-b7b5-11e6-9d58-0ed433a7dd94 4Gi RWO Retain Bound default/claim3 manual 33s
In the preceding output, you can see that the volume bound to claim
`default/claim3` has reclaim policy `Retain`. It will not be automatically
deleted when a user deletes claim `default/claim3`.
The output is similar to this:
```none
NAME CAPACITY ACCESSMODES RECLAIMPOLICY STATUS CLAIM STORAGECLASS REASON AGE
pvc-b6efd8da-b7b5-11e6-9d58-0ed433a7dd94 4Gi RWO Delete Bound default/claim1 manual 40s
pvc-b95650f8-b7b5-11e6-9d58-0ed433a7dd94 4Gi RWO Delete Bound default/claim2 manual 36s
pvc-bb3ca71d-b7b5-11e6-9d58-0ed433a7dd94 4Gi RWO Retain Bound default/claim3 manual 33s
```
In the preceding output, you can see that the volume bound to claim
`default/claim3` has reclaim policy `Retain`. It will not be automatically
deleted when a user deletes claim `default/claim3`.
## {{% heading "whatsnext" %}}
@@ -91,8 +90,8 @@ kubectl patch pv <your-pv-name> -p "{\"spec\":{\"persistentVolumeReclaimPolicy\"
### References {#reference}
* {{< api-reference page="config-and-storage-resources/persistent-volume-v1" >}}
* Pay attention to the `.spec.persistentVolumeReclaimPolicy` [field](https://kubernetes.io/docs/reference/kubernetes-api/config-and-storage-resources/persistent-volume-v1/#PersistentVolumeSpec) of PersistentVolume.
* Pay attention to the `.spec.persistentVolumeReclaimPolicy`
[field](/docs/reference/kubernetes-api/config-and-storage-resources/persistent-volume-v1/#PersistentVolumeSpec)
of PersistentVolume.
* {{< api-reference page="config-and-storage-resources/persistent-volume-claim-v1" >}}
content/en/docs/tasks/administer-cluster/declare-network-policy.md
+3 -3
View File
@@ -68,7 +68,7 @@ pod/nginx-701339712-e0qfq 1/1 Running 0 35s
You should be able to access the new `nginx` service from other Pods. To access the `nginx` Service from another Pod in the `default` namespace, start a busybox container:
```console
kubectl run busybox --rm -ti --image=busybox -- /bin/sh
kubectl run busybox --rm -ti --image=busybox:1.28 -- /bin/sh
```
In your shell, run the following command:
@@ -111,7 +111,7 @@ networkpolicy.networking.k8s.io/access-nginx created
When you attempt to access the `nginx` Service from a Pod without the correct labels, the request times out:
```console
kubectl run busybox --rm -ti --image=busybox -- /bin/sh
kubectl run busybox --rm -ti --image=busybox:1.28 -- /bin/sh
```
In your shell, run the command:
@@ -130,7 +130,7 @@ wget: download timed out
You can create a Pod with the correct labels to see that the request is allowed:
```console
kubectl run busybox --rm -ti --labels="access=true" --image=busybox -- /bin/sh
kubectl run busybox --rm -ti --labels="access=true" --image=busybox:1.28 -- /bin/sh
```
In your shell, run the command:
content/en/docs/tasks/administer-cluster/ip-masq-agent.md
+40 -33
View File
@@ -4,31 +4,27 @@ content_type: task
---
<!-- overview -->
This page shows how to configure and enable the ip-masq-agent.
This page shows how to configure and enable the `ip-masq-agent`.
## {{% heading "prerequisites" %}}
{{< include "task-tutorial-prereqs.md" >}} {{< version-check >}}
<!-- discussion -->
## IP Masquerade Agent User Guide
The ip-masq-agent configures iptables rules to hide a pod's IP address behind the cluster node's IP address. This is typically done when sending traffic to destinations outside the cluster's pod [CIDR](https://en.wikipedia.org/wiki/Classless_Inter-Domain_Routing) range.
The `ip-masq-agent` configures iptables rules to hide a pod's IP address behind the cluster node's IP address. This is typically done when sending traffic to destinations outside the cluster's pod [CIDR](https://en.wikipedia.org/wiki/Classless_Inter-Domain_Routing) range.
### **Key Terms**
* **NAT (Network Address Translation)**
Is a method of remapping one IP address to another by modifying either the source and/or destination address information in the IP header. Typically performed by a device doing IP routing.
* **Masquerading**
A form of NAT that is typically used to perform a many to one address translation, where multiple source IP addresses are masked behind a single address, which is typically the device doing the IP routing. In Kubernetes this is the Node's IP address.
* **CIDR (Classless Inter-Domain Routing)**
Based on the variable-length subnet masking, allows specifying arbitrary-length prefixes. CIDR introduced a new method of representation for IP addresses, now commonly known as **CIDR notation**, in which an address or routing prefix is written with a suffix indicating the number of bits of the prefix, such as 192.168.2.0/24.
* **Link Local**
A link-local address is a network address that is valid only for communications within the network segment or the broadcast domain that the host is connected to. Link-local addresses for IPv4 are defined in the address block 169.254.0.0/16 in CIDR notation.
* **NAT (Network Address Translation)**
Is a method of remapping one IP address to another by modifying either the source and/or destination address information in the IP header. Typically performed by a device doing IP routing.
* **Masquerading**
A form of NAT that is typically used to perform a many to one address translation, where multiple source IP addresses are masked behind a single address, which is typically the device doing the IP routing. In Kubernetes this is the Node's IP address.
* **CIDR (Classless Inter-Domain Routing)**
Based on the variable-length subnet masking, allows specifying arbitrary-length prefixes. CIDR introduced a new method of representation for IP addresses, now commonly known as **CIDR notation**, in which an address or routing prefix is written with a suffix indicating the number of bits of the prefix, such as 192.168.2.0/24.
* **Link Local**
A link-local address is a network address that is valid only for communications within the network segment or the broadcast domain that the host is connected to. Link-local addresses for IPv4 are defined in the address block 169.254.0.0/16 in CIDR notation.
The ip-masq-agent configures iptables rules to handle masquerading node/pod IP addresses when sending traffic to destinations outside the cluster node's IP and the Cluster IP range. This essentially hides pod IP addresses behind the cluster node's IP address. In some environments, traffic to "external" addresses must come from a known machine address. For example, in Google Cloud, any traffic to the internet must come from a VM's IP. When containers are used, as in Google Kubernetes Engine, the Pod IP will be rejected for egress. To avoid this, we must hide the Pod IP behind the VM's own IP address - generally known as "masquerade". By default, the agent is configured to treat the three private IP ranges specified by [RFC 1918](https://tools.ietf.org/html/rfc1918) as non-masquerade [CIDR](https://en.wikipedia.org/wiki/Classless_Inter-Domain_Routing). These ranges are 10.0.0.0/8, 172.16.0.0/12, and 192.168.0.0/16. The agent will also treat link-local (169.254.0.0/16) as a non-masquerade CIDR by default. The agent is configured to reload its configuration from the location */etc/config/ip-masq-agent* every 60 seconds, which is also configurable.
@@ -36,14 +32,20 @@ The ip-masq-agent configures iptables rules to handle masquerading node/pod IP a
The agent configuration file must be written in YAML or JSON syntax, and may contain three optional keys:
* **nonMasqueradeCIDRs:** A list of strings in [CIDR](https://en.wikipedia.org/wiki/Classless_Inter-Domain_Routing) notation that specify the non-masquerade ranges.
* **masqLinkLocal:** A Boolean (true / false) which indicates whether to masquerade traffic to the link local prefix 169.254.0.0/16. False by default.
* **resyncInterval:** A time interval at which the agent attempts to reload config from disk. For example: '30s', where 's' means seconds, 'ms' means milliseconds, etc...
* `nonMasqueradeCIDRs`: A list of strings in
[CIDR](https://en.wikipedia.org/wiki/Classless_Inter-Domain_Routing) notation that specify the non-masquerade ranges.
* `masqLinkLocal`: A Boolean (true/false) which indicates whether to masquerade traffic to the
link local prefix `169.254.0.0/16`. False by default.
* `resyncInterval`: A time interval at which the agent attempts to reload config from disk.
For example: '30s', where 's' means seconds, 'ms' means milliseconds.
Traffic to 10.0.0.0/8, 172.16.0.0/12 and 192.168.0.0/16) ranges will NOT be masqueraded. Any other traffic (assumed to be internet) will be masqueraded. An example of a local destination from a pod could be its Node's IP address as well as another node's address or one of the IP addresses in Cluster's IP range. Any other traffic will be masqueraded by default. The below entries show the default set of rules that are applied by the ip-masq-agent:
```
```shell
iptables -t nat -L IP-MASQ-AGENT
```
```none
RETURN all -- anywhere 169.254.0.0/16 /* ip-masq-agent: cluster-local traffic should not be subject to MASQUERADE */ ADDRTYPE match dst-type !LOCAL
RETURN all -- anywhere 10.0.0.0/8 /* ip-masq-agent: cluster-local traffic should not be subject to MASQUERADE */ ADDRTYPE match dst-type !LOCAL
RETURN all -- anywhere 172.16.0.0/12 /* ip-masq-agent: cluster-local traffic should not be subject to MASQUERADE */ ADDRTYPE match dst-type !LOCAL
@@ -52,33 +54,35 @@ MASQUERADE all -- anywhere anywhere /* ip-masq-agent:
```
By default, in GCE/Google Kubernetes Engine starting with Kubernetes version 1.7.0, if network policy is enabled or you are using a cluster CIDR not in the 10.0.0.0/8 range, the ip-masq-agent will run in your cluster. If you are running in another environment, you can add the ip-masq-agent [DaemonSet](/docs/concepts/workloads/controllers/daemonset/) to your cluster:
By default, in GCE/Google Kubernetes Engine, if network policy is enabled or
you are using a cluster CIDR not in the 10.0.0.0/8 range, the `ip-masq-agent`
will run in your cluster. If you are running in another environment,
you can add the `ip-masq-agent` [DaemonSet](/docs/concepts/workloads/controllers/daemonset/)
to your cluster.
<!-- steps -->
## Create an ip-masq-agent
To create an ip-masq-agent, run the following kubectl command:
`
```shell
kubectl apply -f https://raw.githubusercontent.com/kubernetes-sigs/ip-masq-agent/master/ip-masq-agent.yaml
`
```
You must also apply the appropriate node label to any nodes in your cluster that you want the agent to run on.
`
kubectl label nodes my-node beta.kubernetes.io/masq-agent-ds-ready=true
`
```shell
kubectl label nodes my-node node.kubernetes.io/masq-agent-ds-ready=true
```
More information can be found in the ip-masq-agent documentation [here](https://github.com/kubernetes-sigs/ip-masq-agent)
In most cases, the default set of rules should be sufficient; however, if this is not the case for your cluster, you can create and apply a [ConfigMap](/docs/tasks/configure-pod-container/configure-pod-configmap/) to customize the IP ranges that are affected. For example, to allow only 10.0.0.0/8 to be considered by the ip-masq-agent, you can create the following [ConfigMap](/docs/tasks/configure-pod-container/configure-pod-configmap/) in a file called "config".
{{< note >}}
It is important that the file is called config since, by default, that will be used as the key for lookup by the ip-masq-agent:
It is important that the file is called config since, by default, that will be used as the key for lookup by the `ip-masq-agent`:
```
```yaml
nonMasqueradeCIDRs:
- 10.0.0.0/8
resyncInterval: 60s
@@ -87,15 +91,18 @@ resyncInterval: 60s
Run the following command to add the config map to your cluster:
```
```shell
kubectl create configmap ip-masq-agent --from-file=config --namespace=kube-system
```
This will update a file located at */etc/config/ip-masq-agent* which is periodically checked every *resyncInterval* and applied to the cluster node.
This will update a file located at `/etc/config/ip-masq-agent` which is periodically checked every `resyncInterval` and applied to the cluster node.
After the resync interval has expired, you should see the iptables rules reflect your changes:
```
```shell
iptables -t nat -L IP-MASQ-AGENT
```
```none
Chain IP-MASQ-AGENT (1 references)
target prot opt source destination
RETURN all -- anywhere 169.254.0.0/16 /* ip-masq-agent: cluster-local traffic should not be subject to MASQUERADE */ ADDRTYPE match dst-type !LOCAL
@@ -103,9 +110,9 @@ RETURN all -- anywhere 10.0.0.0/8 /* ip-masq-agent:
MASQUERADE all -- anywhere anywhere /* ip-masq-agent: outbound traffic should be subject to MASQUERADE (this match must come after cluster-local CIDR matches) */ ADDRTYPE match dst-type !LOCAL
```
By default, the link local range (169.254.0.0/16) is also handled by the ip-masq agent, which sets up the appropriate iptables rules. To have the ip-masq-agent ignore link local, you can set *masqLinkLocal* to true in the config map.
By default, the link local range (169.254.0.0/16) is also handled by the ip-masq agent, which sets up the appropriate iptables rules. To have the ip-masq-agent ignore link local, you can set `masqLinkLocal` to true in the ConfigMap.
```
```yaml
nonMasqueradeCIDRs:
- 10.0.0.0/8
resyncInterval: 60s
content/en/docs/tasks/configure-pod-container/configure-liveness-readiness-startup-probes.md
+16 -15
View File
@@ -81,13 +81,13 @@ kubectl describe pod liveness-exec
The output indicates that no liveness probes have failed yet:
```
FirstSeen LastSeen Count From SubobjectPath Type Reason Message
--------- -------- ----- ---- ------------- -------- ------ -------
24s 24s 1 {default-scheduler } Normal Scheduled Successfully assigned liveness-exec to worker0
23s 23s 1 {kubelet worker0} spec.containers{liveness} Normal Pulling pulling image "k8s.gcr.io/busybox"
23s 23s 1 {kubelet worker0} spec.containers{liveness} Normal Pulled Successfully pulled image "k8s.gcr.io/busybox"
23s 23s 1 {kubelet worker0} spec.containers{liveness} Normal Created Created container with docker id 86849c15382e; Security:[seccomp=unconfined]
23s 23s 1 {kubelet worker0} spec.containers{liveness} Normal Started Started container with docker id 86849c15382e
Type Reason Age From Message
---- ------ ---- ---- -------
Normal Scheduled 11s default-scheduler Successfully assigned default/liveness-exec to node01
Normal Pulling 9s kubelet, node01 Pulling image "k8s.gcr.io/busybox"
Normal Pulled 7s kubelet, node01 Successfully pulled image "k8s.gcr.io/busybox"
Normal Created 7s kubelet, node01 Created container liveness
Normal Started 7s kubelet, node01 Started container liveness
```
After 35 seconds, view the Pod events again:
@@ -100,14 +100,15 @@ At the bottom of the output, there are messages indicating that the liveness
probes have failed, and the containers have been killed and recreated.
```
FirstSeen LastSeen Count From SubobjectPath Type Reason Message
--------- -------- ----- ---- ------------- -------- ------ -------
37s 37s 1 {default-scheduler } Normal Scheduled Successfully assigned liveness-exec to worker0
36s 36s 1 {kubelet worker0} spec.containers{liveness} Normal Pulling pulling image "k8s.gcr.io/busybox"
36s 36s 1 {kubelet worker0} spec.containers{liveness} Normal Pulled Successfully pulled image "k8s.gcr.io/busybox"
36s 36s 1 {kubelet worker0} spec.containers{liveness} Normal Created Created container with docker id 86849c15382e; Security:[seccomp=unconfined]
36s 36s 1 {kubelet worker0} spec.containers{liveness} Normal Started Started container with docker id 86849c15382e
2s 2s 1 {kubelet worker0} spec.containers{liveness} Warning Unhealthy Liveness probe failed: cat: can't open '/tmp/healthy': No such file or directory
Type Reason Age From Message
---- ------ ---- ---- -------
Normal Scheduled 57s default-scheduler Successfully assigned default/liveness-exec to node01
Normal Pulling 55s kubelet, node01 Pulling image "k8s.gcr.io/busybox"
Normal Pulled 53s kubelet, node01 Successfully pulled image "k8s.gcr.io/busybox"
Normal Created 53s kubelet, node01 Created container liveness
Normal Started 53s kubelet, node01 Started container liveness
Warning Unhealthy 10s (x3 over 20s) kubelet, node01 Liveness probe failed: cat: can't open '/tmp/healthy': No such file or directory
Normal Killing 10s kubelet, node01 Container liveness failed liveness probe, will be restarted
```
Wait another 30 seconds, and verify that the container has been restarted:
content/en/docs/tasks/configure-pod-container/translate-compose-kubernetes.md
-50
View File
@@ -208,7 +208,6 @@ you need is an existing `docker-compose.yml` file.
- CLI
- [`kompose convert`](#kompose-convert)
- Documentation
- [Build and Push Docker Images](#build-and-push-docker-images)
- [Alternative Conversions](#alternative-conversions)
- [Labels](#labels)
- [Restart](#restart)
@@ -326,55 +325,6 @@ INFO OpenShift file "foo-buildconfig.yaml" created
If you are manually pushing the OpenShift artifacts using ``oc create -f``, you need to ensure that you push the imagestream artifact before the buildconfig artifact, to workaround this OpenShift issue: https://github.com/openshift/origin/issues/4518 .
{{< /note >}}
## Build and Push Docker Images
Kompose supports both building and pushing Docker images. When using the `build` key within your Docker Compose file, your image will:
- Automatically be built with Docker using the `image` key specified within your file
- Be pushed to the correct Docker repository using local credentials (located at `.docker/config`)
Using an [example Docker Compose file](https://raw.githubusercontent.com/kubernetes/kompose/master/examples/buildconfig/docker-compose.yml):
```yaml
version: "2"
services:
foo:
build: "./build"
image: docker.io/foo/bar
```
Using `kompose up` with a `build` key:
```none
kompose up
INFO Build key detected. Attempting to build and push image 'docker.io/foo/bar'
INFO Building image 'docker.io/foo/bar' from directory 'build'
INFO Image 'docker.io/foo/bar' from directory 'build' built successfully
INFO Pushing image 'foo/bar:latest' to registry 'docker.io'
INFO Attempting authentication credentials 'https://index.docker.io/v1/
INFO Successfully pushed image 'foo/bar:latest' to registry 'docker.io'
INFO We are going to create Kubernetes Deployments, Services and PersistentVolumeClaims for your Dockerized application. If you need different kind of resources, use the 'kompose convert' and 'kubectl apply -f' commands instead.
INFO Deploying application in "default" namespace
INFO Successfully created Service: foo
INFO Successfully created Deployment: foo
Your application has been deployed to Kubernetes. You can run 'kubectl get deployment,svc,pods,pvc' for details.
```
In order to disable the functionality, or choose to use BuildConfig generation (with OpenShift) `--build (local|build-config|none)` can be passed.
```sh
# Disable building/pushing Docker images
kompose up --build none
# Generate Build Config artifacts for OpenShift
kompose up --provider openshift --build build-config
```
## Alternative Conversions
The default `kompose` transformation will generate Kubernetes [Deployments](/docs/concepts/workloads/controllers/deployment/) and [Services](/docs/concepts/services-networking/service/), in yaml format. You have alternative option to generate json with `-j`. Also, you can alternatively generate [Replication Controllers](/docs/concepts/workloads/controllers/replicationcontroller/) objects, [Daemon Sets](/docs/concepts/workloads/controllers/daemonset/), or [Helm](https://github.com/helm/helm) charts.
content/en/docs/tasks/debug-application-cluster/debug-running-pod.md
+4 -4
View File
@@ -110,7 +110,7 @@ specify the `-i`/`--interactive` argument, `kubectl` will automatically attach
to the console of the Ephemeral Container.
```shell
kubectl debug -it ephemeral-demo --image=busybox --target=ephemeral-demo
kubectl debug -it ephemeral-demo --image=busybox:1.28 --target=ephemeral-demo
```
```
@@ -182,7 +182,7 @@ but you need debugging utilities not included in `busybox`. You can simulate
this scenario using `kubectl run`:
```shell
kubectl run myapp --image=busybox --restart=Never -- sleep 1d
kubectl run myapp --image=busybox:1.28 --restart=Never -- sleep 1d
```
Run this command to create a copy of `myapp` named `myapp-debug` that adds a
@@ -225,7 +225,7 @@ To simulate a crashing application, use `kubectl run` to create a container
that immediately exits:
```
kubectl run --image=busybox myapp -- false
kubectl run --image=busybox:1.28 myapp -- false
```
You can see using `kubectl describe pod myapp` that this container is crashing:
@@ -283,7 +283,7 @@ additional utilities.
As an example, create a Pod using `kubectl run`:
```
kubectl run myapp --image=busybox --restart=Never -- sleep 1d
kubectl run myapp --image=busybox:1.28 --restart=Never -- sleep 1d
```
Now use `kubectl debug` to make a copy and change its container image
content/en/docs/tasks/debug-application-cluster/resource-metrics-pipeline.md
+95 -37
View File
@@ -8,14 +8,19 @@ content_type: concept
<!-- overview -->
For Kubernetes, the _Metrics API_ offers a basic set of metrics to support automatic scaling and similar use cases.
This API makes information available about resource usage for node and pod, including metrics for CPU and memory.
If you deploy the Metrics API into your cluster, clients of the Kubernetes API can then query for this information, and
you can use Kubernetes' access control mechanisms to manage permissions to do so.
For Kubernetes, the _Metrics API_ offers a basic set of metrics to support automatic scaling and
similar use cases. This API makes information available about resource usage for node and pod,
including metrics for CPU and memory. If you deploy the Metrics API into your cluster, clients of
the Kubernetes API can then query for this information, and you can use Kubernetes' access control
mechanisms to manage permissions to do so.
The [HorizontalPodAutoscaler](/docs/tasks/run-application/horizontal-pod-autoscale/) (HPA) and [VerticalPodAutoscaler](https://github.com/kubernetes/autoscaler/tree/master/vertical-pod-autoscaler#readme) (VPA) use data from the metrics API to adjust workload replicas and resources to meet customer demand.
The [HorizontalPodAutoscaler](/docs/tasks/run-application/horizontal-pod-autoscale/) (HPA) and
[VerticalPodAutoscaler](https://github.com/kubernetes/autoscaler/tree/master/vertical-pod-autoscaler#readme) (VPA)
use data from the metrics API to adjust workload replicas and resources to meet customer demand.
You can also view the resource metrics using the [`kubectl top`](https://kubernetes.io/docs/reference/generated/kubectl/kubectl-commands#top) command.
You can also view the resource metrics using the
[`kubectl top`](/docs/reference/generated/kubectl/kubectl-commands#top)
command.
{{< note >}}
The Metrics API, and the metrics pipeline that it enables, only offers the minimum
@@ -59,34 +64,51 @@ Figure 1. Resource Metrics Pipeline
The architecture components, from right to left in the figure, consist of the following:
* [cAdvisor](https://github.com/google/cadvisor): Daemon for collecting, aggregating and exposing container metrics included in Kubelet.
* [kubelet](/docs/concepts/overview/components/#kubelet): Node agent for managing container resources. Resource metrics are accessible using the `/metrics/resource` and `/stats` kubelet API endpoints.
* [Summary API](#summary-api-source): API provided by the kubelet for discovering and retrieving per-node summarized stats available through the `/stats` endpoint.
* [metrics-server](#metrics-server): Cluster addon component that collects and aggregates resource metrics pulled from each kubelet. The API server serves Metrics API for use by HPA, VPA, and by the `kubectl top` command. Metrics Server is a reference implementation of the Metrics API.
* [Metrics API](#metrics-api): Kubernetes API supporting access to CPU and memory used for workload autoscaling. To make this work in your cluster, you need an API extension server that provides the Metrics API.
* [cAdvisor](https://github.com/google/cadvisor): Daemon for collecting, aggregating and exposing
container metrics included in Kubelet.
* [kubelet](/docs/concepts/overview/components/#kubelet): Node agent for managing container
resources. Resource metrics are accessible using the `/metrics/resource` and `/stats` kubelet
API endpoints.
* [Summary API](#summary-api-source): API provided by the kubelet for discovering and retrieving
per-node summarized stats available through the `/stats` endpoint.
* [metrics-server](#metrics-server): Cluster addon component that collects and aggregates resource
metrics pulled from each kubelet. The API server serves Metrics API for use by HPA, VPA, and by
the `kubectl top` command. Metrics Server is a reference implementation of the Metrics API.
* [Metrics API](#metrics-api): Kubernetes API supporting access to CPU and memory used for
workload autoscaling. To make this work in your cluster, you need an API extension server that
provides the Metrics API.
{{< note >}}
cAdvisor supports reading metrics from cgroups, which works with typical container runtimes on Linux.
If you use a container runtime that uses another resource isolation mechanism, for example virtualization, then that container runtime must support [CRI Container Metrics](https://github.com/kubernetes/community/blob/master/contributors/devel/sig-node/cri-container-stats.md) in order for metrics to be available to the kubelet.
If you use a container runtime that uses another resource isolation mechanism, for example
virtualization, then that container runtime must support
[CRI Container Metrics](https://github.com/kubernetes/community/blob/master/contributors/devel/sig-node/cri-container-stats.md)
in order for metrics to be available to the kubelet.
{{< /note >}}
<!-- body -->
## Metrics API
The metrics-server implements the Metrics API. This API allows you to access CPU and memory usage for the nodes and pods in your cluster. Its primary role is to feed resource usage metrics to K8s autoscaler components.
The metrics-server implements the Metrics API. This API allows you to access CPU and memory usage
for the nodes and pods in your cluster. Its primary role is to feed resource usage metrics to K8s
autoscaler components.
Here is an example of the Metrics API request for a `minikube` node piped through `jq` for easier
reading:
Here is an example of the Metrics API request for a `minikube` node piped through `jq` for easier reading:
```shell
kubectl get --raw "/apis/metrics.k8s.io/v1beta1/nodes/minikube" | jq '.'
```
Here is the same API call using `curl`:
```shell
curl http://localhost:8080/apis/metrics.k8s.io/v1beta1/nodes/minikube
```
Sample reply:
Sample response:
```json
{
"kind": "NodeMetrics",
@@ -104,16 +126,22 @@ Sample reply:
}
}
```
Here is an example of the Metrics API request for a `kube-scheduler-minikube` pod contained in the `kube-system` namespace and piped through `jq` for easier reading:
Here is an example of the Metrics API request for a `kube-scheduler-minikube` pod contained in the
`kube-system` namespace and piped through `jq` for easier reading:
```shell
kubectl get --raw "/apis/metrics.k8s.io/v1beta1/namespaces/kube-system/pods/kube-scheduler-minikube" | jq '.'
```
Here is the same API call using `curl`:
```shell
curl http://localhost:8080/apis/metrics.k8s.io/v1beta1/namespaces/kube-system/pods/kube-scheduler-minikube
```
Sample reply:
Sample response:
```json
{
"kind": "PodMetrics",
@@ -138,47 +166,72 @@ Sample reply:
}
```
The Metrics API is defined in the [k8s.io/metrics](https://github.com/kubernetes/metrics) repository. You must enable the [API aggregation layer](/docs/tasks/extend-kubernetes/configure-aggregation-layer/) and register an [APIService](/docs/reference/kubernetes-api/cluster-resources/api-service-v1/) for the `metrics.k8s.io` API.
The Metrics API is defined in the [k8s.io/metrics](https://github.com/kubernetes/metrics)
repository. You must enable the [API aggregation layer](/docs/tasks/extend-kubernetes/configure-aggregation-layer/)
and register an [APIService](/docs/reference/kubernetes-api/cluster-resources/api-service-v1/)
for the `metrics.k8s.io` API.
To learn more about the Metrics API, see [resource metrics API design](https://github.com/kubernetes/design-proposals-archive/blob/main/instrumentation/resource-metrics-api.md), the [metrics-server repository](https://github.com/kubernetes-sigs/metrics-server) and the [resource metrics API](https://github.com/kubernetes/metrics#resource-metrics-api).
To learn more about the Metrics API, see [resource metrics API design](https://github.com/kubernetes/design-proposals-archive/blob/main/instrumentation/resource-metrics-api.md),
the [metrics-server repository](https://github.com/kubernetes-sigs/metrics-server) and the
[resource metrics API](https://github.com/kubernetes/metrics#resource-metrics-api).
{{< note >}} You must deploy the metrics-server or alternative adapter that serves the Metrics API to be able to access it. {{< /note >}}
{{< note >}}
You must deploy the metrics-server or alternative adapter that serves the Metrics API to be able
to access it.
{{< /note >}}
## Measuring resource usage
### CPU
CPU is reported as the average core usage measured in cpu units. One cpu, in Kubernetes, is equivalent to 1 vCPU/Core for cloud providers, and 1 hyper-thread on bare-metal Intel processors.
CPU is reported as the average core usage measured in cpu units. One cpu, in Kubernetes, is
equivalent to 1 vCPU/Core for cloud providers, and 1 hyper-thread on bare-metal Intel processors.
This value is derived by taking a rate over a cumulative CPU counter provided by the kernel (in both Linux and Windows kernels). The time window used to calculate CPU is shown under window field in Metrics API.
This value is derived by taking a rate over a cumulative CPU counter provided by the kernel (in
both Linux and Windows kernels). The time window used to calculate CPU is shown under window field
in Metrics API.
To learn more about how Kubernetes allocates and measures CPU resources, see [meaning of CPU](/docs/concepts/configuration/manage-compute-resources-container/#meaning-of-cpu).
To learn more about how Kubernetes allocates and measures CPU resources, see
[meaning of CPU](/docs/concepts/configuration/manage-resources-container/#meaning-of-cpu).
### Memory
Memory is reported as the working set, measured in bytes, at the instant the metric was collected.
In an ideal world, the "working set" is the amount of memory in-use that cannot be freed under memory pressure. However, calculation of the working set varies by host OS, and generally makes heavy use of heuristics to produce an estimate.
In an ideal world, the "working set" is the amount of memory in-use that cannot be freed under
memory pressure. However, calculation of the working set varies by host OS, and generally makes
heavy use of heuristics to produce an estimate.
The Kubernetes model for a container's working set expects that the container runtime counts anonymous memory associated with the container in question. The working set metric typically also includes some cached (file-backed) memory, because the host OS cannot always reclaim pages.
The Kubernetes model for a container's working set expects that the container runtime counts
anonymous memory associated with the container in question. The working set metric typically also
includes some cached (file-backed) memory, because the host OS cannot always reclaim pages.
To learn more about how Kubernetes allocates and measures memory resources, see [meaning of memory](/docs/concepts/configuration/manage-compute-resources-container/#meaning-of-memory).
To learn more about how Kubernetes allocates and measures memory resources, see
[meaning of memory](/docs/concepts/configuration/manage-resources-container/#meaning-of-memory).
## Metrics Server
The metrics-server fetches resource metrics from the kubelets and exposes them in the Kubernetes API server through the Metrics API for use by the HPA and VPA. You can also view these metrics using the `kubectl top` command.
The metrics-server fetches resource metrics from the kubelets and exposes them in the Kubernetes
API server through the Metrics API for use by the HPA and VPA. You can also view these metrics
using the `kubectl top` command.
The metrics-server uses the Kubernetes API to track nodes and pods in your cluster. The metrics-server queries each node over HTTP to fetch metrics. The metrics-server also builds an internal view of pod metadata, and keeps a cache of pod health. That cached pod health information is available via the extension API that the metrics-server makes available.
The metrics-server uses the Kubernetes API to track nodes and pods in your cluster. The
metrics-server queries each node over HTTP to fetch metrics. The metrics-server also builds an
internal view of pod metadata, and keeps a cache of pod health. That cached pod health information
is available via the extension API that the metrics-server makes available.
For example with an HPA query, the metrics-server needs to identify which pods fulfill the label selectors in the deployment.
For example with an HPA query, the metrics-server needs to identify which pods fulfill the label
selectors in the deployment.
The metrics-server calls the [kubelet](/docs/reference/command-line-tools-reference/kubelet/) API
to collect metrics from each node. Depending on the metrics-server version it uses:
The metrics-server calls the [kubelet](/docs/reference/command-line-tools-reference/kubelet/) API to collect metrics from each node. Depending on the metrics-server version it uses:
* Metrics resource endpoint `/metrics/resource` in version v0.6.0+ or
* Summary API endpoint `/stats/summary` in older versions
To learn more about the metrics-server, see the [metrics-server repository](https://github.com/kubernetes-sigs/metrics-server).
To learn more about the metrics-server, see the
[metrics-server repository](https://github.com/kubernetes-sigs/metrics-server).
You can also check out the following:
@@ -190,20 +243,25 @@ You can also check out the following:
### Summary API source
The [kubelet](/docs/reference/command-line-tools-reference/kubelet/) gathers stats at the node, volume, pod and container level, and emits this information in
The [kubelet](/docs/reference/command-line-tools-reference/kubelet/) gathers stats at the node,
volume, pod and container level, and emits this information in
the [Summary API](https://github.com/kubernetes/kubernetes/blob/7d309e0104fedb57280b261e5677d919cb2a0e2d/staging/src/k8s.io/kubelet/pkg/apis/stats/v1alpha1/types.go)
for consumers to read.
Here is an example of a Summary API request for a `minikube` node:
```shell
kubectl get --raw "/api/v1/nodes/minikube/proxy/stats/summary"
```
Here is the same API call using `curl`:
```shell
curl http://localhost:8080/api/v1/nodes/minikube/proxy/stats/summary
```
{{< note >}}
The summary API `/stats/summary` endpoint will be replaced by the `/metrics/resource` endpoint beginning with metrics-server 0.6.x.
{{< /note >}}
The summary API `/stats/summary` endpoint will be replaced by the `/metrics/resource` endpoint
beginning with metrics-server 0.6.x.
{{< /note >}}
content/en/docs/tasks/job/parallel-processing-expansion.md
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View File
@@ -201,7 +201,7 @@ spec:
spec:
containers:
- name: c
image: busybox
image: busybox:1.28
command: ["sh", "-c", "echo Processing URL {{ url }} && sleep 5"]
restartPolicy: Never
{% endfor %}
content/en/docs/tasks/manage-daemon/update-daemon-set.md
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View File
@@ -34,11 +34,11 @@ DaemonSet has two update strategy types:
To enable the rolling update feature of a DaemonSet, you must set its
`.spec.updateStrategy.type` to `RollingUpdate`.
You may want to set
[`.spec.updateStrategy.rollingUpdate.maxUnavailable`](/docs/concepts/workloads/controllers/deployment/#max-unavailable)
You may want to set
[`.spec.updateStrategy.rollingUpdate.maxUnavailable`](/docs/reference/kubernetes-api/workload-resources/daemon-set-v1/#DaemonSetSpec)
(default to 1),
[`.spec.minReadySeconds`](/docs/concepts/workloads/controllers/deployment/#min-ready-seconds)
(default to 0) and
[`.spec.minReadySeconds`](/docs/reference/kubernetes-api/workload-resources/daemon-set-v1/#DaemonSetSpec)
(default to 0) and
[`.spec.updateStrategy.rollingUpdate.maxSurge`](/docs/reference/kubernetes-api/workload-resources/daemon-set-v1/#DaemonSetSpec)
(a beta feature and defaults to 0) as well.
content/en/docs/tasks/manage-kubernetes-objects/update-api-object-kubectl-patch.md
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View File
@@ -189,11 +189,11 @@ kubectl get deployment patch-demo --output yaml
The output shows that the PodSpec in the Deployment has only one Toleration:
```shell
```yaml
tolerations:
- effect: NoSchedule
key: disktype
value: ssd
- effect: NoSchedule
key: disktype
value: ssd
```
Notice that the `tolerations` list in the PodSpec was replaced, not merged. This is because
content/en/docs/tasks/run-application/access-api-from-pod.md
+2 -1
View File
@@ -48,7 +48,8 @@ While running in a Pod, the Kubernetes apiserver is accessible via a Service nam
do this automatically.
The recommended way to authenticate to the API server is with a
[service account](/docs/tasks/configure-pod-container/configure-service-account/) credential. By default, a Pod
[service account](/docs/tasks/configure-pod-container/configure-service-account/)
credential. By default, a Pod
is associated with a service account, and a credential (token) for that
service account is placed into the filesystem tree of each container in that Pod,
at `/var/run/secrets/kubernetes.io/serviceaccount/token`.
content/en/docs/tasks/run-application/horizontal-pod-autoscale-walkthrough.md
+1 -1
View File
@@ -152,7 +152,7 @@ runs in an infinite loop, sending queries to the php-apache service.
```shell
# Run this in a separate terminal
# so that the load generation continues and you can carry on with the rest of the steps
kubectl run -i --tty load-generator --rm --image=busybox --restart=Never -- /bin/sh -c "while sleep 0.01; do wget -q -O- http://php-apache; done"
kubectl run -i --tty load-generator --rm --image=busybox:1.28 --restart=Never -- /bin/sh -c "while sleep 0.01; do wget -q -O- http://php-apache; done"
```
Now run:
content/en/docs/tasks/tools/install-kubectl-linux.md
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View File
@@ -52,7 +52,7 @@ For example, to download version {{< param "fullversion" >}} on Linux, type:
Validate the kubectl binary against the checksum file:
```bash
echo "$(<kubectl.sha256) kubectl" | sha256sum --check
echo "$(cat kubectl.sha256) kubectl" | sha256sum --check
```
If valid, the output is:
@@ -212,7 +212,7 @@ Below are the procedures to set up autocompletion for Bash, Fish, and Zsh.
Validate the kubectl-convert binary against the checksum file:
```bash
echo "$(<kubectl-convert.sha256) kubectl-convert" | sha256sum --check
echo "$(cat kubectl-convert.sha256) kubectl-convert" | sha256sum --check
```
If valid, the output is:
content/en/docs/tasks/tools/install-kubectl-macos.md
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View File
@@ -69,7 +69,7 @@ The following methods exist for installing kubectl on macOS:
Validate the kubectl binary against the checksum file:
```bash
echo "$(<kubectl.sha256) kubectl" | shasum -a 256 --check
echo "$(cat kubectl.sha256) kubectl" | shasum -a 256 --check
```
If valid, the output is:
@@ -114,7 +114,7 @@ The following methods exist for installing kubectl on macOS:
Or use this for detailed view of version:
```cmd
kubectl version --client --output=yaml
kubectl version --client --output=yaml
```
### Install with Homebrew on macOS
@@ -124,7 +124,7 @@ If you are on macOS and using [Homebrew](https://brew.sh/) package manager, you
1. Run the installation command:
```bash
brew install kubectl
brew install kubectl
```
or
@@ -205,7 +205,7 @@ Below are the procedures to set up autocompletion for Bash, Fish, and Zsh.
Validate the kubectl-convert binary against the checksum file:
```bash
echo "$(<kubectl-convert.sha256) kubectl-convert" | shasum -a 256 --check
echo "$(cat kubectl-convert.sha256) kubectl-convert" | shasum -a 256 --check
```
If valid, the output is:
content/en/docs/tasks/tools/install-kubectl-windows.md
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View File
@@ -38,13 +38,13 @@ The following methods exist for installing kubectl on Windows:
1. Validate the binary (optional)
Download the kubectl checksum file:
Download the `kubectl` checksum file:
```powershell
curl -LO "https://dl.k8s.io/{{< param "fullversion" >}}/bin/windows/amd64/kubectl.exe.sha256"
```
Validate the kubectl binary against the checksum file:
Validate the `kubectl` binary against the checksum file:
- Using Command Prompt to manually compare `CertUtil`'s output to the checksum file downloaded:
@@ -59,7 +59,7 @@ The following methods exist for installing kubectl on Windows:
$($(CertUtil -hashfile .\kubectl.exe SHA256)[1] -replace " ", "") -eq $(type .\kubectl.exe.sha256)
```
1. Append or prepend the kubectl binary folder to your `PATH` environment variable.
1. Append or prepend the `kubectl` binary folder to your `PATH` environment variable.
1. Test to ensure the version of `kubectl` is the same as downloaded:
@@ -156,13 +156,13 @@ Below are the procedures to set up autocompletion for PowerShell.
1. Validate the binary (optional)
Download the kubectl-convert checksum file:
Download the `kubectl-convert` checksum file:
```powershell
curl -LO "https://dl.k8s.io/{{< param "fullversion" >}}/bin/windows/amd64/kubectl-convert.exe.sha256"
```
Validate the kubectl-convert binary against the checksum file:
Validate the `kubectl-convert` binary against the checksum file:
- Using Command Prompt to manually compare `CertUtil`'s output to the checksum file downloaded:
@@ -177,7 +177,7 @@ Below are the procedures to set up autocompletion for PowerShell.
$($(CertUtil -hashfile .\kubectl-convert.exe SHA256)[1] -replace " ", "") -eq $(type .\kubectl-convert.exe.sha256)
```
1. Append or prepend the kubectl binary folder to your `PATH` environment variable.
1. Append or prepend the `kubectl-convert` binary folder to your `PATH` environment variable.
1. Verify plugin is successfully installed
content/en/docs/tutorials/security/apparmor.md
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View File
@@ -264,7 +264,7 @@ metadata:
spec:
containers:
- name: hello
image: busybox
image: busybox:1.28
command: [ "sh", "-c", "echo 'Hello AppArmor!' && sleep 1h" ]
EOF
pod/hello-apparmor-2 created
content/en/docs/tutorials/services/source-ip.md
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View File
@@ -119,7 +119,7 @@ clusterip ClusterIP 10.0.170.92 <none> 80/TCP 51s
And hitting the `ClusterIP` from a pod in the same cluster:
```shell
kubectl run busybox -it --image=busybox --restart=Never --rm
kubectl run busybox -it --image=busybox:1.28 --restart=Never --rm
```
The output is similar to this:
```