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Steve Perry
2017-02-01 14:05:49 -08:00
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_data/concepts.yml
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@@ -5,6 +5,9 @@ toc:
- title: Kubectl Command Line
section:
- docs/concepts/tools/kubectl/object-management-overview.md
- docs/concepts/tools/kubectl/object-management-using-imperative-commands.md
- docs/concepts/tools/kubectl/object-management-using-imperative-config.md
- docs/concepts/tools/kubectl/object-management-using-declarative-config.md
- title: Kubernetes Objects
section:
- docs/concepts/abstractions/overview.md
docs/concepts/tools/kubectl/object-management-overview.md
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@@ -59,12 +59,6 @@ Disadvantages compared to object configuration:
- Commands do not provide a source of records except for what is live.
- Commands do not provide a template for creating new objects.
{% comment %}
If we use Markdown comments instead of HTML comments, they won't appear in the built HTML files.
For a tutorial on how to use Imperative Commands for app management, see:
[App Management Using Comands](/docs/tutorials/kubectl/app-management-using-commands/)
{% endcomment %}
## Imperative object configuration
When using imperative object configuration, a user operates on object
@@ -124,11 +118,6 @@ Disadvantages compared to declarative object configuration:
- Imperative object configuration works best on files, not directories.
- Updates to live objects must be reflected in configuration files, or they will be lost during the next replacement.
{% comment %}
For a tutorial on how to use Yaml Config for app management, see:
[App Management Yaml Config](/docs/tutorials/kubectl/app-management-using-yaml-config/)
{% endcomment %}
## Declarative object configuration
When using declarative object configuration, a user operates on object
@@ -170,20 +159,16 @@ Disadvantages compared to imperative object configuration:
- Declarative object configuration is harder to debug and understand results when they are unexpected.
- Partial updates using diffs create complex merge and patch operations.
{% comment %}
For a tutorial on how to use Yaml Config with multiple writers, see:
[App Management Yaml Config](/docs/tutorials/kubectl/app-management-using-yaml-config-multiple-writers/)
{% endcomment %}
{% endcapture %}
{% capture whatsnext %}
- [Managing Kubernetes Objects Using Imperative Commands](/docs/concepts/tools/kubectl/object-management-using-imperative-commands/)
- [Managing Kubernetes Objects Using Object Configuration (Imperative)](/docs/concepts/tools/kubectl/object-management-using-imperative-config/)
- [Managing Kubernetes Objects Using Object Configuration (Declarative)](/docs/concepts/tools/kubectl/object-management-using-declarative-config/)
- [Kubectl Command Reference](/docs/user-guide/kubectl/v1.5/)
- [Kubernetes Object Schema Reference](/docs/resources-reference/v1.5/)
{% comment %}
- [App Management Using Yaml Config](/docs/tutorials/kubectl/declarative-app-management-using-yaml-config/)
- [App Management Using Yaml Config With Multiple Writers](/docs/tutorials/kubectl/declarative-app-management-using-yaml-config-multiple-writers/)
{% endcomment %}
{% endcapture %}
docs/concepts/tools/kubectl/object-management-using-declarative-config.md
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@@ -0,0 +1,958 @@
---
title: Declarative Management of Kubernetes Objects Using Configuration Files
---
{% capture overview %}
Kubernetes objects can be created, updated, and deleted by storing multiple
object configuration files in a directory and using `kubectl apply` to
recursively create and update those objects as needed. This method
retains writes made to live objects without merging the changes
back into the object configuration files.
{% endcapture %}
{% capture body %}
## Trade-offs
The `kubectl` tool supports three kinds of object management:
* Imperative commands
* Imperative object configuration
* Declarative object configuration
See [Kubernetes Object Management](/docs/concepts/tools/kubectl/object-management-overview/)
for a discussion of the advantages and disadvantage of each kind of object management.
## Before you begin
Declarative object configuration requires a firm understanding of
the Kubernetes object definitions and configuration. Read and complete
the following documents if you have not already:
- [Managing Kubernetes Objects Using Imperative Commands](/docs/concepts/tools/kubectl/object-management-using-imperative-commands/)
- [Imperative Management of Kubernetes Objects Using Configuration Files](/docs/concepts/tools/kubectl/object-management-using-imperative-config/)
Following are definitions for terms used in this document:
- *object configuration file / configuration file*: A file that defines the
configuration for a Kubernetes object. This topic shows how to pass configuration
files to `kubectl apply`. Configuration files are typically stored in source control, such as Git.
- *live object configuration / live configuration*: The live configuration
values of an object, as observed by the Kubernetes cluster. These are kept in the Kubernetes
cluster storage, typically etcd.
- *declarative configuration writer / declarative writer*: A person or software component
that makes updates to a live object. The live writers refered to in this topic make changes
to object configuration files and run `kubectl apply` to write the changes.
## How to create objects
Use `kubectl apply` to create all objects, except those that already exist,
defined by configuration files in a specified directory:
```shell
kubectl apply -f <directory>/
```
This sets the `kubectl.kubernetes.io/last-applied-configuration: '{...}'`
annotation on each object. The annotation contains the contents of the object
configuration file that was used to create the object.
**Note**: Add the `-R` flag to recursively process directories.
Here's an example of an object configuration file:
{% include code.html language="yaml" file="simple_deployment.yaml" ghlink="/docs/concepts/tools/simple_deployment.yaml" %}
Create the object using `kubectl apply`:
```shell
kubectl apply -f http://k8s.io/docs/concepts/tools/kubectl/simple_deployment.yaml
```
Print the live configuration using `kubectl get`:
```shell
kubectl get -f http://k8s.io/docs/concepts/tools/kubectl/simple_deployment.yaml -o yaml
```
The output shows that the `kubectl.kubernetes.io/last-applied-configuration` annotation
was written to the live configuration, and it matches the configuration file:
```shell
kind: Deployment
metadata:
annotations:
# ...
# This is the json representation of simple_deployment.yaml
# It was written by kubectl apply when the object was created
kubectl.kubernetes.io/last-applied-configuration: |
{"apiVersion":"extensions/v1beta1","kind":"Deployment",
"metadata":{"annotations":{},"name":"nginx-deployment","namespace":"default"},
"spec":{"minReadySeconds":5,"template":{"metadata":{"labels":{"app":"nginx"}},
"spec":{"containers":[{"image":"nginx:1.7.9","name":"nginx",
"ports":[{"containerPort":80}]}]}}}}
# ...
spec:
# ...
minReadySeconds: 5
template:
metadata:
# ...
labels:
app: nginx
spec:
containers:
- image: nginx:1.7.9
# ...
name: nginx
ports:
- containerPort: 80
# ...
# ...
# ...
# ...
```
## How to update objects
You can also use `kubectl apply` to update all objects defined in a directory, even
if those objects already exist. This approach accomplishes the following:
1. Sets fields that appear in the configuration file in the live configuration.
2. Clears fields removed from the configuration file in the live configuration.
```shell
kubectl apply -f <directory>/
```
**Note**: Add the `-R` flag to recursively process directories.
Here's an example configuration file:
{% include code.html language="yaml" file="simple_deployment.yaml" ghlink="/docs/concepts/tools/simple_deployment.yaml" %}
Create the object using `kubectl apply`:
```shell
kubectl apply -f http://k8s.io/docs/concepts/tools/kubectl/simple_deployment.yaml
```
**Note:** For purposes of illustration, the preceding command refers to a single
configuration file instead of a directory.
Print the live configuration using `kubectl get`:
```shell
kubectl get -f http://k8s.io/docs/concepts/tools/kubectl/simple_deployment.yaml -o yaml
```
The output shows that the `kubectl.kubernetes.io/last-applied-configuration` annotation
was written to the live configuration, and it matches the configuration file:
```shell
kind: Deployment
metadata:
annotations:
# ...
# This is the json representation of simple_deployment.yaml
# It was written by kubectl apply when the object was created
kubectl.kubernetes.io/last-applied-configuration: |
{"apiVersion":"extensions/v1beta1","kind":"Deployment",
"metadata":{"annotations":{},"name":"nginx-deployment","namespace":"default"},
"spec":{"minReadySeconds":5,"template":{"metadata":{"labels":{"app":"nginx"}},
"spec":{"containers":[{"image":"nginx:1.7.9","name":"nginx",
"ports":[{"containerPort":80}]}]}}}}
# ...
spec:
# ...
minReadySeconds: 5
template:
metadata:
# ...
labels:
app: nginx
spec:
containers:
- image: nginx:1.7.9
# ...
name: nginx
ports:
- containerPort: 80
# ...
# ...
# ...
# ...
```
Directly update the `replicas` field in the live configuration by using `kubectl scale`.
This does not use `kubectl apply`:
```shell
kubectl scale deployment/nginx-deployment --replicas 2
```
Print the live configuration using `kubectl get`:
```shell
kubectl get -f http://k8s.io/docs/concepts/tools/kubectl/simple_deployment.yaml -o yaml
```
The output shows that the `replicas` field has been set to 2, and the `last-applied-configuration`
annotation does not contain a `replicas` field:
```
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
annotations:
# ...
# note that the annotation does not contain replicas
# because it was not updated through apply
kubectl.kubernetes.io/last-applied-configuration: |
{"apiVersion":"extensions/v1beta1","kind":"Deployment",
"metadata":{"annotations":{},"name":"nginx-deployment","namespace":"default"},
"spec":{"minReadySeconds":5,"template":{"metadata":{"labels":{"app":"nginx"}},
"spec":{"containers":[{"image":"nginx:1.7.9","name":"nginx",
"ports":[{"containerPort":80}]}]}}}}
# ...
spec:
replicas: 2 # written by scale
# ...
minReadySeconds: 5
template:
metadata:
# ...
labels:
app: nginx
spec:
containers:
- image: nginx:1.7.9
# ...
name: nginx
ports:
- containerPort: 80
# ...
```
Update the `simple_deployment.yaml` configuration file to change the image from
`nginx:1.7.9` to `nginx:1.11.9`, and delete the `minReadySeconds` field:
{% include code.html language="yaml" file="update_deployment.yaml" ghlink="/docs/concepts/tools/update_deployment.yaml" %}
Apply the changes made to the configuration file:
```shell
kubectl apply -f http://k8s.io/docs/concepts/tools/kubectl/updated_deployment.yaml
```
Print the live configuration using `kubectl get`:
```
kubectl get -f http://k8s.io/docs/concepts/tools/kubectl/simple_deployment.yaml -o yaml
```
The output shows the following changes to the live configuration:
- The `replicas` field retains the value of 2 set by `kubectl scale`.
This is possible because it is omitted from the configuration file.
- The `image` field has been updated to `nginx:1.11.9` from `nginx:1.7.9`.
- The `last-applied-configuration` annotation has been updated with the new image.
- The `minReadySeconds` field has been cleared.
- The `last-applied-configuration` annotation no longer contains the `minReadySeconds` field.
```shell
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
annotations:
# ...
# The annotation contains the updated image to nginx 1.11.9,
# but does not contain the updated replicas to 2
kubectl.kubernetes.io/last-applied-configuration: |
{"apiVersion":"extensions/v1beta1","kind":"Deployment",
"metadata":{"annotations":{},"name":"nginx-deployment","namespace":"default"},
"spec":{"template":{"metadata":{"labels":{"app":"nginx"}},
"spec":{"containers":[{"image":"nginx:1.11.9","name":"nginx",
"ports":[{"containerPort":80}]}]}}}}
# ...
spec:
replicas: 2 # Set by `kubectl scale`. Ignored by `kubectl apply`.
# minReadySeconds cleared by `kubectl apply`
# ...
template:
metadata:
# ...
labels:
app: nginx
spec:
containers:
- image: nginx:1.11.9 # Set by `kubectl apply`
# ...
name: nginx
ports:
- containerPort: 80
# ...
# ...
# ...
# ...
```
**Warning**: Mixing `kubectl apply` with the imperative object configuration commands
`create` and `replace` is not supported. This is because `create`
and `replace` do not retain the `kubectl.kubernetes.io/last-applied-configuration`
that `kubectl apply` uses to compute updates.
**Warning**: As of Kubernetes 1.5, the `kubectl edit` command is
incompatible with `kubectl apply`, and the two should not be
used together.
## How to delete objects
There are two approaches to delete objects managed by `kubectl apply`.
### Recommended: `delete -f <filename>`
Manually deleting objects using the imperative command is the recommended
approach, as it is more explicit about what is being deleted, and less likely
to result in the user deleting something unintentionally:
```shell
delete -f <filename>
```
### Alternative: `kubectl apply -f <directory/> --prune -l your=label`
Only use this if you know what you are doing.
**Warning:** `kubectl apply --prune` is in alpha, and backwards incompatible
changes might be introduced in subsequent releases.
**Warning**: You must be careful when using this command, so that you
do not delete objects unintentionally.
As an alternative to `kubectl delete`, you can use `kubectl apply` to identify objects to be deleted after their
configuration files have been removed from the directory. Apply with `--prune`
queries the API server for all objects matching a set of labels, and attempts
to match the returned live object configurations against the object
configuration files. If an object matches the query, and it does not have a
configuration file in the directory, and it does not have a `last-applied-configuration` annotation,
it is deleted.
{% comment %}
TODO(pwittrock): We need to change the behavior to prevent the user from running apply on subdirectories unintentionally.
{% endcomment %}
```shell
kubectl apply -f <directory/> --prune -l <labels>
```
**Important:** Apply with prune should only be run against the root directory
containing the object configuration files. Running against sub-directories
can cause objects to be unintentionally deleted if they are returned
by the label selector query specified with `-l <labels>` and
do not appear in the subdirectory.
## How to view an object
You can use `kubectl get` with `-o yaml` to view the configuration of a live object:
```shell
kubectl get -f <filename|url> -o yaml
```
## How apply calculates differences and merges changes
**Definition:** A *patch* is an update operation that is scoped to specific
fields of an object instead of the entire object.
This enables updating only a specific set of fields on an object without
reading the object first.
When `kubectl apply` updates the live configuration for an object,
it does so by sending a patch request to the API server. The
patch defines updates scoped to specific fields of the live object
configuration. The `kubectl apply` command calculates this patch request
using the configuration file, the live configuration, and the
`last-applied-configuration` annotation stored in the live configuration.
### Merge patch calculation
The `kubectl apply` command writes the contents of the configuration file to the
`kubectl.kubernetes.io/last-applied-configuration` annotation. This
is used to identify fields that have been removed from the configuration
file and need to be cleared from the live configuration. Here are the steps used
to caluculate which fields should be deleted or set:
1. Calculate the fields to delete. Thes are the fields present in `last-applied-configuration` and missing from the configuration file.
2. Calculate the fields to add or set. These are the fields present in the configuration file whose values don't match the live configuration.
Here's an example. Suppose this is the configuration file for a Deployment object:
{% include code.html language="yaml" file="update_deployment.yaml" ghlink="/docs/concepts/tools/update_deployment.yaml" %}
Also, suppose this is the live configuration for the same Deployment object:
```shell
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
annotations:
# ...
# note that the annotation does not contain replicas
# because it was not updated through apply
kubectl.kubernetes.io/last-applied-configuration: |
{"apiVersion":"extensions/v1beta1","kind":"Deployment",
"metadata":{"annotations":{},"name":"nginx-deployment","namespace":"default"},
"spec":{"minReadySeconds":5,"template":{"metadata":{"labels":{"app":"nginx"}},
"spec":{"containers":[{"image":"nginx:1.7.9","name":"nginx",
"ports":[{"containerPort":80}]}]}}}}
# ...
spec:
replicas: 2 # written by scale
# ...
minReadySeconds: 5
template:
metadata:
# ...
labels:
app: nginx
spec:
containers:
- image: nginx:1.7.9
# ...
name: nginx
ports:
- containerPort: 80
# ...
```
Here are the merge calculations that would be performed by `kubectl apply`:
1. Calculate the fields to delete by reading values from
`last-applied-configuration` and comparing them to values in the
configuration file. In this example, `minReadySeconds` appears in the
`last-applied-configuration` annotation, but does not appear in the configuration file.
**Action:** Clear `minReadySeconds` from the live configuration.
2. Calculate the fields to set by reading values from the configuration
file and comparing them to values in the live configuration. In this example,
the value of `image` in the configuration file does not match
the value in the live configuration. **Action:** Set the value of `image` in the live configuration.
3. Set the `last-applied-configuration` annotation to match the value
of the configuration file.
4. Merge the results from 1, 2, 3 into a single patch request to the API server.
Here is the live configuration that is the result of the merge:
```shell
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
annotations:
# ...
# The annotation contains the updated image to nginx 1.11.9,
# but does not contain the updated replicas to 2
kubectl.kubernetes.io/last-applied-configuration: |
{"apiVersion":"extensions/v1beta1","kind":"Deployment",
"metadata":{"annotations":{},"name":"nginx-deployment","namespace":"default"},
"spec":{"template":{"metadata":{"labels":{"app":"nginx"}},
"spec":{"containers":[{"image":"nginx:1.11.9","name":"nginx",
"ports":[{"containerPort":80}]}]}}}}
# ...
spec:
replicas: 2 # Set by `kubectl scale`. Ignored by `kubectl apply`.
# minReadySeconds cleared by `kubectl apply`
# ...
template:
metadata:
# ...
labels:
app: nginx
spec:
containers:
- image: nginx:1.11.9 # Set by `kubectl apply`
# ...
name: nginx
ports:
- containerPort: 80
# ...
# ...
# ...
# ...
```
{% comment %}
TODO(1.6): For 1.6, add the following bullet point to 1.
- clear fields explicitly set to null in the local object configuration file regardless of whether they appear in the last-applied-configuration
{% endcomment %}
### How different types of fields are merged
How a particular field in a configuration file is merged with
with the live configuration depends on the
type of the field. There are several types of fields:
- *primitive*: A field of type string, integer, or boolean.
For example, `image` and `replicas` are primitive fields. **Action:** Replace.
- *map*, also called *object*: A field of type map or a complex type that contains subfields. For example `labels`
and `annotations` are maps; `spec` and `metadata` are complex types. **Action:** Merge elements or subfields.
- *list*: A field containing a list of items that can be either primitive types, maps, or complex types.
For example, `containers`, `ports`, and `args` are lists. **Action:** Varies.
When `kubectl apply` updates a map or list field, it typically does
not replace the entire field, but instead updates the individual subelements.
For instance, when merging the `spec` on a Deployment, the entire `spec` is
not replaced. Instead the subfields of `spec`, such as `replicas`, are compared
and merged.
### Merging changes to primitive fields
Primative fieldss are replaced or cleared.
**Note:** '-' is used for "not applicable" because the value is not used.
| Field in object configuration file | Field in live object configuration | Field in last-applied-configuration | Action |
|-------------------------------------|------------------------------------|-------------------------------------|-------------------------------------------|
| Yes | Yes | - | Set live to configuration file value. |
| Yes | No | - | Set live to local configuration. |
| No | - | Yes | Clear from live configuration. |
| No | - | No | Do nothing. Keep live value. |
### Merging changes to map or complex fields
Fields that represent maps or complex-types are merged by comparing each of the sub fields or elements of of the map / complex-type:
**Note:** '-' is used for "not applicable" because the value is not used.
| Key in object configuration file | Key in live object configuration | Field in last-applied-configuration | Action |
|-------------------------------------|------------------------------------|-------------------------------------|----------------------------------|
| Yes | Yes | - | Compare sub fields values. |
| Yes | No | - | Set live to local configuration. |
| No | - | Yes | Delete from live configuration. |
| No | - | No | Do nothing. Keep live value. |
### Merging changes for fields of type list
Merging changes to a list uses one of three strategies:
* Replace the list.
* Merge individual elements in a list of complex elements.
* Merge a list of primitive elements.
The choice of strategy is made on a per-field basis.
#### Replace the list
Treat the list the same as a primitive field. Replace or delete the
entire list. This preserves ordering.
**Example:** Use `kubectl apply` to update the `args` field of a Container in a Pod. This sets
the value of `args` in the live configuration to the value in the configuration file.
Any `args` elements that had previously been added to the live configuration are lost.
The order of the `args` elements defined in the configuration file is
retained in the live configuration.
```yaml
# last-applied-configuration value
args: ["a, b"]
# configuration file value
args: ["a", "c"]
# live configuration
args: ["a", "b", "d"]
# result after merge
args: ["a", "c"]
```
**Explanation:** The merge used the configuration file value as the new list value.
#### Merge individual elements of a list of complex elements:
Treat the list as a map, and treat a specific field of each element as a key.
Add, delete, or update individual elements. This does not preserve ordering.
This merge strategy uses a special tag on each field called a `patchMergeKey`. The
`patchMergeKey` is defined for each field in the Kubernetes source code:
[types.go](https://github.com/kubernetes/kubernetes/blob/master/pkg/api/v1/types.go#L2119)
When merging a list of complex elements, the field specified as the `patchMergeKey` for a given element
is used like a map key for that element.
**Example:** Use `kubectl apply` to update the `containers` field of a PodSpec.
This merges the list as though `containers` was a map where each element is keyed
by `name`.
```yaml
# last-applied-configuration value
containers:
- name: nginx
image: nginx:1.10
- name: nginx-helper-a # key: nginx-helper-a; will be deleted in result
image: helper:1.3
- name: nginx-helper-b # key: nginx-helper-b; will be retained
image: helper:1.3
# configuration file value
containers:
- name: nginx
image: nginx:1.11
- name: nginx-helper-b
image: helper:1.3
- name: nginx-helper-c # key: nginx-helper-c; will be added in result
image: helper:1.3
# live configuration
containers:
- name: nginx
image: nginx:1.10
- name: nginx-helper-a
image: helper:1.3
- name: nginx-helper-b
image: helper:1.3
args: ["run"] # Field will be retained
- name: nginx-helper-d # key: nginx-helper-d; will be retained
image: helper:1.3
# result after merge
containers:
- name: nginx
image: nginx:1.10
# Element nginx-helper-a was deleted
- name: nginx-helper-b
image: helper:1.3
args: ["run"] # Field was retained
- name: nginx-helper-c # Element was added
image: helper:1.3
- name: nginx-helper-d # Element was ignored
image: helper:1.3
```
**Explanation:**
- The container named "nginx-helper-a" was deleted because no container
named "nginx-helper-a" appeared in the configuration file.
- The container named "nginx-helper-b" retained the changes to `args`
in the live configuration. `kubectl apply` was able to identify
that "nginx-helper-b" in the live configuration was the same
"nginx-helper-b" as in the configuration file, even though their fields
had different values (no `args` in the configuration file). This is
because the `patchMergeKey` field value (name) was identical in both.
- The container named "nginx-helper-c" was added because no container
with that name appeared in the live configuration, but one with
that name appeared in the configuration file.
- The container named "nginx-helper-d" was retained because
no element with that name appeared in the last-applied-configuration.
#### Merge a list of primitive elements
As of Kubernetes 1.5, merging lists of primitive elements is not supported.
**Note:** Which of the above strategies is chosen for a given field is controlled by
the `patchStrategy` tag in [types.go](https://github.com/kubernetes/kubernetes/blob/master/pkg/api/v1/types.go#L2119)
If no `patchStrategy` is specified for a field of type list, then
the list is replaced.
{% comment %}
TODO(pwittrock): Uncomment this for 1.6
- Treat the list as a set of primitives. Replace or delete individual
elements. Does not preserve ordering. Does not preserve duplicates.
**Example:** Using apply to update the `finalizers` field of ObjectMeta
keeps elements added to the live configuration. Ordering of finalizers
is lost.
{% endcomment %}
## Default field values
The API server sets certain fields to default values in the live configuration if they are
not specified when the object is created.
Here's a configuration file for a Deployment. The file does not specify `strategy` or `selector`:
{% include code.html language="yaml" file="simple_deployment.yaml" ghlink="/docs/concepts/tools/simple_deployment.yaml" %}
Create the object using `kubectl apply`:
```shell
kubectl apply -f http://k8s.io/docs/concepts/tools/kubectl/simple_deployment.yaml
```
Print the live configuration using `kubectl get`:
```shell
kubectl get -f http://k8s.io/docs/concepts/tools/kubectl/simple_deployment.yaml -o yaml
```
The output shows that the API server set several fields to default values in the live
configuration. These fields were not specified in the configuration file.
```shell
apiVersion: extensions/v1beta1
kind: Deployment
# ...
spec:
minReadySeconds: 5
replicas: 1 # defaulted by apiserver
selector:
matchLabels: # defaulted by apiserver - derived from template.metadata.labels
app: nginx
strategy:
rollingUpdate: # defaulted by apiserver - derived from strategy.type
maxSurge: 1
maxUnavailable: 1
type: RollingUpdate # defaulted apiserver
template:
metadata:
creationTimestamp: null
labels:
app: nginx
spec:
containers:
- image: nginx:1.7.9
imagePullPolicy: IfNotPresent # defaulted by apiserver
name: nginx
ports:
- containerPort: 80
protocol: TCP # defaulted by apiserver
resources: {} # defaulted by apiserver
terminationMessagePath: /dev/termination-log # defaulted by apiserver
dnsPolicy: ClusterFirst # defaulted by apiserver
restartPolicy: Always # defaulted by apiserver
securityContext: {} # defaulted by apiserver
terminationGracePeriodSeconds: 30 # defaulted by apiserver
# ...
```
**Note:** Some of the fields' default values have been derived from
the values of other fields that were specified in the configuration file,
such as the `selector` field.
In a patch request, defaulted fields are not re-defaulted unless they are explicitly cleared
as part of a patch request. This can cause unexpected behavior for
fields that are defaulted based
on the values of other fields. When the other fields are later changed,
the values defaulted from them will not be updated unless they are
explicitly cleared.
For this reason, it is recommended that certain fields defaulted
by the server are explicitly defined in the configuration file, even
if the desired values match the server defaults. This makes it
easier to recognize conflicting values that will not be re-defaulted
by the server.
**Example:**
```yaml
# last-applied-configuration
spec:
template:
metadata:
labels:
app: nginx
spec:
containers:
- name: nginx
image: nginx:1.7.9
ports:
- containerPort: 80
# configuration file
spec:
strategy:
type: Recreate # updated value
template:
metadata:
labels:
app: nginx
spec:
containers:
- name: nginx
image: nginx:1.7.9
ports:
- containerPort: 80
# live configuration
spec:
strategy:
type: RollingUpdate # defaulted value
rollingUpdate: # defaulted value derived from type
maxSurge : 1
maxUnavailable: 1
template:
metadata:
labels:
app: nginx
spec:
containers:
- name: nginx
image: nginx:1.7.9
ports:
- containerPort: 80
# result after merge - ERROR!
spec:
strategy:
type: Recreate # updated value: incompatible with rollingUpdate
rollingUpdate: # defaulted value: incompatible with "type: Recreate"
maxSurge : 1
maxUnavailable: 1
template:
metadata:
labels:
app: nginx
spec:
containers:
- name: nginx
image: nginx:1.7.9
ports:
- containerPort: 80
```
**Explanation:**
1. The user creates a Deployment without defining `strategy.type`.
2. The server defaults `strategy.type` to `RollingUpdate` and defaults the
`strategy.rollingUpdate` values.
3. The user changes `strategy.type` to `Recreate`. The `strategy.rollingUpdate`
values remain at their defaulted values, though the server expects them to be cleared.
If the `strategy.rollingUpdate` values had been defined initially in the configuration file,
it would have been more clear that they needed to be deleted.
4. Apply fails because `strategy.rollingUpdate` is not cleared. The `strategy.rollingupdate`
field cannot be defined with a `strategy.type` of `Recreate`.
Recommendation: These fields should be explicitly defined in the object configuration file:
- Selectors and PodTemplate labels on workloads, such as Deployment, StatefulSet, Job, DaemonSet,
ReplicaSet, and ReplicationController
- Deployment rollout strategy
### How to clear server-defaulted fields or fields set by other writers
As of Kubernetes 1.5, fields that do not appear in the configuration file cannot be
cleared by a merge operation. Here are some workarounds:
Option 1: Remove the field by directly modifying the live object.
**Note:** As of Kubernetes 1.5, `kubectl edit` does not work with `kubectl apply`.
Using these together will cause unexpected behavior.
Option 2: Remove the field through the configuration file.
1. Add the field to the configuration file to match the live object.
1. Apply the configuration file; this updates the annotation to include the field.
1. Delete the field from the configuration file.
1. Apply the configuration file; this deletes the field from the live object and annotation.
{% comment %}
TODO(1.6): Update this with the following for 1.6
Fields that do not appear in the configuration file can be cleared by
setting their values to `null` and then applying the configuration file.
For fields defaulted by the server, this triggers re-defaulting
the values.
{% endcomment %}
## How to change ownership of a field between the configuration file and direct imperative writers
These are the only methods you should use to change an individual object field:
- Use `kubectl apply`.
- Write directly to the live configuration without modifying the configuration file:
for example, use `kubectl scale`.
### Changing the owner from a direct imperative writer to a configuration file
Add the field to the configuration file. For the field, discontinue direct updates to
the live configuration that do not go through `kubectl apply`.
### Changing the owner from a configuration file to a direct imperative writer
As of Kubernetes 1.5, changing ownership of a field from a configuration file to
an imperative writer requires manual steps:
- Remove the field from the configuration file.
- Remove the field from the `kubectl.kubernetes.io/last-applied-configuration` annotation on the live object.
## Changing management methods
Kubernetes objects should be managed using only one method at a time.
Switching from one method to another is possible, but is a manual process.
**Exception:** It is OK to use imperative deletion with declarative management.
{% comment %}
TODO(pwittrock): We need to make using imperative commands with
declarative object configuration work so that it doesn't write the
fields to the annotation, and instead. Then add this bullet point.
- using imperative commands with declarative configuration to manage where each manages different fields.
{% endcomment %}
### Migrating from imperative command management to declarative object configuration
Migrating from imperative command management to declarative object
configuration involves several manual steps:
1. Export the live object to a local configuration file:
kubectl get <kind>/<name> -o yaml --export > <kind>_<name>.yaml
1. Manually remove the `status` field from the configuration file.
**Note:** This step is optional, as `kubectl apply` does not update the status field
even if it is present in the configuration file.
1. Set the `kubectl.kubernetes.io/last-applied-configuration` annotation on the object:
kubectl replace --save-config -f <kind>_<name>.yaml
1. Change processes to use `kubectl apply` for managing the object exclusively.
{% comment %}
TODO(pwittrock): Why doesn't export remove the status field? Seems like it should.
{% endcomment %}
### Migrating from imperative object configuration to declarative object configuration
1. Set the `kubectl.kubernetes.io/last-applied-configuration` annotation on the object:
kubectl replace --save-config -f <kind>_<name>.yaml
1. Change processes to use `kubectl apply` for managing the object exclusively.
## Defining controller selectors and PodTemplate labels
**Warning**: Updating selectors on controllers is strongly discouraged.
The recommended approach is to define a single, immutable PodTemplate label
used only by the controller selector with no other semantic meaning.
**Example:**
```yaml
selector:
matchLabels:
controller-selector: "v1beta1/deployment/nginx"
template:
metadata:
labels:
controller-selector: "v1beta1/deployment/nginx"
```
## Support for ThirdPartyResources
As of Kubernetes 1.5, ThirdPartyResources are not supported by `kubectl apply`.
The recommended approach for ThirdPartyResources is to use [imperative object configuration](/docs/concepts/tools/kubectl/object-management-using-imperative-config/).
{% endcapture %}
{% capture whatsnext %}
- [Managing Kubernetes Objects Using Imperative Commands](/docs/concepts/tools/kubectl/object-management-using-imperative-commands/)
- [Imperative Management of Kubernetes Objects Using Configuration Files](/docs/concepts/tools/kubectl/object-management-using-imperative-config/)
- [Kubectl Command Reference](/docs/user-guide/kubectl/v1.5/)
- [Kubernetes Object Schema Reference](/docs/resources-reference/v1.5/)
{% endcapture %}
{% include templates/concept.md %}
docs/concepts/tools/kubectl/object-management-using-imperative-commands.md
+159
View File
@@ -0,0 +1,159 @@
---
title: Managing Kubernetes Objects Using Imperative Commands
---
{% capture overview %}
Kubernetes objects can quickly be created, updated, and deleted directly using
imperative commands built into the `kubectl` command-line tool. This document
explains how those commands are organized and how to use them to manage live objects.
{% endcapture %}
{% capture body %}
## Trade-offs
The `kubectl` tool supports three kinds of object management:
* Imperative commands
* Imperative object configuration
* Declarative object configuration
See [Kubernetes Object Management](/docs/concepts/tools/kubectl/object-management-overview/)
for a discussion of the advantages and disadvantage of each kind of object management.
## How to create objects
The `kubectl` tool supports verb-driven commands for creating some of the most common
object types. The commands are named to be recognizable to users unfamiliar with
the Kubernetes object types.
- `run`: Create a new Deployment object to run Containers in one or more Pods.
- `expose`: Create a new Service object to load balance traffic across Pods.
- `autoscale`: Create a new Autoscaler object to automatically horizontally scale a controller, such as a Deployment.
The `kubectl` tool also supports creation commands driven by object type.
These commands support more object types and are more explicit about
their intent, but require users to know the type of objects they intend
to create.
- `create <objecttype> [<subtype>] <instancename>`
Some objects types have subtypes that you can specify in the `create` command.
For example, the Service object has several subtypes including ClusterIP,
LoadBalancer, and NodePort. Here's an example that creates a Service with
subtype NodePort:
```shell
kubectl create service nodeport <myservicename>
```
In the preceding example, the `create service nodeport` command is called
a subcommand of the `create service` command.
You can use the `-h` flag to find the arguments and flags supported by
a subcommand:
```shell
kubectl create service nodeport -h
```
## How to update objects
The `kubectl` command supports verb-driven commands for some common update operations.
These commands are named to enable users unfamiliar with Kubernetes
objects to perform updates without knowing the specific fields
that must be set:
- `scale`: Horizontally scale a controller to add or remove Pods by updating the replica count of the controller.
- `annotate`: Add or remove an annotation from an object.
- `label`: Add or remove a label from an object.
The `kubectl` command also supports update commands driven by an aspect of the object.
Setting this aspect may set different fields for different object types:
- `set` <field>: Set an aspect of an object.
**Note**: In Kubernetes version 1.5, not every verb-driven command has an
associated field-driven command.
The `kubectl` tool supports these additional ways to update a live object directly,
however they require a better understanding of the Kubernetes object schema.
- `edit`: Directly edit the raw configuration of a live object by opening its configuration in an editor.
- `patch`: Directly modify specific fields of a live object by using a patch string.
For more details on patch strings, see the patch section in
[API Conventions](https://github.com/kubernetes/community/blob/master/contributors/devel/api-conventions.md#patch-operations).
## How to delete objects
You can use the `delete` command to delete an object from a cluster:
- `delete <type>/<name>`
**Note**: You can use `kubectl delete` for both imperative commands and imperative object
configuration. The difference is in the arguments passed to the command. To use
`kubectl delete` as an imperative command, pass the object to be deleted as
an argument. Here's an example that passes a Deployment object named nginx:
```shell
kubectl delete deployment/nginx
```
## How to view an object
{% comment %}
TODO(pwittrock): Uncomment this when implemented.
You can use `kubectl view` to print specific fields of an object.
- `view`: Prints the value of a specific field of an object.
{% endcomment %}
There are several commands for printing information about an object:
- `get`: Prints basic information about matching objects. Use `get -h` to see a list of options.
- `describe`: Prints aggregated detailed information about matching objects.
- `logs`: Prints the stdout and stderr for a container running in a Pod.
## Using `set` commands to modify objects before creation
There are some object fields that don't have a flag you can use
in a `create` command. In some of those cases, you can use a combination of
`set` and `create` to specify a value for the field before object
creation. This is done by piping the output of the `create` command to the
`set` command, and then back to the `create` command. Here's an example:
```sh
kubectl create service clusterip <myservicename> -o yaml --dry-run | kubectl set selector --local -f - 'environment=qa' -o yaml | kubectl create -f -
```
1. The `create service -o yaml --dry-run` command creates the configuration for the Service, but prints it to stdout as YAML instead of sending it to the Kubernetes API server.
1. The `set --local -f - -o yaml` command reads the configuration from stdin, and writes the updated configuration to stdout as YAML.
1. The `kubectl create -f -` command creates the object using the configuration provided via stdin.
## Using `--edit` to modify objects before creation
You can use `kubectl create --edit` to make arbitrary changes to an object
before it is created. Here's an example:
```sh
kubectl create service clusterip my-svc -o yaml --dry-run > /tmp/srv.yaml
kubectl create --edit -f /tmp/srv.yaml
```
1. The `create service` command creates the configuration for the Service and saves it to `/tmp/srv.yaml`.
1. The `create --edit` command opens the configuration file for editing before it creates the object.
{% endcapture %}
{% capture whatsnext %}
- [Managing Kubernetes Objects Using Object Configuration (Imperative)](/docs/concepts/tools/kubectl/object-management-using-imperative-config/)
- [Managing Kubernetes Objects Using Object Configuration (Declarative)](/docs/concepts/tools/kubectl/object-management-using-declarative-config/)
- [Kubectl Command Reference](/docs/user-guide/kubectl/v1.5/)
- [Kubernetes Object Schema Reference](/docs/resources-reference/v1.5/)
{% endcapture %}
{% include templates/concept.md %}
docs/concepts/tools/kubectl/object-management-using-imperative-config.md
+129
View File
@@ -0,0 +1,129 @@
---
title: Imperative Management of Kubernetes Objects Using Configuration Files
---
{% capture overview %}
Kubernetes objects can be created, updated, and deleted by using the `kubectl`
command-line tool along with an object configuration file written in YAML or JSON.
This document explains how to define and manage objects using configuration files.
{% endcapture %}
{% capture body %}
## Trade-offs
The `kubectl` tool supports three kinds of object management:
* Imperative commands
* Imperative object configuration
* Declarative object configuration
See [Kubernetes Object Management](/docs/concepts/tools/kubectl/object-management-overview/)
for a discussion of the advantages and disadvantage of each kind of object management.
## How to create objects
You can use `kubectl create -f` to create an object from a configuration file.
Refer to the [kubernetes object schema reference](/docs/resources-reference/v1.5/)
for details.
- `create -f <filename|url>`
## How to update objects
You can use `kubectl replace -f` to update a live object according to a
configuration file.
- `replace -f <filename|url>`
## How to delete objects
You can use `kubectl delete -f` to delete an object that is described in a
configuration file.
- `delete -f <filename|url>`
## How to view an object
You can use `kubectl get -f` to view information about an object that is
described in a configuration file.
- `get -f <filename|url> -o yaml`
The `-o yaml` flag specifies that the full object configuration is printed.
Use `get -h` to see a list of options.
## Limitations
The `create`, `replace`, and `delete` commands work well when each object's
configuration is fully defined and recorded in its configuration
file. However when a live object is updated, and the updates are not merged
into its configuration file, the updates will be lost the next time a `replace`
is executed. This is can happen if a controller, such as
a HorizontalPodAutoscaler, makes updates directly to a live object. Here's
an example:
1. You create an object from a configuration file.
1. Another source updates the object by changing some field.
1. You replace the object from the configuration file. Changes made by
the other source in step 2 are lost.
If you need to support multiple writers to the same object, you can use
`kubectl apply` to manage the object.
## Creating and editing an object from a URL without saving the configuration
Suppose you have the URL of an object configuration file. You can use
`kubectl create --edit` to make changes to the configuration before the
object is created. This is particularly useful for tutorials and tasks
that point to a configuration file that could be modified by the reader.
```sh
kubectl create -f <url> --edit
```
## Migrating from imperative commands to imperative object configuration
Migrating from imperative commands to imperative object configuration involves
several manual steps.
1. Export the live object to a local object configuration file:
kubectl get <kind>/<name> -o yaml --export > <kind>_<name>.yaml
1. Manually remove the status field from the object configuration file.
1. For subsequent object management, use `replace` exclusively.
kubectl replace -f <kind>_<name>.yaml
## Defining controller selectors and PodTemplate labels
**Warning**: Updating selectors on controllers is strongly discouraged.
The recommended approach is to define a single, immutable PodTemplate label
used only by the controller selector with no other semantic meaning.
Example label:
```yaml
selector:
matchLabels:
controller-selector: "v1beta1/deployment/nginx"
template:
metadata:
labels:
controller-selector: "v1beta1/deployment/nginx"
```
{% endcapture %}
{% capture whatsnext %}
- [Managing Kubernetes Objects Using Imperative Commands](/docs/concepts/tools/kubectl/object-management-using-imperative-commands/)
- [Managing Kubernetes Objects Using Object Configuration (Declarative)](/docs/concepts/tools/kubectl/object-management-using-declarative-config/)
- [Kubectl Command Reference](/docs/user-guide/kubectl/v1.5/)
- [Kubernetes Object Schema Reference](/docs/resources-reference/v1.5/)
{% endcapture %}
{% include templates/concept.md %}
docs/concepts/tools/kubectl/simple_deployment.yaml
+16
View File
@@ -0,0 +1,16 @@
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: nginx-deployment
spec:
minReadySeconds: 5
template:
metadata:
labels:
app: nginx
spec:
containers:
- name: nginx
image: nginx:1.7.9
ports:
- containerPort: 80
docs/concepts/tools/kubectl/update_deployment.yaml
+15
View File
@@ -0,0 +1,15 @@
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: nginx-deployment
spec:
template:
metadata:
labels:
app: nginx
spec:
containers:
- name: nginx
image: nginx:1.11.9 # update the image
ports:
- containerPort: 80
docs/getting-started-guides/binary_release.md
+1 -1
View File
@@ -33,7 +33,7 @@ cd kubernetes
make release
```
For more details on the release process see the [`build-tools/`](http://releases.k8s.io/{{page.githubbranch}}/build-tools/) directory
For more details on the release process see the [`build`](http://releases.k8s.io/{{page.githubbranch}}/build/) directory
### Download Kubernetes and automatically set up a default cluster