Distribute Reference Objects

note

This section requires you to know the basics about how to deploy multi-cluster application with policy and workflow.

You can reference and distribute existing Kubernetes objects with KubeVela in the following scenarios:

• Copying secrets from the hub cluster into managed clusters.
• Promote deployments from canary clusters into production clusters.
• Using Kubernetes apiserver as the control plane and storing all Kubernetes objects data in external databases. Then dispatch those data into real Kuberenetes managed clusters.

Besides, you can also refer to Kubernetes objects from remote URL links.

Refer to Existing Kubernetes Objects in Component

Refer to objects in cluster

To use existing Kubernetes objects in the component, you need to use the ref-objects typed component and declare which resources you want to refer to. For example, in the following example, the secret image-credential-to-copy in namespace examples will be taken as the source object for the component. Then you can use the topology policy to dispatch it into hangzhou clusters.

apiVersion: core.oam.dev/v1beta1
kind: Application
metadata:
  name: ref-objects-example
  namespace: examples
spec:
  components:
    - name: image-pull-secrets
      type: ref-objects
      properties:
        objects:
          - resource: secret
            name: image-credential-to-copy
  policies:
    - name: topology-hangzhou-clusters
      type: topology
      properties:
        clusterLabelSelector:
          region: hangzhou

Refer to objects from URL

If your source Kubernetes objects are from remote URLs, you can also refer to them in the component properties as follows. Your remote URL files could include multiple-resources as well.

apiVersion: core.oam.dev/v1beta1
kind: Application
metadata:
  name: example-app
  namespace: default
spec:
  components:
  - name: busybox
    type: ref-objects
    properties:
      urls: ["https://gist.githubusercontent.com/Somefive/b189219a9222eaa70b8908cf4379402b/raw/e603987b3e0989e01e50f69ebb1e8bb436461326/example-busybox-deployment.yaml"]

Details for the ref-objects typed component

The most simple way to specify resources is to directly use resource: secret or resource: deployment to describe the kind of resources. If no name or labelSelector is set, the application will try to find the resource with the same name as the component name in the application's namespace. You can also explicitly specify name and namespace for the target resource as well.

In addition to name and namespace, you can also specify the cluster field to let the application component refer to resources in managed clusters. You can also use the labelSelector to select resources in replace of finding resources by names.

In the following example, the application will select all deployments in the hangzhou-1 cluster inside the examples namespace, which matches the desided labels. Then the application will copy these deployments into hangzhou-2 cluster.

apiVersion: core.oam.dev/v1beta1
kind: Application
metadata:
  name: ref-objects-duplicate-deployments
  namespace: examples
spec:
  components:
    - name: duplicate-deployment
      type: ref-objects
      properties:
        objects:
          - resource: deployment
            cluster: hangzhou-1
            # select all deployment in the `examples` namespace in cluster `hangzhou-1` that matches the labelSelector
            labelSelector:
              need-duplicate: "true"
  policies:
    - name: topology-hangzhou-2
      type: topology
      properties:
        clusters: ["hangzhou-2"]

In some cases, you might want to restrict the scope for the application to access resources. You can set the --ref-objects-available-scope to namespace or cluster in KubeVela controller's bootstrap parameter, to retrict the application to be only able to refer to the resources inside the same namespace or the same cluster.

Override Configuration for Reference Objects

The override policy can be used to override properties defined in component and traits while the reference objects don't have those properties.

If you want to override configuration for the ref-objects typed component, you can use traits. The implicit main workload is the first referenced object and trait patch will be applied on it. The following example demonstrate how to set the replica number for the referenced deployment while deploying it in hangzhou clusters.

apiVersion: core.oam.dev/v1beta1
kind: Application
metadata:
  name: ref-objects-multiple-resources
  namespace: examples
spec:
  components:
    - name: nginx-ref-multiple-resources
      type: ref-objects
      properties:
        objects:
          - resource: deployment
          - resource: service
      traits:
        - type: scaler
          properties:
            replicas: 3
  policies:
    - name: topology-hangzhou-clusters
      type: topology
      properties:
        clusterLabelSelector:
          region: hangzhou

There are several commonly used trait that could be used together with the ref-objects, particularly for Deployment.

Override Container Image

The container-image trait can be used to change the default image settings declared in the original deployment.

By default, the container-image will replace the original image in the main container (the container uses the name of the component).

traits:
- type: container-image
  properties:
    image: busybox-1.34.0

You can modify other containers by setting the containerName field.

traits:
- type: container-image
  properties:
    image: busybox-1.34.0
    containerName: sidecar-nginx

You can also modify the ImagePullPolicy as well.

traits:
- type: container-image
  properties:
    image: busybox-1.34.0
    containerName: sidecar-nginx
    imagePullPolicy: IfNotPresent

Multiple container patch is also available.

traits:
- type: container-image
  properties:
    containers:
      - containerName: busybox
        image: busybox-1.34.0
        imagePullPolicy: IfNotPresent
      - containerName: sidecar-nginx
        image: nginx-1.20

Override Container Command

The command trait can be used to modify the original running command in deployment's pods.

traits:
- type: command
  properties:
    command: ["sleep", "8640000"]

The above configuration can be used to patch the main container (the container that uses the name of the component). If you would like to modify another container, you could use the field containerName.

traits:
- type: command
  properties:
    command: ["sleep", "8640000"]
    containerName: sidecar-nginx

If you want to replace the existing args in the container, instead of the command, use the args parameter.

traits:
- type: command
  properties:
    args: ["86400"]

If you want to append/delete args to the existing args, use the addArgs/delArgs parameter. This can be useful if you have lots of args to be managed.

traits:
- type: command
  properties:
    addArgs: ["86400"]

traits:
- type: command
  properties:
    delArgs: ["86400"]

You can also configure commands in multiple containers.

traits:
- type: command
  properties:
    containers:
      - containerName: busybox
        command: ["sleep", "8640000"]
      - containerName: sidecar-nginx
        args: ["-q"]

Override Container Environment Variable

With the trait env, you can easily manipulate the declared environment variables.

For example, the following usage shows how to set multiple environment variables in the main container (the container uses the component's name). If any environment variable does not exist, it will be added. If exists, it will be updated.

traits:
- type: env
  properties:
    env:
      key_first: value_first
      key_second: value_second

You can remove existing environment variables by setting the unset field.

traits:
- type: env
  properties:
    unset: ["key_existing_first", "key_existing_second"]

If you would like to clear all the existing environment variables first, and then add new variables, use replace: true.

traits:
- type: env
  properties:
    env:
      key_first: value_first
      key_second: value_second
    replace: true

If you want to modify the environment variable in other containers, use the containerName field.

traits:
- type: env
  properties:
    env:
      key_first: value_first
      key_second: value_second
    containerName: sidecar-nginx

You can set environment variables in multiple containers as well.

traits:
- type: env
  properties:
    containers:
      - containerName: busybox
        env:
          key_for_busybox_first: value_first
          key_for_busybox_second: value_second
      - containerName: sidecar-nginx
        env:
          key_for_nginx_first: value_first
          key_for_nginx_second: value_second

Override Labels & Annotations

To add/update/remove labels or annotations for the workload (like Kubernetes Deployment), use the labels or annotations trait.

traits:
  # the `labels` trait will add/delete label key/value pair to the
  # labels of the workload and the template inside the spec of the workload (if exists)
  # 1. if original labels contains the key, value will be overridden
  # 2. if original labels do not contain the key, value will be added
  # 3. if original labels contains the key and the value is null, the key will be removed
  - type: labels
    properties:
      added-label-key: added-label-value
      label-key: modified-label-value
      to-delete-label-key: null

traits:
  # the `annotations` trait will add/delete annotation key/value pair to the
  # labels of the workload and the template inside the spec of the workload (if exists)
  # 1. if original annotations contains the key, value will be overridden
  # 2. if original annotations do not contain the key, value will be added
  # 3. if original annotations contains the key and the value is null, the key will be removed
  - type: annotations
    properties:
      added-annotation-key: added-annotation-value
      annotation-key: modified-annotation-value
      to-delete-annotation-key: null

Override by using JSON Patch & JSON Merge Patch

Except for the above trait, a more powerful but more complex way to modify the original resources is to use the json-patch or json-merge-patch trait. They follow the RFC 6902 and RFC 7386 respectively. Usage examples are shown below.

 traits:
# the json patch can be used to add, replace and delete fields
# the following part will
# 1. add `deploy-label-key` to deployment labels
# 2. set deployment replicas to 3
# 3. set `pod-label-key` to `pod-label-modified-value` in pod labels
# 4. delete `to-delete-label-key` in pod labels
# 5. add sidecar container for pod
- type: json-patch
  properties:
    operations:
      - op: add
        path: "/spec/replicas"
        value: 3
      - op: replace
        path: "/spec/template/metadata/labels/pod-label-key"
        value: pod-label-modified-value
      - op: remove
        path: "/spec/template/metadata/labels/to-delete-label-key"
      - op: add
        path: "/spec/template/spec/containers/1"
        value:
          name: busybox-sidecar
          image: busybox:1.34
          command: ["sleep", "864000"]

traits:
# the json merge patch can be used to add, replace and delete fields
# the following part will
# 1. add `deploy-label-key` to deployment labels
# 2. set deployment replicas to 3
# 3. set `pod-label-key` to `pod-label-modified-value` in pod labels
# 4. delete `to-delete-label-key` in pod labels
# 5. reset `containers` for pod
- type: json-merge-patch
  properties:
    metadata:
      labels:
        deploy-label-key: deploy-label-added-value
    spec:
      replicas: 3
      template:
        metadata:
          labels:
            pod-label-key: pod-label-modified-value
            to-delete-label-key: null
        spec:
          containers:
            - name: busybox-new
              image: busybox:1.34
              command: ["sleep", "864000"]

Distribute Reference Objects with different configuration

The general idea is to using override policy to override traits. Then you can distribute reference objects with different traits for different clusters.

Assume we're distributing the following Deployment YAML to multi-clusters:

apiVersion: apps/v1
kind: Deployment
metadata:
  labels:
    app: demo
  name: demo
  namespace: demo
spec:
  replicas: 1
  selector:
    matchLabels:
      app: demo
  template:
    metadata:
      labels:
        app: demo
    spec:
      containers:
      - image: oamdev/testapp:v1
        name: demo

We can specify the following topology policies.

apiVersion: core.oam.dev/v1alpha1
kind: Policy
metadata:
  name: cluster-beijing
  namespace: demo
type: topology
properties:
  clusters: ["<clusterid1>"]
---
apiVersion: core.oam.dev/v1alpha1
kind: Policy
metadata:
  name: cluster-hangzhou
  namespace: demo
type: topology
properties:
  clusters: ["<clusterid2>"]

Then we can use override policy to override with different traits for the reference objects.

apiVersion: core.oam.dev/v1alpha1
kind: Policy
metadata:
  name: override-replic-beijing
  namespace: demo
type: override
properties:
  components:
  - name: "demo"
    traits:
    - type: scaler
      properties:
        replicas: 3
---
apiVersion: core.oam.dev/v1alpha1
kind: Policy
metadata:
  name: override-replic-hangzhou
  namespace: demo
type: override
properties:
  components:
  - name: "demo"
    traits:
    - type: scaler
      properties:
        replicas: 5

The workflow can be defined like:

apiVersion: core.oam.dev/v1alpha1
kind: Workflow
metadata:
  name: deploy-demo
  namespace: demo
steps:
  - type: deploy
    name: deploy-bejing
    properties:
      policies: ["override-replic-beijing", "cluster-beijing"]
  - type: deploy
    name: deploy-hangzhou
    properties:
      policies: ["override-replic-hangzhou", "cluster-hangzhou"]

As a result, we can combine them and trigger the final deploy by the following application:

apiVersion: core.oam.dev/v1beta1
kind: Application
metadata:
  name: demo
  namespace: demo
  annotations:
    app.oam.dev/publishVersion: version1
spec:
  components:
    - name: demo
      type: ref-objects
      properties:
        objects:
          - apiVersion: apps/v1
            kind: Deployment
            name: demo
  workflow:
    ref: deploy-demo

With the help of KubeVela, you can reference and distribute any Kubernetes resources to multi clusters.