In this section, it will introduce how to use CUE to declare app components via
Before reading this part, please make sure you've learned the Definition CRD in KubeVela.
Here is a CUE based
ComponentDefinition example which provides a abstraction for stateless workload type:
.spec.workloadis required to indicate the workload type of this component.
.spec.schematic.cue.templateis a CUE template, specifically:
outputfiled defines the template for the abstraction.
parameterfiled defines the template parameters, i.e. the configurable properties exposed in the
Applicationabstraction (and JSON schema will be automatically generated based on them).
Let's declare another component named
task, i.e. an abstraction for run-to-completion workload.
ComponentDefinition objects to files and install them to your Kubernetes cluster by
$ kubectl apply -f stateless-def.yaml task-def.yaml
ComponentDefinition can be instantiated in
Application abstraction as below:
Above application resource will generate and manage following Kubernetes resources in your target cluster based on the
output in CUE template and user input in
KubeVela allows you to reference the runtime information of your application via
The most widely used context is application name(
context.appName) component name(
For example, let's say you want to use the component name filled in by users as the container name in the workload instance:
contextinformation are auto-injected before resources are applied to target cluster.
Full available information in CUE
|The revision of the application|
|The revision number(|
|The name of the application|
|The name of the component of the application|
|The namespace of the application|
|The rendered workload API resource of the component, this usually used in trait|
|The rendered trait API resource of the component, this usually used in trait|
It's common that a component definition is composed by multiple API resources, for example, a
webserver component that is composed by a Deployment and a Service. CUE is a great solution to achieve this in simplified primitives.
Another approach to do composition in KubeVela of course is using Helm.
KubeVela requires you to define the template of workload type in
output section, and leave all the other resource templates in
outputs section with format as below:
The reason for this requirement is KubeVela needs to know it is currently rendering a workload so it could do some "magic" like patching annotations/labels or other data during it.
Below is the example for
The user could now declare an
Application with it:
It will generate and manage below API resources in target cluster:
Please check the Learning CUE documentation about why we support CUE as first-class templating solution and more details about using CUE efficiently.