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Version: v1.0

Resource Model

This documentation will explain the core resource model of KubeVela which is fully powered by Open Application Model (OAM).

Application#

The Application is the core API of KubeVela. It allows application team to work with a single artifact to capture the complete application deployment with simplified primitives.

This provides a simpler path for on-boarding application team to the platform without leaking low level details in runtime infrastructure. For example, they will be able to declare a "web service" without defining a detailed Kubernetes Deployment + Service combo each time, or claim the auto-scaling requirements without referring to the underlying KEDA ScaleObject. They can also declare a cloud database with same API if they want.

Every application is composed by multiple components with attachable operational behaviors (traits). For example:

apiVersion: core.oam.dev/v1beta1
kind: Application
metadata:
name: application-sample
spec:
components:
- name: foo
type: webservice
properties:
image: crccheck/hello-world
port: 8000
traits:
- type: ingress
properties:
domain: testsvc.example.com
http:
"/": 8000
- type: sidecar
properties:
name: "logging"
image: "fluentd"
- name: bar
type: aliyun-oss # cloud service
bucket: "my-bucket"

The Application resource in KubeVela is a LEGO-style entity and does not even have fixed schema. Instead, it is assembled by below building block entities that are maintained by the platform team. Though the application object doesn't have fixed schema, it is a composition object assembled by several programmable building blocks as shown below.

Component#

The component model (ComponentDefinition API) is designed to allow component providers to encapsulate deployable/provisionable entities with a wide range of tools, and hence give a easier path to application team to deploy complicated microservices across hybrid environments at ease. A component normally carries its workload type description (i.e. WorkloadDefinition), a encapsulation module with a parameter list.

Hence, a components provider could be anyone who packages software components in form of Helm chart of CUE modules. Think about 3rd-party software distributor, DevOps team, or even your CI pipeline.

Components are shareable and reusable. For example, by referencing the same Alibaba Cloud RDS component and setting different parameter values, application team could easily provision Alibaba Cloud RDS instances of different sizes in different availability zones.

Application team will use the Application entity to declare how they want to instantiate and deploy a group of certain components. In above example, it describes an application composed with Kubernetes stateless workload (component foo) and a Alibaba Cloud OSS bucket (component bar) alongside.

How it Works?#

In above example, type: worker means the specification of this component (claimed in following properties section) will be enforced by a ComponentDefinition object named worker as below:

apiVersion: core.oam.dev/v1beta1
kind: ComponentDefinition
metadata:
name: worker
annotations:
definition.oam.dev/description: "Describes long-running, scalable, containerized services that running at backend. They do NOT have network endpoint to receive external network traffic."
spec:
workload:
definition:
apiVersion: apps/v1
kind: Deployment
schematic:
cue:
template: |
output: {
apiVersion: "apps/v1"
kind: "Deployment"
spec: {
selector: matchLabels: {
"app.oam.dev/component": context.name
}
template: {
metadata: labels: {
"app.oam.dev/component": context.name
}
spec: {
containers: [{
name: context.name
image: parameter.image
if parameter["cmd"] != _|_ {
command: parameter.cmd
}
}]
}
}
}
}
parameter: {
image: string
cmd?: [...string]
}

Hence, the properties section of backend only exposes two parameters to fill: image and cmd, this is enforced by the parameter list of the .spec.template field of the definition.

Traits#

Traits (TraitDefinition API) are operational features provided by the platform. A trait augments the component instance with operational behaviors such as load balancing policy, network ingress routing, auto-scaling policies, or upgrade strategies, etc.

To attach a trait to component instance, the user will declare .type field to reference the specific TraitDefinition, and .properties field to set property values of the given trait. Similarly, TraitDefiniton also allows you to define template for operational features.

In the above example, type: autoscaler in frontend means the specification (i.e. properties section) of this trait will be enforced by a TraitDefinition object named autoscaler as below:

apiVersion: core.oam.dev/v1beta1
kind: TraitDefinition
metadata:
annotations:
definition.oam.dev/description: "configure k8s HPA for Deployment"
name: hpa
spec:
appliesToWorkloads:
- deployments.apps
schematic:
cue:
template: |
outputs: hpa: {
apiVersion: "autoscaling/v2beta2"
kind: "HorizontalPodAutoscaler"
metadata: name: context.name
spec: {
scaleTargetRef: {
apiVersion: "apps/v1"
kind: "Deployment"
name: context.name
}
minReplicas: parameter.min
maxReplicas: parameter.max
metrics: [{
type: "Resource"
resource: {
name: "cpu"
target: {
type: "Utilization"
averageUtilization: parameter.cpuUtil
}
}
}]
}
}
parameter: {
min: *1 | int
max: *10 | int
cpuUtil: *50 | int
}

The application also have a sidecar trait.

apiVersion: core.oam.dev/v1beta1
kind: TraitDefinition
metadata:
annotations:
definition.oam.dev/description: "add sidecar to the app"
name: sidecar
spec:
appliesToWorkloads:
- deployments.apps
schematic:
cue:
template: |-
patch: {
// +patchKey=name
spec: template: spec: containers: [parameter]
}
parameter: {
name: string
image: string
command?: [...string]
}

Please note that the application team do NOT need to know about definition objects, they learn how to use a given capability with visualized forms (or the JSON schema of parameters if they prefer). Please check the Generate Forms from Definitions section about how this is achieved.

Standard Contract Behind The Abstractions#

Once the application is deployed, KubeVela will index and manage the underlying instances with name, revisions, labels and selector etc in automatic approach. These metadata are shown as below.

LabelDescription
workload.oam.dev/type=<component definition name>The name of its corresponding ComponentDefinition
trait.oam.dev/type=<trait definition name>The name of its corresponding TraitDefinition
app.oam.dev/name=<app name>The name of the application it belongs to
app.oam.dev/component=<component name>The name of the component it belongs to
trait.oam.dev/resource=<name of trait resource instance>The name of trait resource instance
app.oam.dev/appRevision=<name of app revision>The name of the application revision it belongs to

Consider these metadata as a standard contract for any "day 2" operation controller such as rollout controller to work on KubeVela deployed applications. This is the key to ensure the interoperability for KubeVela based platform as well.

No Configuration Drift#

Despite the efficiency and extensibility in abstracting application deployment, IaC (Infrastructure-as-Code) tools may lead to an issue called Infrastructure/Configuration Drift, i.e. the generated component instances are not in line with the expected configuration. This could be caused by incomplete coverage, less-than-perfect processes or emergency changes. This makes them can be barely used as a platform level building block.

Hence, KubeVela is designed to maintain all these programmable capabilities with Kubernetes Control Loop and leverage Kubernetes control plane to eliminate the issue of configuration drifting, while still keeps the flexibly and velocity enabled by IaC.

Last updated on by kubevela-bot