--- title: 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: ```yaml 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: ```yaml 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: ```yaml apiVersion: core.oam.dev/v1beta1 kind: TraitDefinition metadata: annotations: definition.oam.dev/description: "configure k8s HPA for Deployment" name: hpa spec: appliesToWorkloads: - webservice - worker 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. ```yaml apiVersion: core.oam.dev/v1beta1 kind: TraitDefinition metadata: annotations: definition.oam.dev/description: "add sidecar to the app" name: sidecar spec: appliesToWorkloads: - webservice - worker 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](openapi-v3-json-schema) 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. | Label | Description | | :--: | :---------: | |`workload.oam.dev/type=` | The name of its corresponding `ComponentDefinition` | |`trait.oam.dev/type=` | The name of its corresponding `TraitDefinition` | |`app.oam.dev/name=` | The name of the application it belongs to | |`app.oam.dev/component=` | The name of the component it belongs to | |`trait.oam.dev/resource=` | The name of trait resource instance | |`app.oam.dev/appRevision=` | 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](https://kubernetes.io/docs/concepts/architecture/controller/) and leverage Kubernetes control plane to eliminate the issue of configuration drifting, while still keeps the flexibly and velocity enabled by IaC.