--- title: K8S API for Pipeline --- Compared with the Application Workflow, the standalone pipeline has the following characteristics: 1. It can manage multiple KubeVela Applications across multiple environments. 2. It is **not bound** to Applications and can be used **independently**. For example, it can expand or shrink a set of resources, perform process-oriented canary publishing for an Application, and perform a set of operation and maintenance operations in batches. 3. It is **one-time** and does not manage resources. Even if the pipeline is deleted, the created resources will not be deleted. 4. It uses the same execution engine as the Application Workflow, which completely inherits the features of KubeVela's lightweight workflow. Compared with the traditional container-based CI pipeline, KubeVela's pipeline does not depend on containers, No additional computing resources are required. :::tip In order to better reuse the existing capabilities and ensure technical consistency, we split the workflow engine part of the original application workflow. Both in-application workflow and pipeline use this [workflow engine](https://github.com/kubevela/workflow) as the underlying technology implementation. The application workflow is represented by the `Workflow` field in the application, and the pipeline is represented by the [WorkflowRun](https://github.com/kubevela/workflow) resource. This means that most of the workflow steps are common between the two, such as: suspend, notification, send HTTP request, read configuration, etc. However, in WorkflowRun, there is only the configuration of steps, and **no configuration of components, traits, and policies**. Therefore, steps related to components/traits/policy can only be used in in-app workflows, such as: deploying/updating components, traits, etc. ::: ## Before starting Please make sure that you have enabled workflow addon: ``` vela addon enable vela-workflow ``` ## WorkflowRun WorkflowRun is the K8S API for pipeline. You can choose to execute an external Workflow template in the WorkflowRun or execute the steps in the WorkflowRun spec (if you declare both, the step in the WorkflowRun spec will override the content in the template). A WorkflowRun consists of the following: ``` apiVersion: core.oam.dev/v1alpha1 kind: WorkflowRun metadata: name: namespace: spec: mode: steps: subSteps: context: workflowRef: workflowSpec: steps: - name: type: dependsOn: meta: alias: properties: if: timeout: outputs: - name: valueFrom: inputs: - name: parameterKey: subSteps: ``` ## Status ### WorkflowRun Status WorkflowRun has the following status: | WorkflowRun State | Description | | :---------------: | :-----------------------------------------------------------------------------------------------------------------------: | | executing | When a step in a WorkflowRun is executing, its status is executing | | suspending | When a step in a WorkflowRun is suspended, its status is suspending | | terminated | When a WorkflowRun is terminated, its status is terminated | | failed | When the WorkflowRun is executed completely and a step fails, its status is failed | | succeeded | When the WorkflowRun is executed completely and the status of all steps is successful or skipped, its status is succeeded | ### WorkflowRun Step Status WorkflowRun steps have the following status: | Step Status | Description | | :---------: | :---------------------------------------------------------------------------------: | | running | This step is being executed | | succeeded | The step is executed successfully | | failed | The step failed | | skipped | The step is skipped and not executed | | pending | The step is wait for certain conditions to execute, such as: waiting for the inputs | #### The Failed Reason of WorkflowRun Step For steps that fail to execute, the `message` of the step status will display the failed message, and the `reason` will display the failed reason, which is divided into the following types: | Step Failed Reason | Description | | :----------------: | :---------------------------------------------------------------------------------------------: | | Execute | The step fails in execution | | Terminate | The step is terminated | | Output | The step has an error when outputting the Output | | FailedAfterRetries | The Step fails in execution and the retry limit is reached | | Timeout | The step is timeout | | Action | [op.#Fail](../../platform-engineers/workflow/cue-actions.md#fail) is used in the step's definition | ## Execution Mode You can define execution mode in WorkflowRun or Workflow templates: ``` mode: steps: subSteps: ``` If not explicitly specified, the WorkflowRun will execute the steps sequentially (StepByStep) and execute sub-steps in parallel (DAG) by default. :::caution If you specify the execution mode in both WorkflowRun and Workflow, the mode in WorkflowRun will override the mode in the Workflow template. ::: ## Built-in Steps You can use KubeVela [built-in steps](../workflow/built-in-workflow-defs.md) that without label: `custom.definition.oam.dev/scope: Application` in WorkflowRun. ## Custom Steps You can refer to the [custom steps documentation](../../platform-engineers/workflow/workflow.md) to customize your steps. :::caution You cannot use [application operations](../../platform-engineers/workflow/cue-actions.md#application-operations). ::: ## Core Features ### Operate WorkflowRun :::tip The vela workflow command can operate both Application Workflow and WorkflowRun. By default, it will look for the application with the same name first, and if it is not found, it will look for WorkflowRun. You can also use `--type=workflow` to indicate that the operation object is WorkflowRun. ::: #### Suspend If you have an executing WorkflowRun, you can use `vela workflow suspend` to suspend the workflow. ```bash vela workflow suspend ``` :::tip If the workflow has executed completely, using the `vela workflow suspend` command has no effect. ::: #### Resume When the WorkflowRun is suspended, you can use `vela workflow resume` command to manually resume the workflow. ```bash vela workflow resume ``` #### Terminate If you have an executing WorkflowRun, you can use `vela workflow terminate` to terminate the workflow. ```bash vela workflow terminate ``` #### Check the Logs If you want to view the WorkflowRun logs, you can use `vela workflow logs` command to view the logs. :::tip Only steps configured with [op.#Log](../../platform-engineers/workflow/cue-actions.md#log) in its definition will have log output. ::: ```bash vela workflow logs ``` ### Suspend and Resume #### Suspend Manually Please refer to [Operate WorkflowRun](#suspend). #### Suspend Automatically(using suspend step) ```yaml apiVersion: core.oam.dev/v1alpha1 kind: WorkflowRun metadata: name: suspend namespace: default spec: workflowSpec: steps: - name: step1 type: apply-deployment properties: image: nginx - name: step2-suspend type: suspend - name: step2 type: apply-deployment properties: image: nginx ``` The WorkflowRun will automatically suspend when the first step is completed, and the third step will not be executed until you continue the WorkflowRun. #### Resume Manually Please refer to [Operate WorkflowRun](#resume). #### Resume Automatically Configure `duration: ` in the `suspend` type of step, when the `duration` time expires, WorkflowRun will automatically continue to execute. ```yaml apiVersion: core.oam.dev/v1alpha1 kind: WorkflowRun metadata: name: suspend namespace: default spec: workflowSpec: steps: - name: step1 type: apply-deployment properties: image: nginx - name: step2-suspend type: suspend properties: duration: 10s - name: step2 type: apply-deployment properties: image: nginx ``` When the first step is completed, the WorkflowRun will suspend, and after ten seconds, the WorkflowRun will automatically continue to execute the third step. ### Sub Steps There is a special step type called `step-group`. When using a `step-group` type of step, you can declare sub steps in it. ```yaml apiVersion: core.oam.dev/v1alpha1 kind: WorkflowRun metadata: name: group namespace: default spec: workflowSpec: steps: - name: my-group type: step-group subSteps: - name: sub1 type: apply-deployment properties: image: nginx - name: sub2 type: apply-deployment properties: image: nginx ``` ### Dependency You can specify dependencies between steps with `dependsOn`. ```yaml apiVersion: core.oam.dev/v1alpha1 kind: WorkflowRun metadata: name: dependency namespace: default spec: mode: steps: DAG workflowSpec: steps: - name: step1 type: apply-deployment dependsOn: - step2 - step3 properties: image: nginx - name: step2 type: apply-deployment properties: image: nginx - name: step3 type: apply-deployment properties: image: nginx ``` step1 will be executed after step2 and step3 are completed. ### Data Passing Data passing between steps can be done through `inputs` and `outputs`. For details, please refer to [Input and output between steps](../workflow/inputs-outputs.md#outputs). ```yaml apiVersion: core.oam.dev/v1alpha1 kind: WorkflowRun metadata: name: request-http namespace: default spec: workflowSpec: steps: - name: request type: request properties: url: https://api.github.com/repos/kubevela/workflow outputs: - name: stars valueFrom: | import "strconv" "Current star count: " + strconv.FormatInt(response["stargazers_count"], 10) - name: notification type: notification inputs: - from: stars parameterKey: slack.message.text properties: slack: url: value: ``` In this WorkflowRun, the first step will request the GitHub API to get the number of stars in the workflow repository as Output, and then use this Output as Input in the next step to send the star number as the message to Slack. ### Timeout You can specify `timeout` for a step to indicate the timeout for that step. `timeout` follows the `duration` format, e.g. `30s`, `1m`, etc. You can refer to Golang's [parseDuration](https://pkg.go.dev/time#ParseDuration). ```yaml apiVersion: core.oam.dev/v1alpha1 kind: WorkflowRun metadata: name: timeout namespace: default spec: workflowSpec: steps: - name: suspend type: suspend timeout: 3s ``` If the above WorkflowRun is not resumed within three seconds, the suspend step will fail with timeout. ### If Conditions You can use `if` in a step to determine whether to execute the step. #### No If specified If the step does not specify `if`, if the step before the step fails to execute, then the step will be skipped and will not be executed. #### if: always With `if: always` specified in a step, the step will be executed no matter what. #### Custom If You can also write your own judgment logic to determine whether the step should be executed. Note: The value in `if` will be executed as CUE code. WorkflowRun provides some built-in variables in `if`, these are: * `status`:`status` contains status information for all workflow steps. You can use `status..phase == "succeeded"` to determine the status of a step, or you can use the simplified `status..succeeded` to determine. * `inputs`:`inputs` contains all the inputs parameters of the step. You can use `inputs. == "value"` to get input for the step. * `context`: `context` contains all the context data of WorkflowRun. You can use `context. == "value"` to get the context of the WorkflowRun. :::tip Note that if your step name or inputs name is not a valid CUE variable name (eg: contains `-`, or starts with a number, etc.), you can refer to it as follows: `status["invalid-name"].failed`. ::: ```yaml apiVersion: core.oam.dev/v1alpha1 kind: WorkflowRun metadata: name: if-condition namespace: default spec: workflowSpec: steps: - name: suspend type: suspend timeout: 3s - name: my-step type: apply-deployment if: status.suspend.failed properties: image: nginx - name: my-step2 type: apply-deployment if: status.suspend.succecceed properties: image: busybox ``` In the above WorkflowRun, if the suspend step fails due to a timeout, then the my-step step will be executed, otherwise the my-step2 step will be executed. ### Custom Context Data Steps in WorkflowRun have some built-in context data, and you can also declare your custom context parameters in `context`. :::tip If your custom context data has the same name as a built-in context data, the built-in context parameter will be overridden by the custom parameter. ::: You can control the execution of WorkflowRun in different situations through the combination of conditional if and custom data. ``` apiVersion: core.oam.dev/v1alpha1 kind: WorkflowRun metadata: name: deploy-run namespace: default spec: context: env: test workflowRef: deploy-template --- apiVersion: core.oam.dev/v1alpha1 kind: Workflow metadata: name: deploy-template namespace: default steps: - name: apply type: apply-deployment if: context.env == "dev" properties: image: nginx - name: apply-test type: apply-deployment if: context.env == "test" properties: image: crccheck/hello-world ``` The above WorkflowRun will refer to the `deploy-template` Workflow as the execution template. If the `env` in the context is `dev`, then the apply step will be executed, otherwise the apply-test step will be executed. ### Built-in Context Data The built-in context data in WorkflowRun are as follows: | Context Variable | Description | Type | | :---------------------: | :--------------------------------------------: | :----: | | `context.name` | The name of the WorkflowRun | string | | `context.namespace` | The namespace of the WorkflowRun | string | | `context.stepName` | The name of the current step | string | | `context.stepSessionID` | The ID of the current step | string | | `context.spanID` | The trace ID of current step in this reconcile | string |