Pipeline Example: Docker Build and Push

JFrog Pipelines Documentation

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JFrog Pipelines
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User Guide
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Paligo

This pipeline demonstrates the definition of a pipeline that builds a single Docker Image and pushes it to Artifactory, and then publishes BuildInfo. An example Pipelines DSL is used to show how to use integrations, resources, and steps to construct a simple, automated workflow.

This pipeline demonstrates the following:

A successful run of the pipeline in this quickstart looks like this:

pipeline_dbp_success_1a.png

Tutorial Video

Before You Begin

Before trying this quickstart, ensure that you have:

  • A GitHub account. This is required for forking the example repository.

  • A JFrog Platform account, or self-hosted JFrog Pipelines.

  • A user account in Artifactory with deploy permissions to at least one binary repository.

  • Create a local Docker repository to set up Artifactory as a Docker Registry.Docker Registry

  • At least one node pool. This is the set of nodes that all pipeline steps will execute in. For more information, see Managing Pipelines Node Pools.

Run the Pipeline

For a detailed overview of the Docker and Build Push YAML example, see Docker and Build Push Example: pipelines.yml.

Perform the steps below to build and push your Docker image:

  1. Fork the Repository

    The Pipelines DSL for this example is available in the jfrog-pipelines-docker-sample repository in the JFrog GitHub account.

    The DSL file is a yaml file that contains the pipeline definitions. The example uses a single YAML file, pipelines.yml. This file contains the declarations for all resources and workflow steps. For a full breakup of all the resources, pipelines and steps used in the yml file, see the pipelines.ymlsection below.

    Fork this repository to your account or organization. This is important since you need admin access to repositories that are used as Pipeline Sources or GitRepo resources, in order to add webhooks to these repositories and listen for change events.

  2. Sign in to Artifactory

    Sign in to JFrog Platform with your Artifactory credentials.

  3. Add Integrations

    1. Go to Administration | Pipelines | Integrations to add two integrations:

    2. Write down the names of both GitHub and Artifactory integrations as these are required for the next step. Ensure that the names are unique and easy to remember.

  4. Update pipelines.yml file

    The pipelines configuration is available in the pipelines.yml file. Edit this file in your fork of the Git repo and replace the following:

    Tag

    Description

    Example

    gitProvider

    Provide the name of the Github integration you added in the previous step.

    gitProvider: my_github

    path

    Provide the path to your fork of this repository.

    path: myuser/repo-name

    registry

    Provide the the name of the Artifactory integration you added in the previous step.

    registry: art

    imageName

    Provide your Docker image path and name.

    docker.artprod.mycompany.com /docker_local/dbp

    Where, docker.artprod.mycompany.com/docker_local is the image path and dbp is the image name.

    sourceArtifactory

    Provide your Artifactory integration.

    sourceArtifactory: art

    Note

    All pipeline definitions are global across JFrog Pipelines within a Project. The names of your pipelines and resources need to be unique within the Project in JFrog Pipelines.

  5. Add Pipeline Sources

    The Pipeline Source represents the Git repo where our Pipelines definition files are stored. A pipeline source connects to the repository through an integration, which we added in the previous step.

    Follow instructions to add a Pipeline Source and point it to the pipelines.yml in your fork of the repo. This automatically adds your configuration to the platform and a pipeline is created based on your YAML. The pipelines.yml file is parsed and resources, steps, and pipelines are added as configured.

    After your pipeline source syncs successfully, navigate to Pipelines | My Pipelines in the left navbar to view the newly added pipeline. In this example,pipeline_dbp is the name of our pipeline.

    pipeline_dbp_1.png

    Click the name of the pipeline. This renders a real-time, interactive, diagram of the pipeline and the results of its most current run.

  6. Execute the Pipeline

    You can trigger the pipeline by committing a change to your Git repository, or by manually triggering it through the UI. The steps in the pipeline execute in sequence. Multiple steps can execute in parallel if the node pool has multiple build nodes available.

    docker_build_trigger_1.png

    Once the pipeline has completed, a new run is listed.

    pipeline_dbp_success_1.png