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Using Workflows to Schedule Jobs

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To increase the speed of your software development through faster feedback, shorter reruns, and more efficient use of resources, configure Workflows. This document describes the Workflows feature and provides example configurations in the following sections:

Overview

A workflow is a set of rules for defining a collection of jobs and their run order. Workflows support complex job orchestration using a simple set of configuration keys to help you resolve failures sooner.

With workflows, you can:

  • Run and troubleshoot jobs independently with real-time status feedback.
  • Schedule workflows for jobs that should only run periodically.
  • Fan-out to run multiple jobs in parallel for efficient version testing.
  • Fan-in to quickly deploy to multiple platforms.

For example, if only one job in a workflow fails, you will know it is failing in real-time. Instead of wasting time waiting for the entire build to fail and rerunning the entire job set, you can rerun just the failed job.

States

Workflows may appear with one of the following states:

  • RUNNING: Workflow is in progress
  • NOT RUN: Workflow was never started
  • CANCELLED: Workflow was cancelled before it finished
  • FAILING: A Job in the workflow has failed
  • FAILED: One or more jobs in the workflow failed
  • SUCCESS: All jobs in the workflow completed successfully
  • ON HOLD: A job in the workflow is waiting for approval
  • NEEDS SETUP: A workflow stanza is not included or is incorrect in the config.yml file for this project

Limitations

Projects that have Build Processing enabled may use the CircleCI API to trigger workflows. Projects that do not enable build processing will run as if the workflows did not exist when triggered by the API. Note: Builds without workflows require a build job.

Refer to the Workflows section of the FAQ for additional information and limitations.

Workflows Configuration Examples

For a full specification of the workflows key, see the Workflows section of the Configuring CircleCI document.

Note: Projects configured with Workflows often include multiple jobs that share syntax for Docker images, environment variables, or run steps. Refer the YAML Anchors/Aliases documentation for information about how to alias and reuse syntax to keep your .circleci/config.yml file small. See the Reuse YAML in the CircleCI Config blog post for a summary.

To run a set of parallel jobs, add a new workflows: section to the end of your existing .circleci/config.yml file with the version and a unique name for the workflow. The following sample .circleci/config.yml file shows the default workflow orchestration with two parallel jobs. It is defined by using the workflows: key named build_and_test and by nesting the jobs: key with a list of job names. The jobs have no dependencies defined, therefore they will run in parallel.

version: 2
jobs:
  build:
    docker:
      - image: circleci/<language>:<version TAG>
    steps:
      - checkout
      - run: <command>
  test:
    docker:
      - image: circleci/<language>:<version TAG>
    steps:
      - checkout
      - run: <command>
workflows:
  version: 2
  build_and_test:
    jobs:
      - build
      - test

See the Sample Parallel Workflow config for a full example.

Sequential Job Execution Example

The following example shows a workflow with four sequential jobs. The jobs run according to configured requirements, each job waiting to start until the required job finishes successfully as illustrated in the diagram.

Sequential Job Execution Workflow

The following config.yml snippet is an example of a workflow configured for sequential job execution:

workflows:
  version: 2
  build-test-and-deploy:
    jobs:
      - build
      - test1:
          requires:
            - build
      - test2:
          requires:
            - test1
      - deploy:
          requires:
            - test2

The dependencies are defined by setting the requires: key as shown. The deploy: job will not run until the build and test1 and test2 jobs complete successfully. A job must wait until all upstream jobs in the dependency graph have run. So, the deploy job waits for the test2 job, the test2 job waits for the test1 job and the test1 job waits for the build job.

See the Sample Sequential Workflow config for a full example.

Fan-Out/Fan-In Workflow Example

The illustrated example workflow runs a common build job, then fans-out to run a set of acceptance test jobs in parallel, and finally fans-in to run a common deploy job.

Fan-out and Fan-in Workflow

The following config.yml snippet is an example of a workflow configured for fan-out/fan-in job execution:

workflows:
  version: 2
  build_accept_deploy:
    jobs:
      - build
      - acceptance_test_1:
          requires:
            - build
      - acceptance_test_2:
          requires:
            - build
      - acceptance_test_3:
          requires:
            - build
      - acceptance_test_4:
          requires:
            - build
      - deploy:
          requires:
            - acceptance_test_1
            - acceptance_test_2
            - acceptance_test_3
            - acceptance_test_4

In this example, as soon as the build job finishes successfully, all four acceptance test jobs start. The deploy job must wait for all four acceptance test jobs to complete successfully before it starts.

See the Sample Fan-in/Fan-out Workflow config for a full example.

Holding a Workflow for a Manual Approval

Workflows can be configured to wait for manual approval of a job before continuing to the next job. Anyone who has push access to the repository can click the Approval button to continue the workflow. To do this, add a job to the jobs list with the key type: approval. Let’s look at a commented config example.

# ...
# << Your config for the build, test1, test2, and deploy jobs >>
# ...

workflows:
  version: 2
  build-test-and-approval-deploy:
    jobs:
      - build  # your custom job from your config, that builds your code
      - test1: # your custom job; runs test suite 1
          requires: # test1 will not run until the `build` job is completed.
            - build
      - test2: # another custom job; runs test suite 2,
          requires: # test2 is dependent on the succes of job `test1`
            - test1
      - hold: # <<< A job that will require manual approval in the CircleCI web application.
          type: approval # <<< This key-value pair will set your workflow to a status of "On Hold"
          requires: # We only run the "hold" job when test2 has succeeded
           - test2
      # On approval of the `hold` job, any successive job that requires the `hold` job will run. 
      # In this case, a user is manually triggering the deploy job.
      - deploy:
          requires:
            - hold

The outcome of the above example is that the deploy: job will not run until you click the hold job in the Workflows page of the CircleCI app and then click Approve. In this example the purpose of the hold job is to wait for approval to begin deployment.

Some things to keep in mind when using manual approval in a workflow:

  • approval is a special job type that is only available to jobs under the workflow key
  • The hold job must be a unique name not used by any other job.
    • that is, your custom configured jobs, such as build or test1 in the example above wouldn’t be given a type: approval key.
  • The name of the job to hold is arbitrary - it could be wait or pause, for example, as long as the job has a type: approval key in it.
  • All jobs that are to run after a manually approved job must require: the name of that job. Refer to the deploy: job in the above example.
  • Jobs run in the order defined until the workflow processes a job with the type: approval key followed by a job on which it depends.

The following screenshots show a workflow on hold waiting for approval of the request-testing job:

Approved Jobs in On Hold Workflow

Following is a screenshot of the Approval dialog box that appears when you click the request-testing job:

Approval Dialog in On Hold Workflow

Scheduling a Workflow

It can be inefficient and expensive to run a workflow for every commit for every branch. Instead, you can schedule a workflow to run at a certain time for specific branches. This will disable commits from triggering jobs on those branches.

Consider running workflows that are resource-intensive or that generate reports on a schedule rather than on every commit by adding a triggers key to the configuration. The triggers key is only added under your workflows key. This feature enables you to schedule a workflow run by using cron syntax to represent Coordinated Universal Time (UTC) for specified branches.

Nightly Example

By default, a workflow is triggered on every git push. To trigger a workflow on a schedule, add the triggers key to the workflow and specify a schedule.

In the example below, the nightly workflow is configured to run every day at 12:00am UTC. The cron key is specified using POSIX crontab syntax, see the crontab man page for cron syntax basics. The workflow will be run on the master and beta branches.

workflows:
  version: 2
  commit:
    jobs:
      - test
      - deploy
  nightly:
    triggers:
      - schedule:
          cron: "0 0 * * *"
          filters:
            branches:
              only:
                - master
                - beta
    jobs:
      - coverage

In the above example, the commit workflow has no triggers key and will run on every git push. The nightly workflow has a triggers key and will run on the specified schedule.

Specifying a Valid Schedule

A valid schedule requires a cron key and a filters key.

The value of the cron key must be a valid crontab entry.

Note: Cron step syntax (for example, */1, */20) is not supported.

The value of the filters key must be a map that defines rules for execution on specific branches.

For more details, see the branches section of the Configuring CircleCI document.

For a full configuration example, see the Sample Scheduled Workflows configuration.

Using Contexts and Filtering in Your Workflows

The following sections provide example for using Contexts and filters to manage job execution.

Using Job Contexts to Share Environment Variables

The following example shows a workflow with four sequential jobs that use a context to share environment variables. See the Contexts document for detailed instructions on this setting in the application.

The following config.yml snippet is an example of a sequential job workflow configured to use the resources defined in the org-global context:

workflows:
  version: 2
  build-test-and-deploy:
    jobs:
      - build
      - test1:
          requires:
            - build
          context: org-global  
      - test2:
          requires:
            - test1
          context: org-global  
      - deploy:
          requires:
            - test2

The environment variables are defined by setting the context key as shown to the default name org-global. The test1 and test2 jobs in this workflows example will use the same shared environment variables when initiated by a user who is part of the organization. By default, all projects in an organization have access to contexts set for that organization.

Branch-Level Job Execution

The following example shows a workflow configured with jobs on three branches: Dev, Stage, and Pre-Prod. Workflows will ignore branches keys nested under jobs configuration, so if you use job-level branching and later add workflows, you must remove the branching at the job level and instead declare it in the workflows section of your config.yml, as follows:

Branch-Level Job Execution

The following config.yml snippet is an example of a workflow configured for branch-level job execution:

workflows:
  version: 2
  dev_stage_pre-prod:
    jobs:
      - test_dev:
          filters:  # using regex filters requires the entire branch to match
            branches:
              only:  # only branches matching the below regex filters will run
                - dev
                - /user-.*/
      - test_stage:
          filters:
            branches:
              only: stage
      - test_pre-prod:
          filters:
            branches:
              only: /pre-prod(?:-.+)?$/

For more information on regular expressions, see the Using Regular Expressions to Filter Tags And Branches section below. For a full example of workflows, see the configuration file for the Sample Sequential Workflow With Branching project.

Executing Workflows for a Git Tag

CircleCI does not run workflows for tags unless you explicitly specify tag filters. Additionally, if a job requires any other jobs (directly or indirectly), you must use regular expressions to specify tag filters for those jobs. Both lightweight and annotated tags are supported.

In the example below, two workflows are defined:

  • untagged-build runs the build job for all branches.
  • tagged-build runs build for all branches and all tags starting with v.
workflows:
  version: 2
  untagged-build:
    jobs:
      - build
  tagged-build:
    jobs:
      - build:
          filters:
            tags:
              only: /^v.*/

In the example below, two jobs are defined within the build-n-deploy workflow:

  • The build job runs for all branches and all tags.
  • The deploy job runs for no branches and only for tags starting with ‘v’.
workflows:
  version: 2
  build-n-deploy:
    jobs:
      - build:
          filters:  # required since `deploy` has tag filters AND requires `build`
            tags:
              only: /.*/
      - deploy:
          requires:
            - build
          filters:
            tags:
              only: /^v.*/
            branches:
              ignore: /.*/

In the example below, three jobs are defined with the build-test-deploy workflow:

  • The build job runs for all branches and only tags starting with ‘config-test’.
  • The test job runs for all branches and only tags starting with ‘config-test’.
  • The deploy job runs for no branches and only tags starting with ‘config-test’.
workflows:
  version: 2
  build-test-deploy:
    jobs:
      - build:
          filters:  # required since `test` has tag filters AND requires `build`
            tags:
              only: /^config-test.*/
      - test:
          requires:
            - build
          filters:  # required since `deploy` has tag filters AND requires `test`
            tags:
              only: /^config-test.*/
      - deploy:
          requires:
            - test
          filters:
            tags:
              only: /^config-test.*/
            branches:
              ignore: /.*/

Note: Webhook payloads from GitHub are capped at 5MB and for some events a maximum of 3 tags. If you push several tags at once, CircleCI may not receive all of them.

Using Regular Expressions to Filter Tags and Branches

CircleCI branch and tag filters support the Java variant of regex pattern matching. When writing filters, CircleCI matches exact regular expressions.

For example, only: /^config-test/ only matches the config-test tag. To match all tags starting with config-test, use only: /^config-test.*/ instead. Using tags for semantic versioning is a common use case. To match patch versions 3-7 of a 2.1 release, you could write /^version-2\.1\.[3-7]/.

For full details on pattern-matching rules, see the java.util.regex documentation.

Using Workspaces to Share Data Among Jobs

Each workflow has an associated workspace which can be used to transfer files to downstream jobs as the workflow progresses. The workspace is an additive-only store of data. Jobs can persist data to the workspace. This configuration archives the data and creates a new layer in an off-container store. Downstream jobs can attach the workspace to their container filesystem. Attaching the workspace downloads and unpacks each layer based on the ordering of the upstream jobs in the workflow graph.

workspaces data flow

Use workspaces to pass along data that is unique to this run and which is needed for downstream jobs. Workflows that include jobs running on multiple branches may require data to be shared using workspaces. Workspaces are also useful for projects in which compiled data are used by test containers.

For example, Scala projects typically require lots of CPU for compilation in the build job. In contrast, the Scala test jobs are not CPU-intensive and may be parallelised across containers well. Using a larger container for the build job and saving the compiled data into the workspace enables the test containers to use the compiled Scala from the build job.

A second example is a project with a build job that builds a jar and saves it to a workspace. The build job fans-out into the integration-test, unit-test, and code-coverage to run those tests in parallel using the jar.

To persist data from a job and make it available to other jobs, configure the job to use the persist_to_workspace key. Files and directories named in the paths: property of persist_to_workspace will be uploaded to the workflow’s temporary workspace relative to the directory specified with the root key. The files and directories are then uploaded and made available for subsequent jobs (and re-runs of the workflow) to use.

Configure a job to get saved data by configuring the attach_workspace key. The following config.yml file defines two jobs where the downstream job uses the artifact of the flow job. The workflow configuration is sequential, so that downstream requires flow to finish before it can start.

# Note that the following stanza uses CircleCI 2.1 to make use of a Reusable Executor
# This allows defining a docker image to reuse across jobs.
# visit https://circleci.com/docs/2.0/reusing-config/#authoring-reusable-executors to learn more.

version: 2.1

executors:
  my-executor:
    docker:
      - image: buildpack-deps:jessie
    working_directory: /tmp

jobs:
  flow:
    executor: my-executor
    steps:
      - run: mkdir -p workspace
      - run: echo "Hello, world!" > workspace/echo-output
      
      # Persist the specified paths (workspace/echo-output) into the workspace for use in downstream job. 
      - persist_to_workspace:
          # Must be an absolute path, or relative path from working_directory. This is a directory on the container which is 
          # taken to be the root directory of the workspace.
          root: workspace
          # Must be relative path from root
          paths:
            - echo-output

  downstream:
    executor: my-executor
    steps:
      - attach_workspace:
          # Must be absolute path or relative path from working_directory
          at: /tmp/workspace

      - run: |
          if [[ `cat /tmp/workspace/echo-output` == "Hello, world!" ]]; then
            echo "It worked!";
          else
            echo "Nope!"; exit 1
          fi

workflows:
  version: 2.1

  btd:
    jobs:
      - flow
      - downstream:
          requires:
            - flow

For a live example of using workspaces to pass data between build and deploy jobs, see the config.yml that is configured to build the CircleCI documentation. For additional conceptual information on using workspaces, caching, and artifacts, refer to the Persisting Data in Workflows: When to Use Caching, Artifacts, and Workspaces blog post.

Rerunning a Workflow’s Failed Jobs

When you use workflows, you increase your ability to rapidly respond to failures. To rerun only a workflow’s failed jobs, click the Workflows icon in the app and select a workflow to see the status of each job, then click the Rerun button and select Rerun from failed.

CircleCI Workflows Page

Troubleshooting

This section describes common problems and solutions for Workflows.

Workflows Not Starting

When creating or modifying workflow configuration, if you don’t see new jobs, you may have a configuration error in config.yml.

Oftentimes if you do not see your workflows triggering, a configuration error is preventing the workflow from starting. As a result, the workflow does not start any jobs.

When setting up workflows, you currently have to check your Workflows page of the CircleCI app (not the Job page) to view the configuration errors.

A project’s Job page URL looks like this:

https://circleci.com/:VCS/:ORG/:PROJECT

A Workflow page URL looks like this:

https://circleci.com/:VCS/:ORG/workflows/:PROJECT

Look for Workflows that have a yellow tag and “Needs Setup” for the text.

Invalid workflow configuration example

Workflows Waiting for Status in GitHub

If you have implemented Workflows on a branch in your GitHub repository, but the status check never completes, there may be status settings in GitHub that you need to deselect. For example, if you choose to protect your branches, you may need to deselect the ci/circleci status key as this check refers to the default CircleCI 1.0 check, as follows:

Uncheck GitHub Status Keys

Having the ci/circleci checkbox enabled will prevent the status from showing as completed in GitHub when using a workflow because CircleCI posts statuses to Github with a key that includes the job by name.

Go to Settings > Branches in GitHub and click the Edit button on the protected branch to deselect the settings, for example https://github.com/your-org/project/settings/branches.

See Also

  • For procedural instructions on how to add Workflows your configuration as you are migrating from a 1.0 circle.yml file to a 2.0 .circleci/config.yml file, see the Steps to Configure Workflows section of the Migrating from 1.0 to 2.0 document.

  • For frequently asked questions and answers about Workflows, see the Workflows section of the FAQ.

  • For demonstration apps configured with Workflows, see the CircleCI Demo Workflows on GitHub.

Video: Configure Multiple Jobs with Workflows

Video: How to Schedule Your Builds to Test and Deploy Automatically