Codefresh YAML

How to define Codefresh pipelines in a declarative manner

Codefresh offers its own built-in format for creating pipelines. The pipeline specification is based on the YAML syntax allowing you to describe your pipelines in a completely declarative manner.

Using Codefresh yaml is the recommended way to create pipelines.

Simple example for codefresh.yml

Here is a very minimal example:


version: '1.0'
    type: build
    description: Building the image...
    image-name: myuser/myservice
    tag: develop # ${{CF_BRANCH}}

    image: node:5
    working_directory: ${{main_clone}}
    description: Performing unit tests...
      - npm install gulp -g 
      - npm install
      - gulp unit_test

It contains two steps, one named build_image that creates a docker image, and another one called perform_tests that runs unit test with gulp.

If you want to know more about how steps work in Codefresh make sure to read the introduction to Pipelines first, before moving on.

Basic skeleton of a codefresh.yml file.

You can customize your build environment (pipeline) by using the Codefresh YAML file, codefresh.yml. Codefresh uses the build specifications in the codefresh.yml file to execute your build. The codefresh.yml can be basic, or include intricate build specifications.

A YAML file is comprised of a series of steps that are executed in the order in which they are specified.


version: '1.0'


You must define a step type for each step. Each step uses Docker images and containers as facilitators for execution. For example, the Freestyle step spins up a container and executes the specified shell commands from the YAML file.

The step names should be unique within the same pipeline. This mainly affects the visualization of the pipeline when it runs.

Each step produces a resource, which you can reference in other steps, and are executed in real-time. For example, a Freestyle step can reference an image that was produced by a Build step. This allows you to chain steps together, and create highly-customized builds.


Steps chaining and referencing is possible due to implementation of variables in yml file - read more on relevant section

Step Type Description
Freestyle Executes one or more shell commands in a container similar to docker run.
Build Builds a Docker image like docker build
Push Pushes a Docker image to a Docker registry similar to docker tag and docker push
Git Clone Overrides the default git clone behavior
Composition Starts a Docker Composition like docker-compose. Discarded once pipelines finishes.
Launch Composition Starts a long term Docker composition that stays up after the end of the pipeline
Deploy Deploys to Kubernetes clusters
Approval Pauses a pipeline and waits for human intervention

To build your pipeline using a codefresh.yml file, in the General Settings section, toggle the Use YML build option to the ON position.

pipeline definition options

Switching between basic steps and YAML syntax

Yaml validation

If you are editing Codefresh yaml within the Codefresh GUI, the editor will automatically highlight errors as they happen.

This allows you to make quick edits (and possibly run some builds) straight from the GUI. Once you are happy with your pipeline you should commit it to your repository as codefresh.yml (pipeline as code).

Graphical Inline Yaml Editor

Graphical Inline Yaml Editor

You can also validate the pipeline yaml outside of the UI by using the Codefresh CLI. The CLI has a validate parameter that can check one or more files for syntax errors

$codefresh validate codefresh.yml
Yaml not valid:
  - "invalid-property" is not allowed

For more information on where the YAML file can be stored see the creating pipelines page.

Execution flow

By default Codefresh will execute all steps in the yaml file and instantly fail the build, if any step presents an error. To change this behavior add the fail_fast:false property in any step that you wish to be ignored in case of errors.

For example, if you have a freestyle step that runs integration tests, and you don’t want the whole pipeline to fail if any of the tests fail, add the fail_fast line to that step:

    image: node:9
    description: Running integration tests
    fail_fast: false
      - gulp integration_test

Now the pipeline will continue to run even if the step perform_tests fails.

Notice also that by default Codefresh pipelines run in sequential mode. All steps will be executed one after the other and in the same order as included in the codefresh.yml file.

If you wish to use parallel steps in your pipelines, see the parallel steps page.

Retrying a step

Sometimes you want to retry a step that has a problem. Network hiccups, transient failures and flaky test environments are common problems that prevent pipelines from working in a predictable manner.

Codefresh allows you to retry any of your steps with the built-in syntax:


      maxAttempts: 5
      delay: 5
      exponentialFactor: 2

The retry: block has the following parameters:

  • maxAttempts defines how many times this step will run again if there are execution errors. Default is 1. Max is 10.
  • delay is the number of seconds to wait before each attempt. Default is 5 seconds. Max is 60 seconds.
  • exponentialFactor defines how many times the delay should be multiplied by itself after each attempt. default is 1. Max is 5.

All parameters are optional. The exponentialFactor works like this:

  • exponentialFactor=1, delay=5 => each time wait 5 seconds before trying again, no matter the number of attempts
  • exponentialFactor=2, delay=5 => first retry will have a delay of 25 seconds, third will have 125 and so on

Here is a full example:


version: '1.0'
    title: Building Docker Image
    type: build
    image_name: my-own-app
      maxAttempts: 2
    title: Running Unit tests
    image: ${{MyAppDockerImage}}
    - ./
      maxAttempts: 3
      delay: 5
    type: push
    title: Pushing To Registry
    candidate: ${{MyAppDockerImage}}
    tag: '${{CF_BRANCH}}'
      maxAttempts: 3
      delay: 3
      exponentialFactor: 2

Notice that Codefresh also provides the following variables that allow you change your script/applications according to the retry attempts:

  • CF_CURRENT_ATTEMPT contains the number of current retry attempt
  • CF_MAX_ATTEMPTS contains all the number of total attempts defined

The retry mechanism is available for all kinds of steps.

Using YAML anchors to avoid repetition

Codefresh also supports yaml anchors, references and extends. These allow you to keep your pipeline DRY.

For example, let’s say that you have two freestyle steps:

  1. The first one fills a MySQL server with data
  2. The second one runs integration tests that use the MySQL server

Here is the respective pipeline:


version: '1.0'
    title: Loading Data
    image: alpine
      - printenv
      - echo "Loading DB"
    environment: &my_common_envs
      - MYSQL_HOST=mysql
      - MYSQL_USER=user
      - MYSQL_PASS=password
      - MYSQL_PORT=3351  
    title: Integration tests
    image: alpine
      - printenv
      - echo "Running tests"
    environment: *my_common_envs  # Same MYSQL_HOST, MYSQL_USER etc.

Instead of repeating the same environment variables in both steps, we can create them once and then just reference them in the second step with the * character.

You also extend steps like below:


version: '1.0'
  deploy_to_k8_staging: &my_basic_deployment
    title: deploying to cluster
    type: deploy
    kind: kubernetes 
    cluster:  myStagingCluster
    namespace: sales
    service: my-python-app
    <<: *my_basic_deployment
    cluster:  myProdCluster # only cluster differs, everything else is the same

Here we deploy to two kubernetes clusters. The first step defines the staging deployment. For the second step, we extend the first one and only change the name of the cluster to point to production. Everything else (i.e. namespace and service ) are exactly the same.