instruction: Explain how to configuration reference :: circleci documentation
output: Configuration reference 18 hours ago · 109 min read Cloud Server v4+ Contribute This document is a reference for the CircleCI 2.x configuration keys that are used in the .circleci/config.yml file. You can see a complete config.yml in our full example . version The version field is intended to be used in order to issue warnings for deprecation or breaking changes. Key Required Type Description version Y String 2 , 2.0 , or 2.1 See the Reusable configuration page for an overview of 2.1 keys available to simplify your .circleci/config.yml file, reuse, and parameterized jobs. Example: version: 2.1 setup The setup field enables you to conditionally trigger configurations from outside the primary .circleci parent directory, update pipeline parameters, or generate customized configurations. Key Required Type Description setup N Boolean Designates the config.yaml for use of CircleCI’s dynamic configuration feature. Example: version: 2.1 setup: true orbs The orbs key is supported in version: 2.1 configuration Use the orbs key to reference or define reusable configuration blocks (orbs) for use in your configuration. Key Required Type Description orbs N Map A map of user-selected names to either: orb references (strings) or orb definitions (maps). Orb definitions must be the orb-relevant subset of 2.1 config. See the Creating Orbs documentation for details. executors N Map A map of strings to executor definitions. See the executors section below. commands N Map A map of command names to command definitions. See the commands section below. The following example uses the node orb that exists in the certified circleci namespace. Refer to the Node orb page in the Orb Registry for more examples and information. Example: version: 2.1 orbs: node: circleci/node@x.y jobs: install-node-example: docker: - image: cimg/base:stable steps: - checkout - node/install: install-yarn: true node-version: '16.13' - run: node --version workflows: test_my_app: jobs: - install-node-example Documentation is available for orbs in the following sections: Using Orbs Authoring Orbs . Public orbs are listed in the Orb Registry . commands The commands key is supported in version: 2.1 configuration A command defines a sequence of steps as a map to be executed in a job, enabling you to reuse a single command definition across multiple jobs. For more information see the Reusable Config Reference Guide . Key Required Type Description steps Y Sequence A sequence of steps run inside the calling job of the command. parameters N Map A map of parameter keys. See the Parameter Syntax section of the Reusing Config document for details. description N String A string that describes the purpose of the command. Example: version: 2.1 commands: sayhello: description: "A very simple command for demonstration purposes" parameters: to: type: string default: "Hello World" steps: - run: echo << parameters.to >> parameters The pipeline parameters key is supported in version: 2.1 configuration Use the parameters key at the top level of your config to declare pipeline parameters for use in the configuration. See Pipeline Values and Parameters for usage details. Key Required Type Description parameters N Map A map of parameter keys. Supports string , boolean , integer and enum types. See Parameter Syntax for details. Example: This example declares a pipeline parameter named image-tag with a type of string and a default value of current . version: 2.1 parameters: image-tag: type: string default: "current" Once you have declared a pipeline parameter, you can pass a pipelines parameter value when triggering a pipeline via the API or from the CircleCI web app. ''' executors The executors key is supported in version: 2.1 configuration Executors define the execution environment in which the steps of a job will be run, allowing you to reuse a single executor definition across multiple jobs. Key Required Type Description docker Y (1) List Options for Docker executor resource_class N String Amount of CPU and RAM allocated to each container in a job. machine Y (1) Map Options for machine executor macos Y (1) Map Options for macOS executor windows Y (1) Map Windows executor currently working with orbs. Check out the orb . shell N String Shell to use for execution command in all steps. Can be overridden by shell in each step (default: See Default Shell Options ) working_directory N String In which directory to run the steps. Will be interpreted as an absolute path. environment N Map A map of environment variable names and values. (1) One executor type should be specified per job. If more than one is set you will receive an error. Example: version: 2.1 executors: my-executor: docker: - image: cimg/ruby:3.0.3-browsers jobs: my-job: executor: my-executor steps: - run: echo "Hello executor!" See the Using Parameters in Executors section of the Reusing config page for examples of parameterized executors. jobs A Workflow is comprised of one or more uniquely named jobs. Jobs are specified in the jobs map, see Sample config.yml for two examples of a job map. The name of the job is the key in the map, and the value is a map describing the job. Jobs have a maximum runtime based on pricing plan, as follows: 1 hour (Free) 3 hours (Performance) 5 hours (Scale) If your jobs are timing out, consider the following: A larger resource_class . Using parallelism . Run some of your jobs concurrently using workflows . You can upgrade your pricing plan. Example: version: 2.1 jobs: my-job: docker: - image: cimg/base:2024.12 resource_class: xlarge steps: ... // other config < job_name > Each job consists of the job’s name as a key and a map as a value. A name should be case insensitive unique within a current jobs list. The value map has the following attributes: Key Required Type Description type N String Job type, can be build , release , no-op , or approval . If not specified, defaults to build . docker Y (1) List Options for the Docker executor machine Y (1) Map Options for the machine executor macos Y (1) Map Options for the macOS executor shell N String Shell to use for execution command in all steps. Can be overridden by shell in each step (default: See Default Shell Options ) parameters N Map Parameters for making a job explicitly configurable in a workflow . steps Y List A list of steps to be performed working_directory N String In which directory to run the steps. Will be interpreted as an absolute path. Default: ~/project (where project is a literal string, not the name of your specific project). Processes run during the job can use the $CIRCLE_WORKING_DIRECTORY environment variable to refer to this directory. Note: Paths written in your YAML configuration file will not be expanded; if your store_test_results.path is $CIRCLE_WORKING_DIRECTORY/tests , then CircleCI will attempt to store the test subdirectory of the directory literally named $CIRCLE_WORKING_DIRECTORY , dollar sign $ and all. working_directory will be created automatically if it doesn’t exist. parallelism N Integer Number of parallel instances of this job to run (default: 1) environment N Map A map of environment variable names and values. branches N Map This key is deprecated. Use workflows filtering to control which jobs run for which branches. resource_class N String Amount of CPU and RAM allocated to each container in a job. retention N Map Configure job retention periods for cache data (1-15 days, for example, "1d", "7d", "15d"). Reduces organization-level retention by automatically removing cache data after the specified period. (1) One executor type should be specified per job. If more than one is set you will receive an error. Example: In this example the job name is my-job . version: 2.1 jobs: my-job: type Configure a job type. Options are release , approval , no-op , build (default). If a type is not specified, the job defaults to a build type. Example of a job with a build type. build is the default type and does not need to be configured: jobs: my-job: docker: - image: cimg/base:2024.12 resource_class: xlarge steps: ... // other config Jobs with the release type are used to connect your pipeline configuration to a deployment in the CircleCI deploys UI. For full details, see the Deploys overview page. Example of a job with a release type: jobs: release-my-service: type: release plan_name: <my-service-release> The no-op type is used to configure a job that performs no actions and consumes no credits. no-op is commonly used to organise the order of operations within a workflow and make it easier to maintain. Only the type is required for a no-op type job, no further job configuration is required. For some examples of using no-op jobs, see the Orchestration cookbook Example of a job with a no-op type: jobs: my-no-op-job: type: no-op The approval type is used to configure a manual approval step. No job configuration is required or allowed for an approval type job. The approval type is most commonly configured within a workflow rather than under the top-level jobs key. Only approval type jobs can have their type configured under workflows . See type under workflows section for full details. Example of a job with an approval type, configured under workflows : workflows: my-workflow: jobs: - build - test: requires: - build - hold: type: approval requires: - test - deploy: requires: - hold environment A map of environment variable names and values. For more information on defining and using environment variables, and the order of precedence governing the various ways they can be set, see the Environment variables page. Example to show setting an environment variable named FOO with a value of bar for use in a job. version: 2.1 jobs: build: docker: - image: cimg/base:2022.04-20.04 environment: FOO: bar retention Configure job retention periods to control how long job data is kept. Job retention specifically controls cache retention at the job level. This setting can be configured from 1 day to 15 days using string values (for example, "1d", "7d", "15d"). Job retention reduces the organization-level retention from the default by automatically removing cache data after the specified period. For more information on cache retention, see the Persisting data overview page. Example: version: 2.1 jobs: test: docker: - image: cimg/node:18.0 retention: caches: 7d steps: - checkout - run: npm install - run: npm test parallelism This feature is used to optimize test steps. If parallelism is set to N > 1, then N independent executors will be set up and each will run the steps of that job in parallel. You can use the CircleCI CLI to split your test suite across parallel containers so the job completes in a shorter time. Read more about splitting tests across parallel execution environments on the Parallelism and test splitting page. Refer to the Use the CircleCI CLI to split tests how-to guide. Follow the Test splitting tutorial . Example: jobs: build: docker: - image: cimg/base:2024.12 environment: FOO: bar parallelism: 3 resource_class: large working_directory: ~/my-app steps: - run: go list ./... | circleci tests run --command "xargs gotestsum --junitfile junit.xml --format testname --" --split-by=timings --timings-type=name parameters Job-level parameters can be used when calling a job in a workflow . Reserved parameter-names: name requires context type filters matrix See Parameter Syntax for definition details. Example to show using a job parameter to set the parallelism for a job when a workflow is run. version: 2.1 jobs: build: parameters: my-parameter: type: integer default: 1 parallelism: << parameters.p >> docker: - image: cimg/base:2023.11 steps: - checkout workflows: workflow: jobs: - build: my-parameter: 2 Executor docker / machine / macos CircleCI offers several execution environments in which to run your jobs. To specify an execution environment choose an executor , then specify and image and a resource class. An executor defines the underlying technology, environment, and operating system in which to run a job. Set up your jobs to run using the docker (Linux), machine (LinuxVM, Windows, GPU, Arm), or macos executor, then specify an image with the tools and packages you need, and a resource class. Learn more about execution environments and executors in the Introduction to Execution Environments . docker Configure a job to use the Docker execution environment using the docker key which takes a list of maps: Key Required Type Description image Y String The name of a custom Docker image to use. The first image listed under a job defines the job’s own primary container image where all steps will run. name N String name defines the hostname for the container (the default is localhost ), which is used for reaching secondary (service) containers. By default, all services are exposed directly on localhost . This field is useful if you would rather have a different hostname instead of localhost , for example, if you are starting multiple versions of the same service. entrypoint N String or List The command used as executable when launching the container. entrypoint overrides the image’s ENTRYPOINT . command N String or List The command used as PID 1 (or arguments for entrypoint) when launching the container. command overrides the image’s COMMAND . It will be used as arguments to the image ENTRYPOINT if it has one, or as the executable if the image has no ENTRYPOINT . user N String Which user to run commands as within the Docker container environment N Map A map of environment variable names and values. The environment settings apply to the entrypoint/command run by the Docker container, not the job steps. auth N Map Authentication for registries using standard docker login credentials aws_auth N Map Authentication for AWS Elastic Container Registry (ECR) For a primary container , (the first container in the list) if neither command nor entrypoint is specified in the configuration, then any ENTRYPOINT and COMMAND in the image are ignored. The primary container is typically only used for running the steps and not for its ENTRYPOINT , and an ENTRYPOINT may consume significant resources or exit prematurely. A custom image may disable this behavior and force the ENTRYPOINT to run. You can specify image versions using tags or digest. You can use any public images from any public Docker registry (defaults to Docker Hub). Learn more about specifying images on the Using the Docker Execution Environment page. Example: version: 2.1 jobs: hello-job: docker: - image: cimg/node:17.2.0 # the primary container, where your job's commands are run steps: - checkout # check out the code in the project directory - run: echo "hello world" # run the `echo` command workflows: my-workflow: jobs: - hello-job Docker registry authentication Some registries, Docker Hub, for example, may rate limit anonymous Docker pulls. We recommend that you authenticate to pull private and public images. The username and password can be specified in the auth field. See Using Docker Authenticated Pulls for details. Example: jobs: build: docker: - image: buildpack-deps:trusty # primary container auth: username: mydockerhub-user password: $DOCKERHUB_PASSWORD # context / project UI env-var reference environment: ENV: CI - image: mongo:2.6.8 auth: username: mydockerhub-user password: $DOCKERHUB_PASSWORD # context / project UI env-var reference command: [--smallfiles] - image: postgres:14.2 auth: username: mydockerhub-user password: $DOCKERHUB_PASSWORD # context / project UI env-var reference environment: POSTGRES_USER: user - image: redis@sha256:54057dd7e125ca41afe526a877e8bd35ec2cdd33b9217e022ed37bdcf7d09673 auth: username: mydockerhub-user password: $DOCKERHUB_PASSWORD # context / project UI env-var reference - image: acme-private/private-image:321 auth: username: mydockerhub-user password: $DOCKERHUB_PASSWORD # context / project UI env-var reference AWS authentication Using an image hosted on AWS ECR requires authentication using AWS credentials. The two configuration options are described in the following sections. Use OIDC Authenticate using OpenID Connect (OIDC) using the oidc_role_arn field, as follows: Example: jobs: job_name: docker: - image: <your-image-arn> aws_auth: oidc_role_arn: <your-iam-role-arn> For steps to get set up with OIDC to pull images from AWS ECR, see the Pull and image from AWS ECR with OIDC page. Use environment variables By default, CircleCI uses the AWS credentials you provide by setting the AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY project environment variables. It is also possible to set the credentials by using the aws_auth field as in the following example: Example: jobs: build: docker: - image: account-id.dkr.ecr.us-east-1.amazonaws.com/org/repo:0.1 aws_auth: aws_access_key_id: AKIAQWERVA # can specify string literal values aws_secret_access_key: $ECR_AWS_SECRET_ACCESS_KEY # or project UI envar reference machine Using CircleCI cloud? The use of machine: true is deprecated. You must specify an image to use. The machine executor is configured using the machine key, which takes a map: Key Required Type Description image Y String The virtual machine image to use. View available images . Note: This key is not supported for Linux VMs on installations of CircleCI server. For information about customizing machine executor images on CircleCI installed on your servers, see our Machine provisioner documentation . docker_layer_caching N Boolean Set this to true to enable Docker layer caching . Example: Cloud Server jobs: build: # name of your job machine: # executor type image: ubuntu-2004:current # recommended linux image steps: # Commands run in a Linux virtual machine environment jobs: build: # name of your job machine: true # executor type steps: # Commands run in a Linux virtual machine environment Linux machine images Specifying an image in your configuration file is strongly recommended. CircleCI supports multiple Linux machine images that can be specified in the image field. For a full list of supported image tags, refer to the following pages in the Developer Hub: Ubuntu-2004 Ubuntu-2204 More information on the software available in each image can be found in our Discuss forum . The machine executor supports Docker Layer Caching , which is useful when you are building Docker images during your job or Workflow. Linux machine images on server If you are using CircleCI server, contact your system administrator for details of available Linux machine images. Linux GPU machine images When using the Linux GPU executor , the available images are: linux-cuda-11:default v11.4, v11.6, v11.8 (default), Docker v20.10.24 linux-cuda-12:default v12.0, v12.1 (default), Docker v20.10.24 Android machine images CircleCI supports running jobs on Android for testing and deploying Android applications. To use the Android image directly with the machine executor, add the following to your job: version: 2.1 jobs: build: machine: image: android:2024.11.1 The Android image can also be accessed using the Android orb . For examples, refer to the Using Android Images with the Machine Executor page. Windows machine images Specifying an image in your configuration file is strongly recommended. CircleCI supports multiple Windows machine images that can be specified in the image field. For a full list of supported images, refer to one of the following: windows-server-2022-gui image windows-server-2019 image More information on what software is available in each image can be found in our Discuss forum . Alternatively, use the Windows orb to manage your Windows execution environment. For examples, see the Using the Windows Execution Environment page. Windows machine images on server If you are using CircleCI server, contact your system administrator for details of available Windows machine images. Windows GPU machine image When using the Windows GPU executor , the available image is: windows-server-2019-cuda Example: version: 2.1 jobs: build: machine: image: windows-server-2019-cuda:current macos CircleCI supports running jobs on macOS , to allow you to build, test, and deploy apps for macOS, iOS , tvOS and watchOS . To run a job on a macOS virtual machine, add the macos key to the top-level configuration for your job and specify the version of Xcode to use. Key Required Type Description xcode Y String The version of Xcode that is installed on the virtual machine, see the Supported Xcode Versions section of the Testing iOS document for the complete list. Example: Use a macOS virtual machine with Xcode version 14.2.0: jobs: build: macos: xcode: "14.2.0" branches - DEPRECATED This key is deprecated. Use workflows filtering to control which jobs run for which branches. resource_class The resource_class feature allows you to configure CPU and RAM resources for each job. Resource classes are available for each execution environment, as described in the tables below. We implement soft concurrency limits for each resource class to ensure our system remains stable for all customers. If you are on a Performance or Custom Plan and experience queuing for certain resource classes, it is possible you are hitting these limits. Contact CircleCI support to request a raise on these limits for your account. If you do not specify a resource class, CircleCI will use a default value that is subject to change. It is best practice to specify a resource class as opposed to relying on a default. Java, Erlang and any other languages that introspect the /proc directory for information about CPU count may require additional configuration to prevent them from slowing down when using the CircleCI resource class feature. Programs with this issue may request 32 CPU cores and run slower than they would when requesting one core. Users of languages with this issue should pin their CPU count to their guaranteed CPU resources. If you want to confirm how much memory you have been allocated, you can check the cgroup memory hierarchy limit with grep hierarchical_memory_limit /sys/fs/cgroup/memory/memory.stat . Self-hosted runner Use the resource_class key to configure a self-hosted runner instance . For example: jobs: job_name: machine: true resource_class: <my-namespace>/<my-runner> Docker execution environment Example: jobs: build: docker: - image: cimg/base:2024.12 resource_class: xlarge steps: ... // other config x86 For credit and access information, see the Resource classes page . Resource class access is dependent on your Plan . Class vCPUs RAM Cloud Server small 1 2GB medium 2 4GB medium+ 3 6GB large 4 8GB xlarge 8 16GB 2xlarge 16 32GB 2xlarge+ 20 40GB Arm Class vCPUs RAM Cloud Server arm.medium 2 8 GB arm.large 4 16 GB arm.xlarge 8 32 GB arm.2xlarge 16 64 GB LinuxVM execution environment Class vCPUs RAM Disk Size Cloud Server medium 2 7.5 GB 150GB large 4 15 GB 150GB xlarge 8 32 GB 150GB 2xlarge 16 64 GB 150GB 2xlarge+ 32 64 GB 150GB Example: Cloud Server jobs: build: machine: image: ubuntu-2004:2024.01.2 # recommended linux image resource_class: large steps: ... // other config jobs: build: machine: true resource_class: large steps: ... // other config macOS execution environment Class vCPUs RAM Cloud Server m4pro.medium 6 @ 4.51 GHz 28GB m4pro.large 12 @ 4.51 GHz 56GB m2pro.medium 4 @ 3.49 GHz 8GB m2pro.large 8 @ 3.49 GHz 16GB macos.m1.medium.gen1 4 @ 3.2 GHz 6GB macos.m1.large.gen1 8 @ 3.2 GHz 12GB Example: jobs: build: macos: xcode: "15.4.0" resource_class: m2pro.medium steps: ... // other config macOS execution environment on server If you are working on CircleCI server you can access the macOS execution environment using self-hosted runner . Windows execution environment Class vCPUs RAM Disk Size Cloud Server windows.medium (default) 4 15GB 200 GB windows.large 8 30GB 200 GB windows.xlarge 16 60GB 200 GB windows.2xlarge 32 128GB 200 GB Using server? Check with your systems administrator whether you have access to the Windows execution environment. Example: Cloud Server version: 2.1 jobs: build: # name of your job resource_class: 'windows.medium' machine: image: 'windows-server-2022-gui:current' shell: 'powershell.exe -ExecutionPolicy Bypass' steps: # Commands are run in a Windows virtual machine environment - checkout - run: Write-Host 'Hello, Windows' version: 2.1 jobs: build: # name of your job machine: image: windows-default steps: # Commands are run in a Windows virtual machine environment - checkout - run: Write-Host 'Hello, Windows' GPU execution environment (Linux) Class vCPUs RAM GPUs GPU model GPU Memory (GiB) Disk Size (GiB) Cloud Server gpu.nvidia.small 4 16 1 NVIDIA Tesla P4 16 150 gpu.nvidia.small.gen2 4 16 1 NVIDIA A10G 24 150 gpu.nvidia.small.multi 4 15 2 NVIDIA Tesla T4 16 150 gpu.nvidia.medium.multi 8 30 4 NVIDIA Tesla T4 16 150 gpu.nvidia.medium 8 30 1 NVIDIA Tesla T4 16 150 gpu.nvidia.large 8 30 1 NVIDIA Tesla V100 16 150 Example: version: 2.1 jobs: build: machine: image: linux-cuda-12:default resource_class: gpu.nvidia.medium steps: - run: nvidia-smi - run: docker run --gpus all nvidia/cuda:9.0-base nvidia-smi See the Available Linux GPU images section for the full list of available images. GPU execution-environment (Windows) Class vCPUs RAM GPUs GPU model GPU Memory (GiB) Disk Size (GiB) Cloud Server windows.gpu.nvidia.medium 16 60 1 NVIDIA Tesla T4 16 200 Example: version: 2.1 orbs: win: circleci/windows@5.0.0 jobs: build: executor: win/server-2019-cuda steps: - checkout - run: '&"C:\Program Files\NVIDIA Corporation\NVSMI\nvidia-smi.exe"' (2) This resource requires review by our support team. Open a support ticket if you would like to request access. Arm VM execution-environment Class vCPUs RAM Disk Size Cloud Server arm.medium (default) 2 8GB 100 GB arm.large 4 16GB 100 GB arm.xlarge 8 32GB 100 GB arm.2xlarge 16 64GB 100 GB Using server? Check with your systems administrator whether you have access to the Arm execution environment. Example: Cloud Server jobs: my-job: machine: image: ubuntu-2004:2024.01.2 resource_class: arm.medium steps: - run: uname -a - run: echo "Hello, Arm!" jobs: my-job: machine: image: arm-default resource_class: arm.medium steps: - run: uname -a - run: echo "Hello, Arm!" steps The steps setting in a job should be a list of single key/value pairs, the key of which indicates the step type. The value may be either a configuration map or a string (depending on what that type of step requires). For example, using a map: jobs: build: docker: - image: cimg/base:2024.01 working_directory: ~/canary-python environment: FOO: bar steps: - run: name: Running tests command: make test Here run is a step type. The name attribute is used by the UI for display purposes. The command attribute is specific for run step and defines command to execute. Some steps may implement a shorthand semantic. For example, run may be also be called like this: jobs: build: docker: - image: cimg/base:2024.01 steps: - run: make test In its short form, the run step allows us to directly specify which command to execute as a string value. In this case step itself provides default suitable values for other attributes ( name here will have the same value as command , for example). Another shorthand, which is possible for some steps, is to use the step name as a string instead of a key/value pair: jobs: build: docker: - image: cimg/base:2024.01 steps: - checkout In this case, the checkout step will check out project source code into the job’s working_directory . In general all steps can be described as: Key Required Type Description <step_type> Y Map or String A configuration map for the step or some string whose semantics are defined by the step. Each built-in step is described in detail below. run The run step is used to invoke command-line programs. The run step takes either a map of configuration values, or, when called in its short-form, a string that will be used as both the command and name . Run commands are executed using non-login shells by default, so you must explicitly source any dotfiles as part of the command. the run step replaces the deprecated deploy step. If your job has a parallelism of 1, the deprecated deploy step can be swapped out directly for the run step. If your job has parallelism > 1 , see Migrate from deploy to run . Key Required Type Description command Y String Command to run via the shell name N String Title of the step to be shown in the CircleCI UI (default: full command ) shell N String Shell to use for execution command (default: See Default Shell Options ) environment N Map Additional environment variables, locally scoped to command background N Boolean Whether or not this step should run in the background (default: false) working_directory N String In which directory to run this step. Will be interpreted relative to the working_directory of the job). (default: . ) no_output_timeout N String Elapsed time the command can run without output. The string is a decimal with unit suffix, such as "20m", "1.25h", "5s". The default is 10 minutes and the maximum is governed by the maximum time a job is allowed to run . when N String Specify when to enable or disable the step . Takes the following values: always , on_success , on_fail (default: on_success ) Each run declaration represents a new shell. It is possible to specify a multi-line command , each line of which will be run in the same shell. Example: jobs: my-job: docker: - image: cimg/base:2024.12 resource_class: xlarge steps: - run: command: | echo Running test mkdir -p /tmp/test-results make test You can also configure commands to run in the background if you do not want to wait for the step to complete before moving on to subsequent run steps. Default shell options For jobs that run on Linux , the default value of the shell option is /bin/bash -eo pipefail if /bin/bash is present in the build container. Otherwise it is /bin/sh -eo pipefail . The default shell is not a login shell ( --login or -l are not specified). Hence, the shell will not source your ~/.bash_profile , ~/.bash_login , ~/.profile files. For jobs that run on macOS , the default shell is /bin/bash --login -eo pipefail . The shell is a non-interactive login shell. The shell will execute /etc/profile/ followed by ~/.bash_profile before every step. For more information about which files are executed when Bash is invocated, see the INVOCATION section of the bash manpage . Descriptions of the -eo pipefail options are provided below. -e Exit immediately if any of the following exits with a non-zero status: A pipeline (which may consist of a single simple command). A subshell command enclosed in parentheses. One of the commands executed as part of a command list enclosed by braces. In the previous example, mkdir failed to create a directory and returned a non-zero status, then command execution would be terminated, and the whole step would be marked as failed. If you desire the opposite behaviour, you need to add set +e in your command or override the default shell in your configuration map of run . For example: Example: - run: command: | echo Running test set +e mkdir -p /tmp/test-results make test - run: shell: /bin/sh command: | echo Running test mkdir -p /tmp/test-results make test -o pipefail If pipefail is enabled, the pipeline’s return status is the value of the last (rightmost) command to exit with a non-zero status, or zero if all commands exit successfully. The shell waits for all commands in the pipeline to terminate before returning a value. Example: - run: make test | tee test-output.log If make test fails, the -o pipefail option will cause the whole step to fail. Without -o pipefail , the step will always run successfully because the result of the whole pipeline is determined by the last command ( tee test-output.log ), which will always return a zero status. If make test fails the rest of pipeline will be executed. If you want to avoid this behaviour, you can specify set +o pipefail in the command or override the whole shell (see example above). In general, we recommend using the default options ( -eo pipefail ) because they show errors in intermediate commands and simplify debugging job failures. For convenience, the UI displays the used shell and all active options for each run step. For more information, see the Using Shell Scripts document. Background commands The background attribute enables you to configure commands to run in the background. Job execution will immediately proceed to the next step rather than waiting for return of a command with the background attribute set to true . The following example shows the configuration for running the X virtual framebuffer in the background which is commonly required to run Selenium tests. Example: - run: name: Running X virtual framebuffer command: Xvfb :99 -screen 0 1280x1024x24 background: true - run: make test Shorthand syntax run has a very convenient shorthand syntax. Example: - run: make test # shorthanded command can also have multiple lines - run: | mkdir -p /tmp/test-results make test In this case, command and name become the string value of run , and the rest of the config map for that run have their default values. The when attribute By default, CircleCI will execute job steps one at a time, in the order that they are defined in config.yml , until a step fails (returns a non-zero exit code). After a command fails, no further job steps will be executed. Adding the when attribute to a job step allows you to override this default behaviour, and selectively run or skip steps depending on the status of the job. The when attribute accepts the following values: on_success The step will run only if all of the previous steps have been successful (returned exit code 0). on_success is the default value. always The step will run regardless of the exit status of previous steps. always is useful if you have a task that you want to run regardless of whether the previous steps are successful or not. For example, you might have a job step that needs to upload logs or code-coverage data somewhere. on_fail The step will run only if one of the preceding steps has failed (returns a non-zero exit code). A common use of on_fail is to store some diagnostic data to help debug test failures, or to run custom notifications about the failure, such as sending emails or triggering alerts. Some steps, such as store_artifacts and store_test_results will always run, even if a step has failed (returned a non-zero exit code) previously. The when attribute, store_artifacts and store_test_results are not run if the job has been killed by a cancel request or has reached the runtime timeout limit. Example: - run: name: Upload CodeCov.io Data command: bash <(curl -s https://codecov.io/bash) -F unittests when: always # Uploads code coverage results, pass or fail Ending a job from within a step A job can exit without failing by using run: circleci-agent step halt . However, if a step within the job is already failing then the job will continue to fail. This can be useful in situations where jobs need to conditionally execute. Example: halt is used to avoid running a job on the develop branch: - run: | if [ "$CIRCLE_BRANCH" = "develop" ]; then circleci-agent step halt fi The when step The when and unless steps are supported in version: 2.1 configuration A conditional step consists of a step with the key when or unless . Under the when key are the subkeys condition and steps . The purpose of the when step is customizing commands and job configuration to run on custom conditions (determined at config-compile time) that are checked before a workflow runs. See the Conditional Steps section of the reusable configuration reference for more details. Key Required Type Description condition Y Logic A logic statement steps Y Sequence A list of steps to execute when the condition is true Example: version: 2.1 jobs: # conditional steps may also be defined in `commands:` job_with_optional_custom_checkout: parameters: custom_checkout: type: string default: "" machine: image: ubuntu-2004:2024.11.1 steps: - when: condition: <<parameters.custom_checkout>> steps: - run: echo "my custom checkout" - unless: condition: <<parameters.custom_checkout>> steps: - checkout workflows: build-test-deploy: jobs: - job_with_optional_custom_checkout: custom_checkout: "any non-empty string is truthy" - job_with_optional_custom_checkout checkout A special step used to check out source code to the configured path (defaults to the working_directory ). The reason this is a special step is because it is more of a helper function designed to simplify the process of checking out code. If you require doing git over HTTPS you should not use this step as it configures git to checkout over SSH. Key Required Type Description path N String Checkout directory. Will be interpreted relative to the working_directory of the job). (default: . ) If path already exists and is: A git repository - step will not clone whole repository, instead will fetch origin NOT a git repository - step will fail. In the case of checkout , the step type is just a string with no additional attributes. Example: jobs: build: docker: - image: cimg/go:1.24.2 steps: - checkout The checkout command automatically adds the required authenticity keys for interacting with GitHub and Bitbucket over SSH. These keys are detailed further in the integration guide . This guide is also helpful if you wish to implement a custom checkout command. CircleCI does not check out submodules. If your project requires submodules, add run steps with appropriate commands as shown in the following example: jobs: build: docker: - image: cimg/go:1.24.2 steps: - checkout - run: git submodule sync - run: git submodule update --init The checkout step will configure Git to skip automatic garbage collection. If you are caching your .git directory with restore_cache and would like to use garbage collection to reduce its size, you may wish to use a run step with command git gc before doing so. setup_remote_docker setup_remote_docker is not compatible with the machine executor. See Docker Layer Caching in Machine Executor for information on how to enable DLC with the machine executor. The version key is not currently supported on CircleCI server. Contact your system administrator for information about the Docker version installed in your remote Docker environment. If you are on server 4.x, you can find the default AWS AMI here . Allows Docker commands to be run locally. See Running Docker commands for details. Key Required Type Description docker_layer_caching N boolean Set this to true to enable Docker Layer Caching in the Remote Docker Environment (default: false ) version N String Version string of Docker you would like to use (default: 24.0.9 ). View the list of supported Docker versions here . Example: jobs: build: docker: - image: cimg/base:2024.06 steps: # ... steps for building/testing app ... - setup_remote_docker: version: default save_cache Generates and stores a cache of a file or directory of files such as dependencies or source code. Caches are stored in CircleCI’s object storage. Later jobs can restore this cache . Learn more on the Caching dependencies page. Cache retention can be customized on the CircleCI web app by navigating to Plan Usage Controls . Key Required Type Description paths Y List List of directories which should be added to the cache key Y String Unique identifier for this cache name N String Title of the step to be shown in the CircleCI UI (default: "Saving Cache") when N String Specify when to enable or disable the step . Takes the following values: always , on_success , on_fail (default: on_success ) The cache for a specific key is immutable and cannot be changed once written. If the cache for the given key already exists it will not be modified, and job execution will proceed to the next step. When storing a new cache, the key value may contain special, templated, values for your convenience: Template Description {{ .Branch }} The VCS branch currently being built. {{ .BuildNum }} The CircleCI build number for this build. {{ .Revision }} The VCS revision currently being built. {{ .CheckoutKey }} The SSH key used to checkout the repository. {{ .Environment.variableName }} The environment variable variableName (supports any environment variable exported by CircleCI or added to a specific context --not any arbitrary environment variable). {{ checksum "filename" }} A base64 encoded SHA256 hash of the given filename’s contents. This should be a file committed in your repository and may also be referenced as a path that is absolute or relative from the current working directory. Good candidates are dependency manifests, such as package-lock.json , pom.xml or project.clj . It is important that this file does not change between restore_cache and save_cache , otherwise the cache will be saved under a cache key different than the one used at restore_cache time. {{ epoch }} The current time in seconds since the UNIX epoch. {{ arch }} The OS and CPU information. Useful when caching compiled binaries that depend on OS and CPU architecture, for example, darwin amd64 versus linux i386/32-bit . During step execution, the templates above will be replaced by runtime values and the resultant string is used as the key . Template examples: myapp-{{ checksum "package-lock.json" }} cache will be regenerated every time something is changed in package-lock.json file, different branches of this project will generate the same cache key. myapp-{{ .Branch }}-{{ checksum "package-lock.json" }} same as the previous one, but each branch will generate separate cache myapp-{{ epoch }} every run of a job will generate a separate cache While choosing suitable templates for your cache key , keep in mind the following: Cache saving is not a free operation. See the billing section on the FAQ page. It takes time to upload the cache. Best practice is to have a key that generates a new cache only if something actually changed and avoid generating a new one every time a job is run. Given the immutability of caches, it might be helpful to start all your cache keys with a version prefix v1-... . That way you will be able to regenerate all your caches just by incrementing the version in this prefix. Examples: - save_cache: key: v1-myapp-{{ arch }}-{{ checksum "project.clj" }} paths: - /home/ubuntu/.m2 - save_cache: key: v1-{{ checksum "yarn.lock" }} paths: - node_modules/workspace-a - node_modules/workspace-c Wildcards are not currently supported in save_cache paths. Visit the Ideas board and vote for this feature if it would be useful for you or your organization. restore_cache Restores a previously saved cache based on a key . Cache needs to have been saved first for this key using the save_cache step . Learn more in the caching documentation . Key Required Type Description key Y (1) String Single cache key to restore keys Y (1) List List of cache keys to lookup for a cache to restore. Only first existing key will be restored. name N String Title of the step to be shown in the CircleCI UI (default: "Restoring Cache") (1) at least one attribute has to be present. If key and keys are both given, key will be checked first, and then keys . A key is searched against existing keys as a prefix. When there are multiple matches, the most recent match will be used, even if there is a more precise match. Example: steps: - save_cache: key: v1-myapp-cache paths: - ~/d1 - save_cache: key: v1-myapp-cache-new paths: - ~/d2 - run: rm -f ~/d1 ~/d2 - restore_cache: key: v1-myapp-cache In this case cache v1-myapp-cache-new will be restored because it’s the most recent match with v1-myapp-cache prefix even if the first key ( v1-myapp-cache ) has exact match. For more information on key formatting, see the key section of save_cache step . When CircleCI encounters a list of keys , the cache will be restored from the first key matching an existing cache. We recommend you use a more specific key first (for example, cache for exact version of package-lock.json ) and more generic keys after (for example, any cache for this project). If no key has a cache that exists, the step will be skipped with a warning. A path is not required here because the cache will be restored to the location from which it was originally saved. Example: - restore_cache: keys: - v1-myapp-{{ arch }}-{{ checksum "project.clj" }} # if cache for exact version of `project.clj` is not present then load any most recent one - v1-myapp- # ... Steps building and testing your application ... # cache will be saved only once for each version of `project.clj` - save_cache: key: v1-myapp-{{ arch }}-{{ checksum "project.clj" }} paths: - /foo deploy - DEPRECATED See run for current processes. If you have parallelism > 1 in your job, see the Migrate from deploy to run guide. store_artifacts Step to store artifacts (for example logs, binaries, etc) to be available in the web app or through the API. See the Uploading Artifacts page for more information. Key Required Type Description path Y String Directory in the primary container to save as job artifacts destination N String Prefix added to the artifact paths in the artifacts API (default: the directory of the file specified in path ) There can be multiple store_artifacts steps in a job. Using a unique prefix for each step prevents them from overwriting files. Artifact storage retention can be customized on the CircleCI web app by navigating to Plan Usage Controls . Example: - run: name: Build the Jekyll site command: bundle exec jekyll build --source jekyll --destination jekyll/_site/docs/ - store_artifacts: path: jekyll/_site/docs/ destination: circleci-docs store_test_results Special step used to upload and store test results for a build. Test results are visible on the CircleCI web application under each build’s Test Summary section. Storing test results is useful for timing analysis of your test suites. For more information on storing test results, see the Collecting Test Data page. You can also store test results as build artifacts. For steps, refer to the store_artifacts step section. Key Required Type Description path Y String Path (absolute, or relative to your working_directory ) to directory containing JUnit XML test metadata files, or to a single test file. Example: Directory structure: test-results ├── jest │ └── results.xml ├── mocha │ └── results.xml └── rspec └── results.xml config.yml syntax: - store_test_results: path: test-results persist_to_workspace Special step used to persist a temporary file to be used by another job in the workflow. For more information on using workspaces, see the Using Workspaces to Share Data Between Jobs page. persist_to_workspace adopts the storage settings from the storage customization controls on the CircleCI web app. If no custom setting is provided, persist_to_workspace defaults to 15 days. Workspace storage retention can be customized on the CircleCI web app by navigating to Plan Usage Controls . Key Required Type Description root Y String Either an absolute path or a path relative to working_directory paths Y List Glob identifying file(s), or a non-glob path to a directory to add to the shared workspace. Interpreted as relative to the workspace root. Must not be the workspace root itself. The root key is a directory on the container which is taken to be the root directory of the workspace. The path values are all relative to the root. Example for root Key: For example, the following step syntax persists the specified paths from /tmp/dir into the workspace, relative to the directory /tmp/dir . - persist_to_workspace: root: /tmp/dir paths: - foo/bar - baz After this step completes, the following directories are added to the workspace: /tmp/dir/foo/bar /tmp/dir/baz Example for paths Key: - persist_to_workspace: root: /tmp/workspace paths: - target/application.jar - build/* The paths list uses Glob from Go, and the pattern matches filepath.Match . pattern: { term } term: '*' matches any sequence of non-Separator characters '?' matches any single non-Separator character '[' [ '^' ] { character-range } ']' character class (must be non-empty) c matches character c (c != '*', '?', '\\', '[') '\\' c matches character c character-range: c matches character c (c != '\\', '-', ']') '\\' c matches character c lo '-' hi matches character c for lo <= c <= hi The Go documentation states that the pattern may describe hierarchical names such as /usr/*/bin/ed (assuming the Separator is '/'). Everything must be relative to the work space root directory. attach_workspace Special step used to attach the workflow’s workspace to the current container. The full contents of the workspace are downloaded and copied into the directory the workspace is being attached at. For more information on using workspaces, see the Using workspaces page. Key Required Type Description at Y String Directory to attach the workspace to. Workspace storage retention can be customized on the CircleCI web app by navigating to Plan Usage Controls . Example: - attach_workspace: at: /tmp/workspace The lifetime of artifacts, workspaces, and caches can be customized on the CircleCI web app by navigating to Plan Usage Controls . Here you can control the storage retention periods for these objects. If no storage period is set, the default storage retention period of artifacts is 30 days, while the default storage retention period of workspaces and caches is 15 days. add_ssh_keys Special step that adds SSH keys from a project’s settings to a container. Also configures SSH to use these keys. For more information on SSH keys see the Create additional GitHub SSH keys page. Using server? only MD5 fingerprints are supported. In CircleCI in Project Settings SSH keys Additional SSH keys the MD5 fingerprint will be visible. SHA256 support is planned for an upcoming server release. Key Required Type Description fingerprints N List List of fingerprints corresponding to the keys to be added (default: all keys added) steps: - add_ssh_keys: fingerprints: - "b7:35:a6:4e:9b:0d:6d:d4:78:1e:9a:97:2a:66:6b:be" - "SHA256:NPj4IcXxqQEKGXOghi/QbG2sohoNfvZ30JwCcdSSNM0" Even though CircleCI uses ssh-agent to sign all added SSH keys, you must use the add_ssh_keys key to actually add keys to a container. Using pipeline values Pipeline values are available to all pipeline configurations and can be used without previous declaration. For a list of pipeline values, see the Pipeline values and parameters page. Example: version: 2.1 jobs: build: docker: - image: cimg/node:20.18.1 environment: IMAGETAG: latest working_directory: ~/main steps: - run: echo "This is pipeline ID << pipeline.id >>" circleci_ip_ranges A paid account on a Performance or Scale Plan is required to access IP ranges. Enables jobs to go through a set of well-defined IP address ranges. See IP ranges for details. Example: version: 2.1 jobs: build: circleci_ip_ranges: true # opts the job into the IP ranges feature docker: - image: curlimages/curl steps: - run: echo “Hello World” workflows: build-workflow: jobs: - build workflows Used for orchestrating all jobs. Each workflow consists of the workflow name as a key and a map as a value. A name should be unique within the current config.yml . The top-level keys for the Workflows configuration are version and jobs . For more information, see the Using Workflows to Orchestrate Jobs page. version The workflows version key is not required for version: 2.1 configuration The Workflows version field is used to issue warnings for deprecation or breaking changes. Key Required Type Description version Y if config version is 2 String Should currently be 2 workflows: version: 2 my-workflow: jobs: - my-job < workflow_name > A unique name for your workflow. workflows: my-workflow: jobs: - my-job max_auto_reruns The max_auto_reruns key is used to configure the maximum number of automatic reruns for a workflow. version: 2.1 workflows: my-workflow: max_auto_reruns: 3 jobs: - build - test - deploy: requires: - build - test The value of max_auto_reruns can be an integer between 1 and 5. For more information, see the Automatic Reruns page. triggers Specifies which triggers will cause this workflow to be executed. Default behavior is to trigger the workflow when pushing to a branch. Key Required Type Description triggers N Array Should currently be schedule . workflows: nightly: triggers: - schedule: cron: "0 0 * * *" filters: branches: only: - main - beta jobs: - test schedule Scheduled workflows are not available for projects integrated through the GitHub App, GitLab or Bitbucket Data Center. The scheduled workflows feature is set to be deprecated. Using scheduled pipelines rather than scheduled workflows offers several benefits. Visit the scheduled pipelines migration guide to find out how to migrate existing scheduled workflows to scheduled pipelines. If you would like to set up scheduled pipelines from scratch, visit the Scheduled pipelines page. A workflow may have a schedule indicating it runs at a certain time, for example a nightly build that runs every day at 12am UTC: workflows: nightly: triggers: - schedule: cron: "0 0 * * *" filters: branches: only: - main - beta jobs: - test cron The cron key is defined using POSIX crontab syntax. Key Required Type Description cron Y String See the crontab man page . workflows: nightly: triggers: - schedule: cron: "0 0 * * *" filters: branches: only: - main - beta jobs: - test filters Trigger filters can have the key branches . Key Required Type Description filters Y Map A map defining rules for execution on specific branches workflows: nightly: triggers: - schedule: cron: "0 0 * * *" filters: branches: only: - main - beta jobs: - test branches The branches key controls whether the current branch should have a schedule trigger created for it, where current branch is the branch containing the config.yml file with the trigger stanza. That is, a push on the main branch will only schedule a workflow for the main branch. Branches can have the keys only and ignore which each map to a single string naming a branch. You may also use regular expressions to match against branches by enclosing them with `/’s, or map to a list of such strings. Regular expressions must match the entire string. Any branches that match only will run the job. Any branches that match ignore will not run the job. If neither only nor ignore are specified then all branches will run the job. If both only and ignore are specified, the only is used and ignore will have no effect. workflows: commit: jobs: - test - deploy nightly: triggers: - schedule: cron: "0 0 * * *" filters: branches: only: - main - /^release\/.*/ jobs: - coverage Key Required Type Description branches Y Map A map defining rules for execution on specific branches only 1 N String, or List of Strings Either a single branch specifier, or a list of branch specifiers ignore 1 N String, or List of Strings Either a single branch specifier, or a list of branch specifiers 1 : One of either only or ignore branch filters must be specified. If both are present, only is used. Using when in workflows Using when or unless under workflows is supported in version: 2.1 configuration. Workflows are always run unless there is a when or unless filter that prevents the workflow from being run. If you want a workflow to run in every pipeline, do not add a when or unless filter. You may use a when clause (the inverse clause unless is also supported) under a workflow declaration with a logic statement to determine whether or not to run that workflow. The example configuration below uses a pipeline parameter, run_integration_tests to drive the integration_tests workflow. version: 2.1 workflows: integration_tests: when: pipeline.git.branch == "main" jobs: - mytestjob jobs: ... This example prevents the workflow integration_tests from running unless the pipeline is triggered on the main branch. Refer to the Workflows for more examples and conceptual information. jobs A job can have the keys requires , name , context , type , and filters . Key Required Type Description jobs Y List A list of jobs to run with their dependencies < job_name > A job name that exists in your config.yml . version: 2.1 jobs: my-job: docker: - image: cimg/node:20.18.1 steps: - run: echo "Hello World" workflows: my-workflow: jobs: - my-job override-with The override-with key is used to override the job configuration with a job from the referenced orb. Key Required Type Description override-with N String The orb job name that will be used to override the existing job configuration. (Both URL-based and registry orbs are supported) Example: version: 2.1 orbs: my-orb: << url-ref >> jobs: build: steps: - run: task build test: steps: - run: task test deploy: steps: - run: ccc deploy workflows: - build-test-deploy: jobs: - build - test: override-with: my-orb/my-test requires: build - deploy: requires: test In the example above, the test job in the workflow is being overridden with the orb job my-orb/my-test . The my-orb/my-test job might be defined with a different resource class or execution steps. If the my-orb/my-test job is not defined inside the orb, the test job will compile using the local job definition. serial-group The serial-group key is used to add a property to a job to allow a group of jobs to run in series, rather than concurrently, across an organization. Serial groups control the orchestration of jobs across an organization, not just within projects and pipelines. The serial-group key is configurable per job. It is not possible to configure the key for a group of jobs at this time. The value of the serial-group key is a string that is used to group jobs together to run one after another. The key must meet the following requirements: Must be less than or equal to (≤) 512 characters, once compiled. Must not be blank. Must consist of alphanumeric characters plus, . , - , _ , / . Note the following features of serial groups: You can use pipeline values and parameters in the serial-group key. Serial groups will wait for five hours. After this jobs waiting in the group will be cancelled. This does not affect the standard limits that apply to a job’s runtime . Pipeline order protection in serial groups Jobs in a serial group follow an order protection mechanism, as follows: Jobs start in the order they join the queue, but are accepted based on pipeline number. If a group is waiting/running and another job in the same project attempts to join the queue with a lower pipeline number, the job is skipped. This immediate skip process exists to maintain order integrity, which is a safety process to avoid unexpected work in a build, for example, a deployment job running a previous version unexpectedly. If there are no serial groups waiting/running, a pipeline with a lower number can start, such as restoring back to a previous pipeline via a rerun workflow. Key Required Type Description serial-group N String A string that is used across an org to group jobs together to run one after another. Can include pipeline values and parameters. Use this same serial group across multiple pipelines to control the orchestration of jobs across an organization. Example: # Creating multiple pipelines at the same time with the below config will results in # all pipelines running test and build but only a single pipeline will run deploy at a time. workflows: main-workflow: jobs: - test - build - deploy: serial-group: << pipeline.project.slug >>/deploy-group requires: - test - build For more information, see the Controlling serial execution across your organization page. requires Jobs are run concurrently by default, so you must explicitly require any dependencies by their job name if you need some jobs to run sequentially. Key Required Type Description requires N List A list of jobs that must succeed or attain a specified status for the job to start. Note : When jobs in the current workflow that are listed as dependencies are not executed (due to a filter function for example), their requirement as a dependency for other jobs will be ignored by the requires option. However, if all dependencies of a job are filtered, then that job will not be executed either. Possible types of requires items: Job name (a required job that must succeed for the job to start) Map of job name to status (a required job that must attain the specified status for the job to start) Map of job name to a list of statuses (a required job that must attain one of the specified status for the job to start) The possible status values are: success , failed and canceled . workflows: my-workflow: jobs: - build - test: requires: - build - deploy: requires: - build - test - notify-build-canceled: requires: - build: canceled - cleanup: requires: - deploy: - failed - canceled name The name key can be used to invoke reusable jobs across any number of workflows. Using the name key ensures numbers are not appended to your job name (for example, sayhello-1 , sayhello-2, etc.). The name you assign to the name key needs to be unique, otherwise the numbers will still be appended to the job name. Key Required Type Description name N String A replacement for the job name. Useful when calling a job multiple times. If you want to invoke the same job multiple times, and a job requires one of the duplicate jobs, this key is required. (2.1 only) workflows: my-workflow: jobs: - my-job: name: my-alternative-job-name context Jobs may be configured to use global environment variables set for an organization, see the Contexts document for adding a context in the application settings. Key Required Type Description context N String/List The name of the context(s). The initial default name is org-global . Each context name must be unique. If using CircleCI server, only a single context per workflow is supported. Note: A maximum of 100 unique contexts across all workflows is allowed. workflows: my-workflow: jobs: - my-job: context: org-global It is also possible to use a list of contexts, as follows: workflows: my-workflow: jobs: - my-job: context: - org-global - project-global type A job may have a type of approval indicating it must be manually approved before downstream jobs may proceed. For more information see the Using workflows to orchestrate jobs page. Jobs run in the dependency order until the workflow processes a job with the type: approval key followed by a job on which it depends, for example: workflows: my-workflow: jobs: - build - test: requires: - build - hold: type: approval requires: - test - deploy: requires: - hold An approval job can have any name. In the example above the approval job is named hold . The name you choose for an approval job should not be used to define a job in the main configuration. An approval job only exists as a workflow orchestration devise. filters Filter job execution within a workflow based on the following: Branch Tag Expression-based condition Job filters can have the keys branches or tags . Workflows will ignore job-level branching. 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 . Key Required Type Description filters N Map A map or string to define rules for job execution. Branch and tag filters require a map. Expression-based filters require a string. The following is an example of how the CircleCI documentation project uses a regular expression to filter running a job in a workflow only on a specific branch: # ... workflows: build-deploy: jobs: - js_build - build_server_pdfs: # << the job to conditionally run based on the filter-by-branch-name. filters: branches: only: /server\/.*/ # the job build_server_pdfs will only run when the branch being built starts with server/ You can read more about using regular expressions in your config in the Using workflows to schedule jobs page. Expression-based job filters Expression-based job filters allow you to conditionally run jobs based on the following: Pipeline values Pipeline parameters An expression-based job filter is a rule that is evaluated against pipeline values and parameters to decide whether a job should run. Using expression-based job filters is one way to optimize your pipelines. Optimizations include the following: Lower costs. Decrease time to feedback. Run specific jobs based on the context of the source of change. workflows: deploy: jobs: - init-service - test-service - build-service-image: requires: - init-service - dry-run-service: requires: - init-service filters: pipeline.git.branch != "main" and pipeline.git.branch != "canary" - publish-service: requires: - build-service-image - test-service filters: pipeline.git.branch == "main" or pipeline.git.tag starts-with "release" - deploy-service: context: - org-global requires: - publish-service filters: pipeline.git.branch == "main" and pipeline.parameters.my-custom-param starts-with "DEPLOY:" Examples: Only run the job on the project’s main branch: filters: pipeline.git.branch == "main" Only run the job on the project’s main branch, or branches starting with integration-test : filters: pipeline.git.branch == "main" or pipeline.git.branch starts-with "integration-test" Only run the job on the main branch, and disallow use with pipelines triggered with unversioned configuration : filters: pipeline.git.branch == "main" and not (pipeline.trigger_source starts-with "api") Use pipeline parameters and the pipeline value pipeline.git.branch to run a job only on specific branches or when triggered via the API with a pipeline parameter set to true: version: 2.1 parameters: run-storybook-tests: type: boolean default: false ... # jobs configuration ommitted for brevity workflows: build: jobs: - setup - storybook-tests: requires: - setup filters: | pipeline.parameters.run-storybook-tests or pipeline.git.branch == "dry-run-deploy" or pipeline.git.branch starts-with "deploy" You can use the API to trigger a pipeline with a pipeline parameter set to true: Using server? If you are using CircleCI server, replace https://circleci.com with your server hostname when interacting with the CircleCI API. curl -X POST https://circleci.com/api/v2/project/circleci/<org-id>/<project-id>/pipeline/run \ --header "Circle-Token: $CIRCLE_TOKEN" \ --header "content-type: application/json" \ --data { "definition_id": "<pipeline-definition-id>", "config": {"branch": "<your-branch-name>"}, "checkout": {"branch": "<your-branch-name>"}, "parameters": {"run-storybook-tests": "true"} } Operators The operators you can use for expression-based job filters are described in the following table. You can also group sub-expressions with parentheses ( , ) . as in the examples above. Operator type Operators Description Logical and , or These are short-circuiting boolean operators. Equality == , != String, numeric, and boolean equality. If the operands are of different types then == will evaluate false , and != will evaluate true . Equality starts-with String prefix equality, "hello world" starts-with "hello" evaluates as true . It is an error to use a non-string type as an operand. Numeric comparison >= , > , ⇐ , < Numeric comparisons. It is an error to use a non-numeric type as an operand. Negation not Boolean negation. Note that not has very high precedence and so binds very tightly. Use sub-expressions to apply not to more complex expressions. For example, with foo being true and bar being false : not foo and bar evaluates to false not (foo and bar) evaluates to true branches The branches filter can have the keys only and ignore , which map to a single string naming a branch. You may also use regular expressions to match against branches by enclosing them with slashes, or map to a list of such strings. Regular expressions must match the entire string. Any branches that match only will run the job. Any branches that match ignore will not run the job. If neither only nor ignore are specified then all branches will run the job. If both only and ignore are specified the only is considered before ignore . Key Required Type Description branches N Map A map defining rules for execution on specific branches. only N String, or list of strings Either a single branch specifier, or a list of branch specifiers. ignore N String, or list of strings Either a single branch specifier, or a list of branch specifiers. workflows: 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(?:-.+)?$/ tags CircleCI does not run workflows for tags unless you explicitly specify tag filters. If a job requires any other jobs (directly or indirectly), you must specify tag filters for those jobs. Tags can have the keys only and ignore . You may also use regular expressions to match against tags by enclosing them with slashes, or map to a list of such strings. Regular expressions must match the entire string. Both lightweight and annotated tags are supported. Any tags that match only will run the job. Any tags that match ignore will not run the job. If neither only nor ignore are specified then the job is skipped for all tags. If both only and ignore are specified the only is considered before ignore . Key Required Type Description tags N Map A map defining rules for execution on specific tags only N String, or List of Strings Either a single tag specifier, or a list of tag specifiers ignore N String, or List of Strings Either a single tag specifier, or a list of tag specifiers For more information, see the Executing workflows for a git tag section of the Workflows page. workflows: untagged-build: jobs: - build tagged-build: jobs: - build: filters: tags: only: /^v.*/ matrix The matrix key is supported in version: 2.1 configuration The matrix stanza allows you to run a parameterized job multiple times with different arguments. For more information see the how-to guide on Using Matrix Jobs . In order to use the matrix stanza, you must use parameterized jobs. Key Required Type Description parameters Y Map A map of parameter names to every value the job should be called with exclude N List A list of argument maps that should be excluded from the matrix alias N String An alias for the matrix, usable from another job’s requires stanza. Defaults to the name of the job being executed Example: The following is a basic example of using matrix jobs. workflows: workflow: jobs: - build: matrix: parameters: version: ["0.1", "0.2", "0.3"] platform: ["macos", "windows", "linux"] This expands to 9 different build jobs, and could be equivalently written as: workflows: workflow: jobs: - build: name: build-macos-0.1 version: "0.1" platform: macos - build: name: build-macos-0.2 version: "0.2" platform: macos - build: name: build-macos-0.3 version: "0.3" platform: macos - build: name: build-windows-0.1 version: "0.1" platform: windows - ... Excluding sets of parameters from a matrix Sometimes you may wish to run a job with every combination of arguments except some value or values. You can use an exclude stanza to achieve this: workflows: workflow: jobs: - build: matrix: parameters: a: [1, 2, 3] b: [4, 5, 6] exclude: - a: 3 b: 5 The matrix above would expand into 8 jobs: every combination of the parameters a and b , excluding {a: 3, b: 5} Dependencies and matrix jobs To require an entire matrix (every job within the matrix), use its alias . The alias defaults to the name of the job being invoked. workflows: workflow: jobs: - deploy: matrix: parameters: version: ["0.1", "0.2"] - another-job: requires: - deploy This means that another-job will require both deploy jobs in the matrix to finish before it runs. Matrix jobs expose their parameter values via << matrix.* >> which can be used to generate more complex workflows. For example, here is a deploy matrix where each job waits for its respective build job in another matrix. workflows: workflow: jobs: - build: name: build-v<< matrix.version >> matrix: parameters: version: ["0.1", "0.2"] - deploy: name: deploy-v<< matrix.version >> matrix: parameters: version: ["0.1", "0.2"] requires: - build-v<< matrix.version >> This workflow will expand to: workflows: workflow: jobs: - build: name: build-v0.1 version: "0.1" - build: name: build-v0.2 version: "0.2" - deploy: name: deploy-v0.1 version: "0.1" requires: - build-v0.1 - deploy: name: deploy-v0.2 version: "0.2" requires: - build-v0.2 pre-steps and post-steps Pre-steps and post-steps are supported in version: 2.1 configuration Every job invocation in a workflow may optionally accept two special arguments: pre-steps and post-steps . Steps under pre-steps are executed before any of the other steps in the job. The steps under post-steps are executed after all of the other steps. Pre and post steps allow you to execute steps in a given job without modifying the job. Pre and post steps are useful, for example, to run custom setup steps before job execution. version: 2.1 jobs: bar: machine: image: ubuntu-2004:2024.05.1 steps: - checkout - run: command: echo "building" - run: command: echo "testing" workflows: build: jobs: - bar: pre-steps: # steps to run before steps defined in the job bar - run: command: echo "install custom dependency" post-steps: # steps to run after steps defined in the job bar - run: command: echo "upload artifact to s3" Logic statements Certain dynamic configuration features accept logic statements as arguments. Logic statements are evaluated to boolean values at configuration compilation time, that is, before the workflow is run. The group of logic statements includes: Type Arguments true if Example YAML literal None is truthy true / 42 / "a string" YAML alias None resolves to a truthy value *my-alias Pipeline Value None resolves to a truthy value << pipeline.git.branch >> Pipeline Parameter None resolves to a truthy value << pipeline.parameters.my-parameter >> and N logic statements all arguments are truthy and: [ true, true, false ] or N logic statements any argument is truthy or: [ false, true, false ] not 1 logic statement the argument is not truthy not: true equal N values all arguments evaluate to equal values equal: [ 42, << pipeline.number >>] matches pattern and value value matches the pattern matches: { pattern: "^feature-.$", value: << pipeline.git.branch >> }+ The following logic values are considered falsy: false  0 NaN empty strings ("") statements with no arguments All other values are truthy. Also note that using logic with an empty list will cause a validation error. Logic statements always evaluate to a boolean value at the top level, and coerce as necessary. They can be nested in an arbitrary fashion, according to their argument specifications, and to a maximum depth of 100 levels. matches uses Java regular expressions for its pattern . A full match pattern must be provided, prefix matching is not an option. Though, it is recommended to enclose a pattern in ^ and $ to avoid accidental partial matches. When using logic statements at the workflow level, do not include the condition: key (the condition key is only needed for job level logic statements). Example: workflows: my-workflow: when: or: - equal: [ main, << pipeline.git.branch >> ] - equal: [ staging, << pipeline.git.branch >> ] Logic statement examples You can find usage examples on the "Orchestration cookbook" page. Example full configuration Using Docker? Authenticating Docker pulls from image registries is recommended when using the Docker execution environment. Authenticated pulls allow access to private Docker images, and may also grant higher rate limits, depending on your registry provider. For further information see Using Docker authenticated pulls . version: 2.1 jobs: build: docker: - image: ubuntu:23.04 - image: mongo:6.0.14 command: [mongod, --smallfiles] - image: postgres:14.12 # some containers require setting environment variables environment: POSTGRES_USER: user - image: redis@sha256:54057dd7e125ca41afe526a877e8bd35ec2cdd33b9217e022ed37bdcf7d09673 - image: rabbitmq:3.12.12 environment: TEST_REPORTS: /tmp/test-reports working_directory: ~/my-project steps: - checkout - run: command: echo 127.0.0.1 devhost | sudo tee -a /etc/hosts # Create Postgres users and database # Note the YAML heredoc '|' for nicer formatting - run: | sudo -u root createuser -h localhost --superuser ubuntu && sudo createdb -h localhost test_db - restore_cache: keys: - v1-my-project-{{ checksum "project.clj" }} - v1-my-project- - run: environment: SSH_TARGET: "localhost" TEST_ENV: "linux" command: | set -xu mkdir -p ${TEST_REPORTS} run-tests.sh cp out/tests/*.xml ${TEST_REPORTS} - run: | set -xu mkdir -p /tmp/artifacts create_jars.sh << pipeline.number >> cp *.jar /tmp/artifacts - save_cache: key: v1-my-project-{{ checksum "project.clj" }} paths: - ~/.m2 # Save artifacts - store_artifacts: path: /tmp/artifacts destination: build # Upload test results - store_test_results: path: /tmp/test-reports deploy-stage: docker: - image: ubuntu:23.04 working_directory: /tmp/my-project steps: - run: name: Deploy if tests pass and branch is Staging command: ansible-playbook site.yml -i staging deploy-prod: docker: - image: ubuntu:23.04 working_directory: /tmp/my-project steps: - run: name: Deploy if tests pass and branch is Main command: ansible-playbook site.yml -i production workflows: build-deploy: jobs: - build: filters: branches: ignore: - develop - /feature-.*/ - deploy-stage: requires: - build filters: branches: only: staging - deploy-prod: requires: - build filters: branches: only: main