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Concurrency control

Concurrency control prevents multiple workflow instances from running simultaneously, protecting shared resources and preventing conflicts.

Schema​

See Schema Reference for the complete #Concurrency definition.

Fields​

group (required)​

Concurrency group identifier. Workflows with the same group cannot run concurrently.

Type: string (non-empty)

Supports expressions: Yes

Example:

concurrency:
  group: production-deploy

With expressions:

concurrency:
  group: train-${{ .inputs.model_type }}

cancel_in_progress (optional)​

Controls behavior when a new workflow arrives while another is running in the same group.

Type: bool

Default: false

Values:

  • true: Cancel running workflow, start new one immediately.
  • false: Queue new workflow (max 1 running + 1 pending, newer replaces pending).

Example:

concurrency:
  group: model-training
  cancel_in_progress: true

Behavior​

Queue Mode (cancel_in_progress: false)​

  • Maximum: 1 running + 1 pending workflow.
  • New arrivals replace pending workflow (keeps newest).
  • When running completes, pending starts.

Cancel Mode (cancel_in_progress: true)​

  • New workflow cancels running workflow.
  • No queue — newest always runs.

Examples​

Model Deployment​

Ensure only one model deployment at a time:

id: deploy-model

concurrency:
  group: production-deploy

jobs:
  deploy:
    steps:
      - run: python deploy_model.py --env production

Per-Model Training​

Allow concurrent training of different models, but serialize same-model training:

id: train-model

inputs:
  model_type:
    type: string
    required: true

concurrency:
  group: train-${{ .inputs.model_type }}

jobs:
  train:
    steps:
      - run: python train.py --model ${{ .inputs.model_type }}

Experiment with Cancel​

For experiments where only the latest hyperparameters matter:

id: hyperparameter-tuning

inputs:
  experiment_id:
    type: string

concurrency:
  group: experiment-${{ .inputs.experiment_id }}
  cancel_in_progress: true

jobs:
  tune:
    steps:
      - run: python tune.py --experiment ${{ .inputs.experiment_id }}

Interaction with Other Features​

cancel_on_failure: Concurrency cancellations have state cancelled (not failed), so they don't trigger cancel_on_failure in other workflows.

Expressions: Concurrency groups support same expression contexts as other fields (.inputs, .secrets, .env).

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