Azure DevOps管道中并行作业数量的限制

Question

我们的团队正在使用YAML模式创建一个Azure DevOps管道来运行我们的测试脚本，运行相同测试脚本的多个迭代。如何告诉作业运行相同的测试8次，但限制并行运行的最大测试数3?

Azure DevOps YAML模式引用展示了一种限制运行矩阵并行运行次数的方法：

job: Build
strategy:
  maxParallel: 2
  matrix:
    Python35:
      PYTHON_VERSION: '3.5'
    Python36:
      PYTHON_VERSION: '3.6'

但试着像

job: Build
strategy:
  maxParallel: 2
  parallel: 8

抛出一个错误，表示并行是一个意外的标识符。

Answer 1

这是有点晚，但仍然希望为其他人提供一个答案。如果您查看以下文档：https://learn.microsoft.com/en-us/azure/devops/pipelines/process/phases?view=azure-devops&tabs=yaml#define-a-single-job

它谈到了YAML工作的完整规范：

- job: string  # name of the job, A-Z, a-z, 0-9, and underscore
  displayName: string  # friendly name to display in the UI
  dependsOn: string | [ string ]
  condition: string
  strategy:
    parallel: # parallel strategy
    matrix: # matrix strategy
    maxParallel: number # maximum number simultaneous matrix legs to run
    # note: `parallel` and `matrix` are mutually exclusive
    # you may specify one or the other; including both is an error
    # `maxParallel` is only valid with `matrix`
  continueOnError: boolean  # 'true' if future jobs should run even if this job fails; defaults to 'false'
  pool: pool # agent pool
  workspace:
    clean: outputs | resources | all # what to clean up before the job runs
  container: containerReference # container to run this job inside
  timeoutInMinutes: number # how long to run the job before automatically cancelling
  cancelTimeoutInMinutes: number # how much time to give 'run always even if cancelled tasks' before killing them
  variables: { string: string } | [ variable | variableReference ] 
  steps: [ script | bash | pwsh | powershell | checkout | task | templateReference ]
  services: { string: string | container } # container resources to run as a service container

它声明了'parallel' and 'matrix' are mutually exclusive。这意味着您只能在矩阵策略中使用maxParallel。没有矩阵，你必须使用“并行”。

Answer 2

我觉得应该是这样的：

jobs:
- job: xxx   
  strategy:
    parallel: 8 # parallel strategy, see below
    maxParallel: 3 # maximum number of agents to simultaneously run copies of this job on