Azure DevOps Pipeline 上没有日志记录

Question

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帖子中链接的解决方案/答案在我的情况下不起作用

更新：

是否可以添加或更改在 Azure DevOps 上执行管道的命令？

---

在Visual Studio Code本地运行我的程序，我确实得到了输出。

但是，在Azure DevOps上运行我的GitHub源分支不会产生任何输出。

我遵循了 Stack Overflow 的答案，该答案将此解决方案引用到了GitHub 问题。

我已经实现了以下内容，但 Azure 的原始日志在我的 Python logging记录中返回空白。

test_logging.py ：

import logging

filename = "my.log"

global logger
logger = logging.getLogger()
logger.setLevel(logging.INFO)
formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
open(filename, "w").close()  # empty logs
fileHandler = logging.FileHandler(filename)
fileHandler.setFormatter(formatter)
fileHandler.setLevel(logging.INFO)
logger.addHandler(fileHandler)

logger.error('TEST')

# fetch logs
with open(filename, "r") as fileHandler:
    logs = [log.rstrip() for log in fileHandler.readlines()]
open(filename, "w").close()  # empty logs
print('logs = ', logs)

>>> logs = []

host.json ：

{
  "version":  "2.0",
  "logging": {
    "fileLoggingMode": "always",
    "logLevel": {
      "default": "Debug"
    }
  } 
}

---

然后我从post尝试了这个替代host.json ：

"logging": {
    "fileLoggingMode": "debugOnly",
    "logLevel": {
        "default": "None",
        "Host.Results": "Information",
        "Function": "Information",
        "Host.Aggregator": "Information"
    },
    "applicationInsights": {
        "samplingSettings": {
            "isEnabled": false,
            "maxTelemetryItemsPerSecond": 5
        }
    }
}

azure-pipeline-ontology_tagger.yaml

# ##########
# A build run against multiple Python targets
# ##########

resources:
- repo: self

variables:
  tag: '$(Build.SourceBranchName)-$(Build.BuildNumber)'
  imageName: '$(Build.Repository.Name)-ontology_tagger'
  artifactFeed: grandproject/private-sources
  repositoryUrl: private-sources
  packageDirectory: workers/ontology_tagger

trigger:
  batch: true
  branches:
    include:
    - master
    - development
    - releases/*
  paths:
    include:
    - "workers/ontology_tagger"
    exclude:
    - "workers"
    - "*.md"
pr:
  branches:
    include:
    - master
    - development
    - releases/*
  paths:
    include:
    - "workers/ontology_tagger"
    exclude:
    - "workers"
    - "*.md"

stages:
- stage: BuildWP
  displayName: Build Workers python package
  jobs:

  - job: Build
    displayName: Build Worker python image

    pool:
      name: EKS-grandproject-dev

    steps:
    - bash: env

    - task: PipAuthenticate@0
      displayName: Authenticate with artifact feed
      inputs:
        artifactFeeds: $(artifactFeed)

    - task: TwineAuthenticate@1
      displayName: Authenticate with artifact feed
      inputs:
        artifactFeed: $(artifactFeed)

    - bash: echo "##vso[task.setvariable variable=POETRY_HTTP_BASIC_AZURE_PASSWORD;isOutput=true]$(echo $PIP_EXTRA_INDEX_URL | sed -r 's|https://(.+):(.+)@.*|\2|')"
      name: "PIPAUTH"

    - task: Bash@3
      displayName: Test worker
      inputs:
        targetType: 'inline'
        workingDirectory: '$(packageDirectory)'
        script: |
          docker build . --progress plain --pull --target test \
          --build-arg POETRY_HTTP_BASIC_AZURE_PASSWORD=${PIPAUTH_POETRY_HTTP_BASIC_AZURE_PASSWORD} \
          --build-arg ATLASSIAN_TOKEN=$(ATLASSIAN_TOKEN)
    - task: Bash@3
      displayName: Build and publish package
      inputs:
        targetType: 'inline'
        workingDirectory: '$(packageDirectory)'
        script: |
          set -e
          cp $(PYPIRC_PATH) ./
          docker build . --target package --progress plain  --build-arg REPO=$(repositoryUrl)
    - task: Bash@3
      displayName: Build docker image
      inputs:
        targetType: 'inline'
        workingDirectory: '$(packageDirectory)'
        script: |
          docker build . --tag '$(imageName):$(tag)' --progress plain --pull --target production \
          --build-arg POETRY_HTTP_BASIC_AZURE_PASSWORD=${PIPAUTH_POETRY_HTTP_BASIC_AZURE_PASSWORD} \
          --label com.azure.dev.image.build.sourceversion=$(Build.SourceVersion) \
          --label com.azure.dev.image.build.sourcebranchname=$(Build.SourceBranchName) \
          --label com.azure.dev.image.build.buildnumber=$(Build.BuildNumber)
    - task: ECRPushImage@1
      displayName: Push image with 'latest' tag
      condition: and(succeeded(),eq(variables['Build.SourceBranchName'], 'master'))
      inputs:
        awsCredentials: 'dev-azure-devops'
        regionName: 'eu-central-1'
        imageSource: 'imagename'
        sourceImageName: $(imageName)
        sourceImageTag: $(tag)
        repositoryName: $(imageName)
        pushTag: 'latest'
        autoCreateRepository: true

    - task: ECRPushImage@1
      displayName: Push image with branch name tag
      condition: and(succeeded(),ne(variables['Build.SourceBranchName'], 'merge'))
      inputs:
        awsCredentials: 'iotahoe-dev-azure-devops'
        regionName: 'eu-central-1'
        imageSource: 'imagename'
        sourceImageName: $(imageName)
        sourceImageTag: $(tag)
        repositoryName: $(imageName)
        pushTag: '$(Build.SourceBranchName)'
        autoCreateRepository: true

    - task: ECRPushImage@1
      displayName: Push image with uniq tag
      condition: and(succeeded(),ne(variables['Build.SourceBranchName'], 'merge'))
      inputs:
        awsCredentials: 'dev-azure-devops'
        regionName: 'eu-central-1'
        imageSource: 'imagename'
        sourceImageName: $(imageName)
        sourceImageTag: $(tag)
        repositoryName: $(imageName)
        pushTag: $(tag)
        autoCreateRepository: true
        outputVariable: 'ECR_PUSHED_IMAGE_NAME'

如果还有什么我应该提供的，请告诉我。

Answer 1

我认为您从根本上混淆了这里的一些内容：您提供和遵循的链接提供了有关在 Azure Functions 中设置日志记录的指导。 但是，您似乎在谈论 Azure Pipelines 中的日志记录，这是完全不同的事情。 所以只是要清楚：

Azure Pipelines 运行生成和部署作业，将 GitHub 存储库中的代码部署到 Azure Functions。 管道在 Azure Pipelines 代理中执行，可以是 Microsoft 或自托管。 如果我们假设你正在使用 Microsoft 托管代理执行管道，则不应假设这些代理具有 Azure Functions 可能具有的任何功能（也不应首先执行针对 Azure Functions 的代码）。 如果你想在你的管道中执行 python 代码，你应该首先开始查看托管代理预先安装了哪些与 python 相关的功能并从那里开始工作： https : //docs.microsoft.com/en-us/azure/ devops/pipelines/agents/hosted?view=azure-devops&tabs=yaml

如果您想记录有关管道运行的信息，您应该在手动排队管道时首先选中“启用系统诊断”选项。 要自己实现更多日志记录，请检查： https : //docs.microsoft.com/en-us/azure/devops/pipelines/scripts/logging-commands?view=azure-devops&tabs=bash

要登录 Azure Functions，您可能希望从这里开始： https : //docs.microsoft.com/en-us/azure/azure-functions/functions-monitoring ，但这与登录 Azure Pipelines 是完全不同的主题。