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Use when automating Azure DevOps operations — az devops CLI, REST API calls, PAT management, service principal automation, webhooks, and scripting repeatable ADO administrative tasks.
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SOC 職業分類に基づく
| name | ado-api-cli |
| description | Use when automating Azure DevOps operations — az devops CLI, REST API calls, PAT management, service principal automation, webhooks, and scripting repeatable ADO administrative tasks. |
# Install
pip install azure-cli
az extension add --name azure-devops
# Configure defaults
az devops configure \
--defaults organization=https://dev.azure.com/MyOrg project=MyProject
# Authenticate
export AZURE_DEVOPS_EXT_PAT="your-pat-token"
# OR: az login (uses AAD auth)
Create PAT (via UI): User Settings → Personal Access Tokens → New Token
PAT scope best practices:
| Scope | Use case |
|---|---|
| Code (Read) | Clone repos in CI |
| Build (Read & Execute) | Trigger pipelines |
| Work Items (Read & Write) | Update work items from scripts |
| Full Access | Admin scripts — minimize lifetime (7 days) |
# List PATs via API
curl -u ":$PAT" \
"https://vssps.dev.azure.com/MyOrg/_apis/tokens/pats?api-version=7.1-preview.1"
PAT security:
# Base URL pattern
BASE="https://dev.azure.com/MyOrg/MyProject/_apis"
AUTH=$(echo -n ":$PAT" | base64)
# List projects
curl -H "Authorization: Basic $AUTH" \
"https://dev.azure.com/MyOrg/_apis/projects?api-version=7.1"
# Create work item
curl -X POST \
-H "Authorization: Basic $AUTH" \
-H "Content-Type: application/json-patch+json" \
"https://dev.azure.com/MyOrg/MyProject/_apis/wit/workitems/\$User%20Story?api-version=7.1" \
-d '[{"op":"add","path":"/fields/System.Title","value":"New feature"}]'
# Get pipeline runs
curl -H "Authorization: Basic $AUTH" \
"$BASE/_apis/pipelines/1/runs?api-version=7.1"
# Create webhook for pull request events
az devops service-endpoint webhooks create \
--name "MyWebhook" \
--url "https://myapp.com/webhook" \
--project MyProject
Common service hook events:
git.push — code pushed to branchgit.pullrequest.created — PR openedbuild.complete — pipeline finishedworkitem.created / workitem.updated — work item changesfrom azure.devops.connection import Connection
from msrest.authentication import BasicAuthentication
credentials = BasicAuthentication('', PAT)
connection = Connection(base_url=f'https://dev.azure.com/{ORG}', creds=credentials)
# Get clients
wit_client = connection.clients.get_work_item_tracking_client()
build_client = connection.clients.get_build_client()
# Create work item programmatically
from azure.devops.v7_1.work_item_tracking.models import JsonPatchOperation
patch = [JsonPatchOperation(op='add', path='/fields/System.Title', value='Bug: Login fails')]
wit_client.create_work_item(patch, project='MyProject', type='Bug')
Install: pip install azure-devops
api-version (e.g., 7.1); avoid api-version=preview in productionwit_client.query_by_wiql().azuredevops/ folder in repoado-organization — automate project/team provisioningado-pipelines-ops — automate service connection and variable group creationado-security-policies — automate security group membership and policy configurationUse when conducting quality audits — reviewing process compliance, identifying gaps between defined process and actual practice, conducting structured inspections (code review audits, test quality reviews), and producing audit reports with remediation plans.
Use when managing quality risk — identifying quality risks in a product or release, applying risk-based testing prioritization, creating risk mitigation plans, and communicating quality risk to stakeholders for go/no-go decisions.
Use when designing or implementing test automation — choosing the right automation framework (Playwright, pytest, JUnit), Page Object Model, selector strategies, test isolation, managing flaky tests, and CI integration.
Use when managing defects — writing effective bug reports, applying severity/priority matrix, tracking defect lifecycle, conducting root cause analysis, and measuring defect metrics for process improvement.
Use when measuring and reporting QA quality — defect escape rate, test coverage analysis, flaky test rate, mean time to detect, shift-left metrics, and building quality dashboards for stakeholders.
Use when managing test data — designing test data strategies, using factories and builders, creating fixtures, generating synthetic data, masking PII for testing, and managing test database state.