Objective domain: skills the exam measures

Syllabus

Skills measured
  • Configure processes and communications (10–15%)
  • Design and implement source control (15–20%)
  • Design and implement build and release pipelines (40–45%)
  • Develop a security and compliance plan (10–15%)
  • Implement an instrumentation strategy (10–15%)

Configure activity traceability and flow of work

  • Plan and implement a structure for the flow of work and feedback cycles
  • Identify appropriate metrics related to flow of work, such as cycle times, time to recovery, and lead time
  • Integrate pipelines with work item tracking tools, such as Azure DevOps and GitHub
  • Implement traceability policies decided by development
  • Integrate a repository with Azure Boards
  • Communicate actionable information by using custom dashboards in Azure DevOps
  • Document a project by using tools, such as wikis and process diagrams
  • Configure release documentation, including release notes and API documentation
  • Automate creation of documentation from Git history
  • Configure notifications by using webhooks

Design and implement a source control strategy

  • Design and implement an authentication strategy
  • Design a strategy for managing large files, including Git LFS and git-fat
  • Design a strategy for scaling and optimizing a Git repository, including Scalar and cross-repository sharing
  • Implement workflow hooks
  • Design a branch strategy, including trunk-based, feature branch, and release branch
  • Design and implement a pull request workflow by using branch policies and branch protections
  • Implement branch merging restrictions by using branch policies and branch protections
  • Integrate GitHub repositories with Azure Pipelines, one of the services in Azure DevOps
  • Configure permissions in the source control repository
  • Configure tags to organize the source control repository
  • Recover data by using Git commands
  • Purge data from source control

Design and implement pipeline automation

  • Integrate pipelines with external tools, including dependency scanning, security scanning, and code coverage
  • Design and implement quality and release gates, including security and governance
  • Design integration of automated tests into a pipeline
  • Design and implement a comprehensive testing strategy
  • Implement orchestration of tools, such as GitHub Actions and Azure Pipelines
  • Design a package management implementation that uses Azure Artifacts, GitHub Packages, NuGet, and npm
  • Design and implement package feeds, including upstream sources
  • Design and implement a dependency versioning strategy for code assets and packages, including semantic versioning and date-based
  • Design and implement a versioning strategy for pipeline artifacts
  • Select a deployment automation solution, including GitHub Actions and Azure Pipelines
  • Design and implement an agent infrastructure, including cost, tool selection, licenses, connectivity, and maintainability
  • Develop and implement pipeline trigger rules
  • Develop pipelines, including classic and YAML
  • Design and implement a strategy for job execution order, including parallelism and multi-stage
  • Develop complex pipeline scenarios, such as containerized agents and hybrid
  • Configure and manage self-hosted agents, including virtual machine (VM) templates and containerization
  • Create reusable pipeline elements, including YAML templates, task groups, variables, and variable groups
  • Design and implement checks and approvals by using YAML environments
  • Design a deployment strategy, including blue/green, canary, ring, progressive exposure, feature flags, and A/B testing
  • Design a pipeline to ensure reliable order of dependency deployments
  • Plan for minimizing downtime during deployments by using VIP swap, load balancer, and rolling deployments
  • Design a hotfix path plan for responding to high-priority code fixes
  • Implement load balancing for deployment, including Azure Traffic Manager and the Web Apps feature of Azure App Service 
  • Implement feature flags by using Azure App Configuration Feature Manager
  • Implement application deployment by using containers, binary, and scripts
  • Recommend a configuration management technology for application infrastructure
  • Implement a configuration management strategy for application infrastructure, including IaC
  • Define an IaC strategy, including source control and automation of testing and deployment
  • Design and implement desired state configuration for environments, including Azure Automation State Configuration, Azure Resource Manager, Bicep, and Azure Policy guest configuration
  • Monitor pipeline health, including failure rate, duration, and flaky tests
  • Optimize pipelines for cost, time, performance, and reliability
  • Analyze pipeline load to determine agent configuration and capacity
  • Design and implement a retention strategy for pipeline artifacts and dependencies

Design and implement a strategy for managing sensitive information in automation

  • Implement and manage service connections
  • Implement and manage personal access tokens
  • Implement and manage secrets, keys, and certificates by using Azure Key Vault, GitHub secrets, and Azure Pipelines secrets
  • Design and implement a strategy for managing sensitive files during deployment
  • Design pipelines to prevent leakage of sensitive information
  • Automate analysis of source code by using GitHub code scanning, GitHub secrets scanning, pipeline-based scans,and SonarQube
  • Automate security scanning, including container scanning and OWASP ZAP
  • Automate analysis of licensing, vulnerabilities, and versioning of open-source components by using WhiteSource Bolt and GitHub Dependency Scanning

 

  • Configure and integrate monitoring by using Azure Monitor
  • Configure and integrate with monitoring tools, such as Azure Monitor and Application Insights
  • Manage access control to the monitoring platform
  • Configure alerts for pipeline events
  • Inspect distributed tracing by using Application Insights
  • Inspect application performance indicators
  • Inspect infrastructure performance indicators, including CPU, memory, disk, and network
  • Identify and monitor metrics for business value
  • Analyze usage metrics by using Application Insight
  • Interrogate logs using basic Kusto Query Language (KQL) queries