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Designing and Implementing Microsoft DevOps Solutions
Course Description
Overview
This exam measures your ability to accomplish the following technical tasks: configure processes and communications; design and implement source control; design and implement build and release pipelines; develop a security and compliance plan; and implement an instrumentation strategy.Passing score: 700
Objectives
Audience
Prerequisites
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Must have experience with administering and developing in Azure, with strong skills in at least one of these areas. They should be familiar with both Azure DevOps and GitHub.
Topics
- 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 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 crossrepository 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
- 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
- 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 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
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