Continuous Delivery Using Azure DevOps Services Training in Germany

By the end of the course, students will have had exposure and hands-on experience with the following:

• DevOps principles, benefits, and related practices
• The Three Ways: flow, feedback, and learning
• Technical excellence at scale
• Working as a team in an Azure DevOps environment
• Increasing flow through a technical value stream
• Practices and mindset of a Professional Scrum Team
• Scaled Professional Scrum (Nexus) framework
• Identifying and eliminating dependencies
• Minimizing dependencies through feature teams
• Configuring Azure DevOps for product development
• Planning work at scale: epics, features, user stories
• Product Backlog Refinement benefits and practices
• Creating a definition of “Ready”
• Types of dependencies and the related risks
• Cross-team refinement to mitigate dependencies
• Working in small batches and limiting WIP
• Using Azure Boards to plan and execute a Sprint
• Creating and abiding-by a definition of “Done”
• Reporting data via queries, charts, and widgets
• Using dashboards as information radiators
• Collaborating as a cross-functional team
• The collective ownership mindset
• Git version control primer and workflows
• Branching strategies and potential side effects
• Visualizing and managing code dependencies
• Adopting an internal open source model
• Creating fast feedback loops
• Automated testing in Visual Studio and Azure Pipelines
• Writing and running unit tests in Visual Studio
• Creating and managing Azure Pipeline builds
• Installing and configuring Azure Pipeline agents
• Queuing and monitoring automated builds
• Running automated tests as part of a build
• Collecting code coverage information
• Using Test Impact Analysis to improve performance
• Continuous Integration (CI) and CI+
• Using Azure Pipelines for deployment
• Using Microsoft Azure for DevOps
• Automated deployment to an Azure Virtual Machine
• Creating and deploying a release
• Infrastructure as Code (IaC)
• Creating and importing YAML builds
• Automatic creation of deployment environments
• Azure Resource Manager and ARM templates
• Continuous Delivery (CD) and using RM triggers
• Hypothesis-Driven Development (HDD)
• Customizing Azure DevOps to implement HDD
• Using feature flags to manage feature availability
• Telemetry and application performance management
• Using feature flags to support A/B testing
• Using LaunchDarkly and Application Insights for HDD
• Exploratory testing, testing “tours” practice
• Using the Microsoft Test and Feedback extension
• Understanding, identifying, and avoiding technical debt
• Using SonarQube to measure your technical debt
• Building a culture of learning and improvement
• Agile metrics and reporting
• Communities of Practice (COPs)
• Recording learnings in the wiki for transparency

Module 1: Increasing Flow at Scale

• The complexity of software development
• The need for empirical process control
• Increasing flow through a technical value stream
• Scrum and Professional Scrum
• The Nexus scaled Scrum framework
• Practices for organizing teams
• Establishing feature teams to minimize dependencies

Module 2: Planning and Executing at Scale

• Organizing and refining the Product Backlog
• Creating a definition of “Ready”
• Dependencies, types, and related risks
• Cross-team refinement to identify dependencies
• Planning and executing a Sprint
• Limiting work in progress (WIP)
• Working in small batches
• Creating and obeying a definition of “Done”
• Using queries, charts, and dashboards for reporting

Module 3: Sharing Code

• Working collaboratively as a team
• Collective ownership mindset
• Git version control workflow (optional)
• Branching strategies and related side effects
• Using Code Maps to visualize code dependencies
• Using Package Management to share binaries
• Adopting an internal open source model

Module 4: Integrating Continuously

• Why and how to create fast feedback loops
• The importance of automated testing
• Unit testing in Visual Studio
• Automated builds in Azure Pipelines
• Build definitions and build tasks
• Cloning and managing build definitions
• Hosted build agents and agent pools
• Running tests during an automated build
• Code coverage and regression testing
• Configuring and using Test Impact Analysis
• Continuous Integration (CI) and CI+

Module 5: Delivering Continuously

• Azure Pipelines deployment
• Release definitions, environments, and releases
• Deployment targets, IaaS, PaaS, containers
• Using Microsoft Azure for DevOps
• Configuring endpoints and deployment groups
• Automated deployment to an Azure Virtual Machine
• Installing and configuring Azure Pipelines agents
• Release tasks and phases
• Creating and deploying a release
• Infrastructure as Code
• Creating and importing YAML builds
• Automatic creation of environments
• Azure Resource Manager and ARM templates
• Release and environment triggers
• Continuous Delivery (CD)

Module 6: Empowering the Product Owner

• Build-Measure-Learn explained
• Hypothesis-Driven Development (HDD)
• Customizing Azure DevOps to implement HDD
• Feature flags overview
• Using LaunchDarkly to manage feature flags
• Telemetry and application performance management
• Application Insights for gathering telemetry
• A/B testing
• Using feature flags to support A/B testing
• Exploratory testing, testing “tours” practice
• Using the Microsoft Test and Feedback extension
• Understanding and identifying technical debt
• Using SonarQube to gauge your technical debt
• Practices for paying off technical debt

Module 7: Learning and Improving Continuously

• Building a culture of learning and improvement
• Agile metrics and reporting
• Communities of Practice (COPs)
• Lean thinking and practices to eliminate waste
• Using the wiki to build tribal knowledge