Azure Deployment Stacks with Bicep for Resource Lifecycle Management
Use Azure Deployment Stacks to manage resource lifecycle as a single unit with detach and delete policies, state inspection, and stack cleanup.

Lab overview
As infrastructure grows in complexity, managing the lifecycle of Azure resources — creation, updates, and cleanup — becomes a critical governance challenge. Azure Deployment Stacks provide a native solution by wrapping Bicep deployments into managed units with built-in lifecycle policies that control what happens when resources are added, removed, or the entire stack is deleted.
In this hands-on lab, you will create Azure deployment stacks from Bicep templates, update stacks to add and remove resources while observing the difference between detach and delete lifecycle behavior, inspect stack state using the Azure CLI, and perform stack deletion with full resource cleanup. By the end, you will understand how deployment stacks simplify resource lifecycle management and provide a single-command approach to deploying and tearing down infrastructure.
Objectives
Upon completing this advanced level lab, you will be able to:
- Create an Azure deployment stack from a Bicep template using the Azure CLI
- Update a deployment stack by adding and removing resources and observe detach lifecycle behavior when resources become unmanaged
- Contrast detach and delete lifecycle policies by redeploying with different action-on-unmanage settings
- Inspect deployment stack state including managed resources, configuration, and exported templates
- Delete a deployment stack with full resource cleanup using the delete-all action
Who is this lab for?
This lab is designed for:
- Cloud engineers and DevOps practitioners who need to manage resource lifecycle and governance through Infrastructure as Code
- Azure administrators looking to standardize deployment management and simplify resource cleanup across teams
- Candidates preparing for Azure certifications that cover infrastructure management and deployment strategies (AZ-104, AZ-305, AZ-400)
Verified against your live environment
An automated validation engine inspects your actual resources and configurations as you work. Completion means the task was performed — not multiple choice, real-world proficiency.
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Related reading
Environment
Every lab includes
- Real environment, pre-credentialed
- Automated checks on every step
- Isolated sandbox, auto cleanup
- AI-recommended next steps
Lab curriculum
- 01
Logging into Azure CLI
- 02
Creating a Deployment Stack from Bicep Templates
1 automated check
- 03
Updating a Deployment Stack and Observing Lifecycle Behavior
1 automated check
- 04
Inspecting Stack State and Managing Stack Deletion
1 automated check
Skills validated
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