workflow-engine

You can orchestrate multi-step Azure infrastructure deployments by defining a declarative, machine-readable workflow that manages a directed acyclic graph (DAG) of steps. This ensures dependencies are correctly linked and validated before execution.

A declarative workflow for Azure infrastructure is a machine-readable format that defines deployment steps and their dependencies. You need it when orchestrating complex, multi-step deployments that require architecture assessment, governance discovery, and parallel execution.

You validate dependencies and outputs by defining your infrastructure steps in a declarative workflow format. The workflow engine checks that dependencies and outputs are correctly defined for each step before executing the Azure deployment.

Yes, you can use Bicep or Terraform to execute the deployment steps. The workflow engine manages the directed acyclic graph (DAG) of dependencies, while requiring tools like Bicep or Terraform for the actual Azure infrastructure provisioning.

Yes, the workflow engine supports parallel execution of infrastructure steps. It manages the directed acyclic graph (DAG) to run independent steps in parallel while ensuring dependent steps execute in the correct order during Azure deployments.

The best way to define a workflow with architecture assessment and governance discovery is to declaratively specify these steps in a machine-readable format. The engine validates dependencies and orchestrates the sequence before deploying to Azure.