Customizing azd Parameters

You can customize the deployment by setting azd environment variables before running azd up. These values are resolved into infra/main.parameters.json at provision time.

How to Set a Parameter

azd env set <PARAMETER_NAME> <value>

After setting parameters, run azd up (or azd provision) to apply them.

Available Parameters

Parameter	azd Environment Variable	Default	Description
environmentName	AZURE_ENV_NAME	(prompted)	Name of the environment; used to derive resource names (3-16 chars, alphanumeric).
location	AZURE_LOCATION	(prompted)	Primary Azure region for infrastructure resources.
contentUnderstandingLocation	AZURE_CU_LOCATION	swedencentral	Region for the Azure AI Content Understanding resource.
azureAdTenantId	AZURE_AD_TENANT_ID	(empty)	Microsoft Entra tenant ID for App Service authentication.
azureAdClientId	AZURE_AD_CLIENT_ID	(empty)	App registration client ID for App Service authentication.
useExistingAiProject	USE_EXISTING_AI_PROJECT	false	Set to true to reuse an existing Azure AI Foundry project.
existingAiFoundryServiceName	EXISTING_AI_FOUNDRY_SERVICE_NAME	(empty)	Name of an existing AI Foundry service to reuse.
existingAiFoundryProjectName	EXISTING_AI_FOUNDRY_PROJECT_NAME	(empty)	Name of an existing AI Foundry project to reuse.
existingAiFoundryEndpoint	EXISTING_AI_FOUNDRY_ENDPOINT	(empty)	Endpoint of an existing AI Foundry project to reuse.
existingAiSearchConnectionName	EXISTING_AI_SEARCH_CONNECTION_NAME	(empty)	Name of an existing Azure AI Search connection to reuse.
adminApiKey	ADMIN_API_KEY	(empty)	Optional admin API key for privileged operations.
deploymentFlavor	DEPLOYMENT_FLAVOR	bicep	Infrastructure variant: bicep, avm, or avm-waf. See Deployment Flavor & Production (WAF) Parameters.
azureAiServiceLocation	AZURE_ENV_AI_SERVICE_LOCATION	(location)	Region for the Azure AI (OpenAI) service.
appServicePlanSku	AZURE_ENV_APP_SERVICE_PLAN_SKU	B3	App Service Plan SKU for the backend and frontend web apps.
containerRegistryName	AZURE_ENV_CONTAINER_REGISTRY_NAME	(generated)	Name of an existing Azure Container Registry to reuse (leave empty to create one).
backendContainerImageTag / frontendContainerImageTag	AZURE_ENV_IMAGE_TAG	latest	Container image tag to deploy.
deployCosmos	AZURE_ENV_DEPLOY_COSMOS	false	Deploy Cosmos DB alongside SQL (SQL is the primary database; not required).
existingLogAnalyticsWorkspaceId	AZURE_ENV_EXISTING_LOG_ANALYTICS_WORKSPACE_RID	(empty)	Resource ID of an existing Log Analytics workspace to reuse.
existingFoundryProjectResourceId	AZURE_EXISTING_AIPROJECT_RESOURCE_ID	(empty)	Resource ID of an existing Azure AI Foundry project to reuse.
deployingUserPrincipalType	DEPLOYING_USER_PRINCIPAL_TYPE	User	Principal type of the deployer (User or ServicePrincipal); used for data-plane RBAC assignments.

Model Configuration

The AI model deployments are defined as parameters in infra/main.bicep with the following defaults for this solution. To change them, edit the defaults in main.bicep (they are not mapped as azd environment variables):

Bicep Parameter	Default	Description
chatDeploymentName	gpt-5.2	Azure OpenAI chat deployment (also used for insights generation). Deployed at 150k capacity on GlobalStandard.
embeddingDeploymentName	text-embedding-3-small	Azure OpenAI embedding deployment for hybrid search. Deployed at 80k capacity on GlobalStandard.
gptModelVersion	2025-12-11	Version of the chat model.
deployCosmos	false	Set to true to also deploy Cosmos DB (SQL is the primary database; not required).

Deployment Flavor & Production (WAF) Parameters

The infrastructure supports three deployment flavors, selected by the deploymentFlavor value in infra/main.parameters.json:

Flavor	Description
bicep	Default. Development / testing deployment without private networking.
avm	Azure Verified Modules without private networking.
avm-waf	Well-Architected Framework aligned: private networking, VNet, private endpoints, jumpbox VM + Bastion, and optional redundancy.

How to select a flavor: the deployment flavor is chosen by which parameters file is active — azd always reads infra/main.parameters.json. To deploy the Production (WAF) flavor, copy the WAF parameters file over the default:

Copy-Item ./infra/main.waf.parameters.json ./infra/main.parameters.json -Force

cp ./infra/main.waf.parameters.json ./infra/main.parameters.json

The WAF parameters file sets the following additional values. Flags without an azd environment variable are hard-coded in the file — edit the file directly to change them.

Parameter	azd Environment Variable	Default (WAF file)	Description
deploymentFlavor	DEPLOYMENT_FLAVOR	avm-waf	Selects the WAF infrastructure variant.
enableMonitoring	(hard-coded)	true	Application Insights + Log Analytics.
enablePrivateNetworking	(hard-coded)	true	VNet, private endpoints, jumpbox VM, and Azure Bastion.
enableScalability	(hard-coded)	true	Higher SKUs and autoscale settings.
enableRedundancy	(hard-coded)	false	Zone redundancy and Log Analytics workspace replication.
enableTelemetry	AZURE_ENV_ENABLE_TELEMETRY	true	Anonymous deployment telemetry.
vmAdminUsername	AZURE_ENV_VM_ADMIN_USERNAME	(empty)	Jumpbox admin username (fallback; login is via Entra ID + Bastion).
vmAdminPassword	AZURE_ENV_VM_ADMIN_PASSWORD	(empty)	Jumpbox admin password.
vmSize	AZURE_ENV_VM_SIZE	Standard_D2s_v5	Jumpbox VM size.

Production prerequisite: the WAF jumpbox VM enables host encryption, so the EncryptionAtHost feature must be registered on the subscription before deploying. See Choose Deployment Type for the registration commands and VM credential setup.

Examples

Deploy to Australia East with a specific environment name:

azd env set AZURE_ENV_NAME kmdev
azd env set AZURE_LOCATION australiaeast
azd up

Reuse an existing Azure AI Foundry project:

azd env set USE_EXISTING_AI_PROJECT true
azd env set EXISTING_AI_FOUNDRY_SERVICE_NAME my-foundry-service
azd env set EXISTING_AI_FOUNDRY_PROJECT_NAME my-foundry-project
azd env set EXISTING_AI_FOUNDRY_ENDPOINT https://my-foundry.services.ai.azure.com/
azd up

Set the Content Understanding region:

azd env set AZURE_CU_LOCATION swedencentral
azd up

Deploy the Production (WAF) configuration with VM credentials:

Copy-Item ./infra/main.waf.parameters.json ./infra/main.parameters.json -Force
azd env set AZURE_ENV_VM_ADMIN_USERNAME azureadmin
azd env set AZURE_ENV_VM_ADMIN_PASSWORD <strong-password>
azd up

Viewing Current Values

azd env get-values

Next Steps

Return to the Deployment Guide to continue.