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.openpublishing.redirection.azure-monitor.json

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.openpublishing.redirection.json

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"redirect_url": "/visualstudio/containers/overview-local-process-kubernetes",
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"redirect_document_id": false
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},
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{
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"source_path_from_root": "/articles/docker/index.yml",
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"redirect_url": "/dotnet/architecture/microservices/container-docker-introduction/docker-defined",
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"redirect_document_id": false
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},
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{
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"source_path_from_root": "/articles/vs-azure-tools-docker-edit-and-refresh.md",
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"redirect_url": "/visualstudio/docker/vs-azure-tools-docker-edit-and-refresh",

articles/active-directory-b2c/partner-akamai-secure-hybrid-access.md

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```xml
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<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
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<TrustFrameworkPolicy
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xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
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xmlns:xsd="http://www.w3.org/2001/XMLSchema"
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xmlns="http://schemas.microsoft.com/online/cpim/schemas/2013/06"
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PolicySchemaVersion="0.3.0.0"
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TenantId="fabrikam.onmicrosoft.com"
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PolicyId="B2C_1A_signup_signin_saml"
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PublicPolicyUri="http://fabrikam.onmicrosoft.com/B2C_1A_signup_signin_saml">
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<BasePolicy>
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<TenantId>fabrikam.onmicrosoft.com</TenantId>
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<PolicyId>B2C_1A_TrustFrameworkExtensions</PolicyId>
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</BasePolicy>
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<UserJourneys>
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<UserJourney Id="SignUpOrSignIn">
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<OrchestrationSteps>
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<OrchestrationStep Order="7" Type="SendClaims" CpimIssuerTechnicalProfileReferenceId="AkamaiSaml2AssertionIssuer"/>
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</OrchestrationSteps>
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</UserJourney>
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</UserJourneys>
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<RelyingParty>
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<DefaultUserJourney ReferenceId="SignUpOrSignIn" />
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<TechnicalProfile Id="PolicyProfile">
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<DisplayName>PolicyProfile</DisplayName>
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<Protocol Name="SAML2"/>
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<OutputClaims>
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<OutputClaim ClaimTypeReferenceId="displayName" />
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<OutputClaim ClaimTypeReferenceId="givenName" />
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<OutputClaim ClaimTypeReferenceId="surname" />
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<OutputClaim ClaimTypeReferenceId="email" DefaultValue="" />
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<OutputClaim ClaimTypeReferenceId="identityProvider" DefaultValue="" />
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<OutputClaim ClaimTypeReferenceId="objectId" PartnerClaimType="objectId"/>
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</OutputClaims>
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<SubjectNamingInfo ClaimType="objectId" ExcludeAsClaim="true"/>
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</TechnicalProfile>
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</RelyingParty>
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</TrustFrameworkPolicy>
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```
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>[!NOTE]
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>You can follow this same process to implement other types of flows, for example, sign-in, password reset, or profile editing flows.
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xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
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xmlns:xsd="http://www.w3.org/2001/XMLSchema"
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xmlns="http://schemas.microsoft.com/online/cpim/schemas/2013/06"
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PolicySchemaVersion="0.3.0.0"
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TenantId="fabrikam.onmicrosoft.com"
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PolicyId="B2C_1A_signup_signin_saml"
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PublicPolicyUri="http://fabrikam.onmicrosoft.com/B2C_1A_signup_signin_saml">
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<BasePolicy>
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<TenantId>fabrikam.onmicrosoft.com</TenantId>
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<PolicyId>B2C_1A_TrustFrameworkExtensions</PolicyId>
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</BasePolicy>
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<UserJourneys>
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<UserJourney Id="SignUpOrSignIn">
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<OrchestrationSteps>
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<OrchestrationStep Order="7" Type="SendClaims" CpimIssuerTechnicalProfileReferenceId="AkamaiSaml2AssertionIssuer"/>
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</OrchestrationSteps>
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</UserJourney>
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</UserJourneys>
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<RelyingParty>
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<DefaultUserJourney ReferenceId="SignUpOrSignIn" />
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<TechnicalProfile Id="PolicyProfile">
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<DisplayName>PolicyProfile</DisplayName>
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<Protocol Name="SAML2"/>
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<OutputClaims>
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<OutputClaim ClaimTypeReferenceId="displayName" />
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<OutputClaim ClaimTypeReferenceId="givenName" />
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<OutputClaim ClaimTypeReferenceId="surname" />
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<OutputClaim ClaimTypeReferenceId="email" DefaultValue="" />
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<OutputClaim ClaimTypeReferenceId="identityProvider" DefaultValue="" />
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<OutputClaim ClaimTypeReferenceId="objectId" PartnerClaimType="objectId"/>
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</OutputClaims>
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<SubjectNamingInfo ClaimType="objectId" ExcludeAsClaim="true"/>
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</TechnicalProfile>
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</RelyingParty>
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</TrustFrameworkPolicy>
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```
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>[!NOTE]
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>You can follow this same process to implement other types of flows, for example, sign-in, password reset, or profile editing flows.
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### Step 4 - Upload your policy
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articles/ai-services/cognitive-services-virtual-networks.md

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```azurepowershell-interactive
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$parameters = @{
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"ResourceGroupName" = "myresourcegroup"
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"Name" = "myaccount"
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}
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(Get-AzCognitiveServicesAccountNetworkRuleSet @parameters).IPRules
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```
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"ResourceGroupName" = "myresourcegroup"
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"Name" = "myaccount"
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}
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(Get-AzCognitiveServicesAccountNetworkRuleSet @parameters).IPRules
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```
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1. Add a network rule for an individual IP address.
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articles/ai-services/containers/azure-kubernetes-recipe.md

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1. Get your container registry ID.
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```azurecli-interactive
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az acr show --resource-group cogserv-container-rg --name pattyregistry --query "id" --o table
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az acr show --resource-group cogserv-container-rg --name pattyregistry --query "id" --output table
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```
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Save the output for the scope parameter value, `<acrId>`, in the next step. It looks like:

articles/ai-services/document-intelligence/concept-analyze-document-response.md

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* Currency: Currency amount with optional currency unit. A value, for example: ```InvoiceTotal: $123.45```
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```json
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{
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"amount": 123.45,
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"currencySymbol": "$"
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}
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```
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```json
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{
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"amount": 123.45,
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"currencySymbol": "$"
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}
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```
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* Address: Parsed address. For example: ```ShipToAddress: 123 Main St., Redmond, WA 98052```
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```json
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{
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"poBox": "PO Box 12",
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"houseNumber": "123",
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"streetName": "Main St.",
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"city": "Redmond",
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"state": "WA",
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"postalCode": "98052",
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"countryRegion": "USA",
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"streetAddress": "123 Main St."
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}
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```
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```json
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{
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"poBox": "PO Box 12",
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"houseNumber": "123",
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"streetName": "Main St.",
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"city": "Redmond",
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"state": "WA",
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"postalCode": "98052",
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"countryRegion": "USA",
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"streetAddress": "123 Main St."
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}
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```
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#### Structured types
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* Array: List of fields of the same type
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```json
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"Items": {
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"type": "array",
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"valueArray": [
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]
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}
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```
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```json
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"Items": {
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"type": "array",
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"valueArray": [
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]
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}
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```
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* Object: Named list of subfields of potentially different types
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"InvoiceTotal": {
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```json
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"InvoiceTotal": {
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"type": "currency",
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"valueCurrency": {
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"currencySymbol": "$",
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"length": 7
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}
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]
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}
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```
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}
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```
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## Next steps
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articles/ai-services/language-service/question-answering/concepts/azure-resources.md

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---
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title: Azure resources - question answering
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title: Azure resources - custom question answering
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description: Question answering uses several Azure sources, each with a different purpose. Understanding how they are used individually allows you to plan for and select the correct pricing tier or know when to change your pricing tier. Understanding how they are used in combination allows you to find and fix problems when they occur.
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ms.service: azure-ai-language
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ms.topic: conceptual
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ms.custom: language-service-question-answering
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---
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# Azure resources for question answering
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# Azure resources for custom question answering
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Question answering uses several Azure sources, each with a different purpose. Understanding how they are used individually allows you to plan for and select the correct pricing tier or know when to change your pricing tier. Understanding how resources are used _in combination_ allows you to find and fix problems when they occur.
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Custom question answering uses several Azure sources, each with a different purpose. Understanding how they are used individually allows you to plan for and select the correct pricing tier or know when to change your pricing tier. Understanding how resources are used _in combination_ allows you to find and fix problems when they occur.
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## Resource planning
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> [!TIP]
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> "Knowledge base" and "project" are equivalent terms in question answering and can be used interchangeably.
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> "Knowledge base" and "project" are equivalent terms in custom question answering and can be used interchangeably.
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When you first develop a project, in the prototype phase, it is common to have a single resource for both testing and production.
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* **The throughput you need**:
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* The throughput for question answering is currently capped at 10 text records per second for both management APIs and prediction APIs.
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* The throughput for custom question answering is currently capped at 10 text records per second for both management APIs and prediction APIs.
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* This should also influence your **Azure AI Search** SKU selection, see more details [here](../../../../search/search-sku-tier.md). Additionally, you may need to adjust Azure AI Search [capacity](../../../../search/search-capacity-planning.md) with replicas.
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For example, if your tier has 15 allowed indexes, you can publish 14 projects of the same language (one index per published project). The 15th index is used for all the projects for authoring and testing. If you choose to have projects in different languages, then you can only publish seven projects.
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* **Number of documents as sources**: There are no limits to the number of documents you can add as sources in question answering.
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* **Number of documents as sources**: There are no limits to the number of documents you can add as sources in custom question answering.
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The following table gives you some high-level guidelines.
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## Recommended settings
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The throughput for question answering is currently capped at 10 text records per second for both management APIs and prediction APIs. To target 10 text records per second for your service, we recommend the S1 (one instance) SKU of Azure AI Search.
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The throughput for custom question answering is currently capped at 10 text records per second for both management APIs and prediction APIs. To target 10 text records per second for your service, we recommend the S1 (one instance) SKU of Azure AI Search.
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## Keys in question answering
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## Keys in custom question answering
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Your custom question answering feature deals with two kinds of keys: **authoring keys** and **Azure AI Search keys** used to access the service in the customer’s subscription.
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|Name|Location|Purpose|
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|--|--|--|
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|Authoring/Subscription key|[Azure portal](https://azure.microsoft.com/free/cognitive-services/)|These keys are used to access the Language service APIs). These APIs let you edit the questions and answers in your project, and publish your project. These keys are created when you create a new resource.<br><br>Find these keys on the **Azure AI services** resource on the **Keys and Endpoint** page.|
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|Azure AI Search Admin Key|[Azure portal](../../../../search/search-security-api-keys.md)|These keys are used to communicate with the Azure AI Search service deployed in the user’s Azure subscription. When you associate an Azure AI Search resource with the custom question answering feature, the admin key is automatically passed to question answering. <br><br>You can find these keys on the **Azure AI Search** resource on the **Keys** page.|
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|Azure AI Search Admin Key|[Azure portal](../../../../search/search-security-api-keys.md)|These keys are used to communicate with the Azure AI Search service deployed in the user’s Azure subscription. When you associate an Azure AI Search resource with the custom question answering feature, the admin key is automatically passed to custom question answering. <br><br>You can find these keys on the **Azure AI Search** resource on the **Keys** page.|
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### Find authoring keys in the Azure portal
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> [!div class="mx-imgBorder"]
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> ![Screenshot of question answering resource list.](../../../qnamaker/media/qnamaker-how-to-setup-service/resources-created-question-answering.png)
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> ![Screenshot of custom question answering resource list.](../../../qnamaker/media/qnamaker-how-to-setup-service/resources-created-question-answering.png)
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## Resource purposes
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Each Azure resource created with Custom question answering feature has a specific purpose:
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Each Azure resource created with custom question answering feature has a specific purpose:
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* Language resource (Also referred to as a Text Analytics resource depending on the context of where you are evaluating the resource.)
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* Azure AI Search resource
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## Next steps
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* Learn about the question answering [projects](../How-To/manage-knowledge-base.md)
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* Learn about the custom question answering [projects](../How-To/manage-knowledge-base.md)

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