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Purpose
The purpose of this document is to provide a detailed This document aims to deliver a comprehensive overview of AI Services Deployment. The document consists of a detailed process, with It outlines a thorough process that includes procedures for Infrastructure Deployment , and Configuration with using AC5.x Professional.
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Scope
This process covers aspects of encompasses the deployment of AI Services in within the production environment and its connectivity to integration with AC 5.x Professional.
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Infrastructure Deployment in Azure
1. Create a “Resource Group” with required “Tags”
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Create “App Service Plan” with required “Tags”
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Once “App Service Plan” is created, it will show the overview as below:
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Create “Web App” with the steps below:
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Create “API Management Service”.
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Configure API’s
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Add required policy
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Create GET & PUT operation
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App Reg and integration
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Create new App reg
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attu: enabled: true service: type: LoadBalancer extraConfigFiles: user.yaml: |+ common: security: authorizationEnabled: true service: type: LoadBalancer minio: persistence: size: 50Gi pulsar: bookkeeper: volumes: journal: size: 50Gi ledgers: size: 50Gi kafka: persistence: size: 50Gi |
Default username and password
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To onboard new clients we need to add new clients in app reg and also create the database of the same.
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Configure AI Service
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Go to manage deployment
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Create new model deployment
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Increase the token limit to max for all
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Create Content filter
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Requested decreased restriction on open ai content filtering
Request Quota increase:
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Document Intelligence
Create document intelligence service
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Security:
API Manamagent: Only allow IP address of AC5 professional AKS cluster in api management
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Swap the prod with prod-02
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