Adeptia AI Services

Purpose

The purpose of this document is to provide a detailed overview of AI Services Deployment. The document consists of a detailed process, with procedures for Infrastructure Deployment, and Configuration with AC5.x Professional.

Scope

This process covers aspects of the deployment of AI Services in the production environment and its connectivity to AC 5.x Professional.

Infrastructure Deployment in Azure

Create a “Resource Group” with required “Tags”

Create “App Service Plan” with required “Tags”

Once “App Service Plan” is created, it will show the overview as below:

Create “Web App” with the steps below:

Put name, Publish Type, Runtime Stack, Java Web Server Stack, OS and Region

Select Pricing Plan, as per recommendation from Product Team

Give reference from where the image will be pulled

Select Networking Options, keep public access as “ON” and Network Injection as “OFF”

Select “Monitoring” option as follow for Application Insight

Give the Tag

Once a Web App is created it will show like this, we can hit the URL to test the default page.

Add environment vairables in app service

Deploy through pipeline - Build Pipeline

Release Pipeline

Create “API Management Service”.

Configure API’s

Add required policy

Update backend

Create GET & PUT operation

App Reg and integration

Create new App reg

Configure certificate and secret

Add the client id in previous created application

Add JWT Token in API management

Update values according to the Application created

Create Log analytics Workspace

Create application Insight

Integrated application insight into api management

Add the required configuration to send logs to application insight

Update the inbound policy for extract unstructured data async and change the client id according to the created details

Create AKS Cluster

Configure Milvus

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

Username - root

Password- jpQfSvbKUkZG

Create new user and password to use in application

Also change the password of root user

Login using Attu loadbalancer:

Create new database - Database name should be start with underscore "_" with client key , Like "_<<Clientkey>>" where all the dash"-" needed to be replaced by underscore "_"

Here: Client key / id = The app reg client id

To onboard new clients we need to add new clients in app reg and also create the database of the same.