Migration Guide for Network File Systems

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Prerequisites

• Cognigy.AI 4.90 or later.
• The kubectl utility is installed locally on a Linux or MacOS client host. Windows client hosts aren’t supported.
• Helm v3.9 or later installed on the client host.
• Kubernetes cluster meets general Cognigy.AI prerequisites, including hardware resources.
• Runtime and IDE file shares have been deployed.

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Migration Process

1. Adjust feature flags to handle multiple NFS shares during the migration process from the old to the current NFS structure.
2. Run the migration job to copy the data from the old NFS structure into the current NFS structure.
3. Clean up the old NFS structure.

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Migration Steps

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Activate the NFS Restructuring Feature

1. In the cognigy-ai-values.yaml file, add the following sections at the root level:
   jobCopyNfs:
       # This will start the migration job automatically with the default configuration
       enabled: true
   
   migrateFS:
       # This will let the services use the new NFS shares at the same time as the old NFS shares
       enabled: true
       # This flag should be set to true after the migration finishes to use only the new NFS volumes
       finished: false
   
2. Deploy the Cognigy.AI Helm chart:
   helm registry login cognigy.azurecr.io \
       --username <your-username> \
       --password <your-password>
   
   helm upgrade --install --namespace cognigy-ai cognigy-ai oci://cognigy.azurecr.io/helm/cognigy.ai --version <Min supported version> --values cognigy-ai-values.yaml
   

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Finish Migration and Switch to New NFS Shares

1. Update the cognigy-ai-values.yaml file:
   migrateFS:
       enabled: true
       # Set this flag to true to use only the new NFS volumes
       finished: true
   
   JobCopyNfs:
       # Set this flag to false to disable the migration job
       enabled: false
   
2. Deploy the Cognigy.AI Helm chart:
   helm registry login cognigy.azurecr.io \
       --username <your-username> \
       --password <your-password>
   
   helm upgrade --install --namespace cognigy-ai cognigy-ai oci://cognigy.azurecr.io/helm/cognigy.ai --version <Min supported version> --values cognigy-ai-values.yaml
   

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Post-Migration Steps

1. In cognigy-ai-values.yaml, remove the trace of flow-modules and functions by deleting the following code:
   ## aws
   flowModules:
       persistence:
           aws:
               efs:
                   enabled: true
                   id: "fs-xx"
                   efs_csi:
                       enabled: true
   functions:
       persistence:
           aws:
               efs:
                   enabled: true
                   id: "fs-yy"
                   efs_csi:
                       enabled: true
   ## azure
   flowModules:
       persistence:
           storageClass: "flow-modules"
   functions:
       persistence:
           storageClass: "functions"
   
   .......
       flowmodules:
           enabled: true
           skuName: Premium_LRS
           lfs: false
       functions:
           enabled: true
           skuName: Premium_LRS
           lfs: false
   
2. Delete all released volumes that were related to flow-modules and functions.

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More Information

• Architecture