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  • Welcome
  • INTRODUCTION
    • What Is Aizen?
    • Aizen Platform Interfaces
    • Typical ML Workflow
    • Datasets and Features
    • Resources and GPUs
    • LLM Operations
    • Glossary
  • INSTALLATION
    • Setting Up Your Environment
      • Hardware Requirements
      • Deploying Kubernetes On Prem
      • Deploying Kubernetes on AWS
      • Deploying Kubernetes on GCP
        • GCP and S3 API Interoperability
        • Provisioning the Cloud Service Mesh
        • Installing Ingress Gateways with Istio
      • Deploying Kubernetes on Azure
        • Setting Up Azure Blob Storage
    • Installing Aizen
      • Software Requirements
      • Installing the Infrastructure Components
      • Installing the Core Components
      • Virtual Services and Gateways Command Script (GCP)
      • Helpful Deployment Commands
    • Installing Aizen Remote Components
      • Static Remote Deployment
      • Dynamic Remote Deployment
    • Installing Optional Components
      • MinIO
      • OpenLDAP
      • OpenEBS Operator
      • NGINX Ingress Controller
      • Airbyte
  • GETTING STARTED
    • Managing Users and Roles
      • Aizen Security
      • Adding Users
      • Updating Users
      • Listing Users and Roles
      • Granting or Revoking Roles
      • Deleting Users
    • Accessing the Aizen Platform
    • Using the Aizen Jupyter Console
  • MANAGING ML WORKFLOWS
    • ML Workflow
    • Configuring Data Sources
    • Configuring Data Sinks
    • Creating Training Datasets
    • Performing ML Data Analysis
    • Training an ML Model
    • Adding Real-Time Data Sources
    • Serving an ML Model
    • Training and Serving Custom ML Models
  • MANAGING LLM WORKFLOWS
    • LLM Workflow
    • Configuring Data Sources
    • Creating Training Datasets for LLMs
    • Fine-Tuning an LLM
    • Serving an LLM
    • Adding Cloud Providers
    • Configuring Vector Stores
    • Running AI Agents
  • Notebook Commands Reference
    • Notebook Commands
  • SYSTEM CONFIGURATION COMMANDS
    • License Commands
      • check license
      • install license
    • Authorization Commands
      • add users
      • alter users
      • list users
      • grant role
      • list roles
      • revoke role
      • delete users
    • Cloud Provider Commands
      • add cloudprovider
      • list cloudproviders
      • list filesystems
      • list instancetypes
      • status instance
      • list instance
      • list instances
      • delete cloudprovider
    • Project Commands
      • create project
      • alter project
      • exportconfig project
      • importconfig project
      • list projects
      • show project
      • set project
      • listconfig all
      • status all
      • stop all
      • delete project
      • shutdown aizen
    • File Commands
      • install credentials
      • list credentials
      • delete credentials
      • install preprocessor
  • MODEL BUILDING COMMANDS
    • Data Source Commands
      • configure datasource
      • describe datasource
      • listconfig datasources
      • delete datasource
    • Data Sink Commands
      • configure datasink
      • describe datasink
      • listconfig datasinks
      • alter datasink
      • start datasink
      • status datasink
      • stop datasink
      • list datasinks
      • display datasink
      • delete datasink
    • Dataset Commands
      • configure dataset
      • describe dataset
      • listconfig datasets
      • exportconfig dataset
      • importconfig dataset
      • start dataset
      • status dataset
      • stop dataset
      • list datasets
      • display dataset
      • export dataset
      • import dataset
      • delete dataset
    • Data Analysis Commands
      • loader
      • show stats
      • show datatypes
      • show data
      • show unique
      • count rows
      • count missingvalues
      • plot
      • run analysis
      • run pca
      • filter dataframe
      • list dataframes
      • set dataframe
      • save dataframe
    • Training Commands
      • configure training
      • describe training
      • listconfig trainings
      • start training
      • status training
      • list trainings
      • list tensorboard
      • start tensorboard
      • stop tensorboard
      • stop training
      • restart training
      • delete training
      • list mlflow
      • save embedding
      • list trained-models
      • list trained-model
      • export trained-model
      • import trained-model
      • delete trained-model
      • register model
      • update model
      • list registered-models
      • list registered-model
  • MODEL SERVING COMMANDS
    • Resource Commands
      • configure resource
      • describe resource
      • listconfig resources
      • alter resource
      • delete resource
    • Prediction Commands
      • configure prediction
      • describe prediction
      • listconfig predictions
      • start prediction
      • status prediction
      • test prediction
      • list predictions
      • stop prediction
      • list prediction-logs
      • display prediction-log
      • delete prediction
    • Data Report Commands
      • configure datareport
      • describe datareport
      • listconfig datareports
      • start datareport
      • list data-quality
      • list data-drift
      • list target-drift
      • status data-quality
      • display data-quality
      • status data-drift
      • display data-drift
      • status target-drift
      • display target-drift
      • delete datareport
    • Runtime Commands
      • configure runtime
      • describe runtime
      • listconfig runtimes
      • start runtime
      • status runtime
      • stop runtime
      • delete runtime
  • LLM AND EMBEDDINGS COMMANDS
    • LLM Commands
      • configure llm
      • listconfig llms
      • describe llm
      • start llm
      • status llm
      • stop llm
      • delete llm
    • Vector Store Commands
      • configure vectorstore
      • describe vectorstore
      • listconfig vectorstores
      • start vectorstore
      • status vectorstore
      • stop vectorstore
      • delete vectorstore
    • LLM Application Commands
      • configure llmapp
      • describe llmapp
      • listconfig llmapps
      • start llmapp
      • status llmapp
      • stop llmapp
      • delete llmapp
  • TROUBLESHOOTING
    • Installation Issues
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  1. INSTALLATION
  2. Installing Optional Components

MinIO

MinIO is a Kubernetes native, high-performance object store with an S3-compatible API. The MinIO operator supports deploying MinIO tenants on any Kubernetes cluster.

To install the MinIO operator, follow these steps:

  1. Add the MinIO repository to your local Helm configuration by running this Helm command:

    helm repo add minio https://operator.min.io/
    helm repo update
  2. Install the MinIO operator in your Aizen installation by running this Helm command:

    helm -n aizen-infra install aizen-minio-operator minio/operator --version 5.0.15
  3. Copy the contents below to a file named minio_values.yaml, and change the storage class name from standard to the storage class name that is defined in your Kubernetes cluster.

    Contents of minio_values.yaml:

    enabled: false
    secrets:
      name: aizen-env-configuration
      accessKey: aizen
      secretKey: aizen@123     
    tenant:
      name: aizen
      configuration:
        name: aizen-env-configuration
      pools:
        - servers: 1
          name: minio-pool
          volumesPerServer: 1
          size: 50Gi
          storageClassName: standard
      mountPath: /opt/aizen
      subPath: /data
      certificate:
        requestAutoCert: false
      prometheusOperator: false
      logging:
        anonymous: true
        json: true
        quiet: true
      prometheus:
        disabled: true
        diskCapacityGB: 1
        storageClassName: standard
      log:
        disabled: true
        db:
          volumeClaimTemplate:
            spec:
              storageClassName: standard
              accessModes: 
                - ReadWriteOnce
              resources:
                requests:
                storage: 1Gi
  4. Deploy the MinIO Tenant by running this Helm command:

    helm -n aizen-infra install aizen-tenant --values minio_values.yaml  minio/tenant --version 5.0.15
  5. Check the deployment status of all the infrastructure components, including the MinIO operator, by running this command:

    kubectl -n aizen-infra get pods

    If any of the components are not in a Running state, see Installation Issues.

Create a bucket in MinIO for MLflow (mlflow-artifacts).

  1. Run the MinIO Client (mc) as a container pod by running these commands:

    kubectl run my-mc -i --tty --image minio/mc:latest --rm --command -- bash
    mc --version
    
    mc alias set az http://minio.aizen-infra.svc.cluster.local aizen aizen@123
    mc ls az
  2. To create a bucket in MinIO for MLflow, run this command:

    mc mb az/mlflow-artifacts
    exit
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Last updated 3 months ago