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Kubeflow v1.3 Documentation
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Deploy using UI

 来源:Kubeflow 浏览 343 扫码 分享 2021-07-11 11:28:22
  • Deploy using UI
    • No longer supported

    Deploy using UI

    Instructions for using the UI to deploy Kubeflow on Google Cloud Platform (GCP)

    No longer supported

    Starting with Kubeflow v1.1.0 deploying Kubeflow via the click to deploy web application is no longer supported. Please use kustomize and kpt to deploy Kubeflow.

    Last modified 17.05.2021: (gke) Full Kubeflow Deployment guide on GKE (revision for Kubeflow 1.3) (#2686) (f50693a3)

    当前内容版权归 Kubeflow 或其关联方所有，如需对内容或内容相关联开源项目进行关注与资助，请访问 Kubeflow .
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    • Documentation
    • About
      • Introduction to Kubeflow
      • Use Cases
      • Contributing to Kubeflow
      • Community
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      • Docs
      • Style Guide for the Kubeflow Docs
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    • Getting Started
      • Kubeflow Overview
      • Installing Kubeflow
    • Components
      • Central Dashboard
        • Central Dashboard
        • Customizing menu items
        • Registration Flow
      • Notebook Servers
        • Overview of Jupyter Notebooks in Kubeflow
        • Set Up Your Notebooks
        • Create a Custom Jupyter Image
        • Submit Kubernetes Resources
        • Troubleshooting Guide for Jupyter Notebooks
      • Kubeflow Pipelines
        • Pipelines Quickstart
        • Installing Pipelines
          • Installation Options for Kubeflow Pipelines
          • Kubeflow Pipelines Standalone Deployment
          • Deploying Kubeflow Pipelines on a local cluster
        • Understanding Pipelines
          • Overview of Kubeflow Pipelines
          • Introduction to the Pipelines Interfaces
          • Concepts
            • Pipeline
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            • Run Trigger
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        • Building Pipelines with the SDK
          • Kubeflow Pipelines SDK v2
            • Introducing Kubeflow Pipelines SDK v2
            • Build a Pipeline
            • Building Components
            • Building Python Function-based Components
          • Introduction to the Pipelines SDK
          • Install the Kubeflow Pipelines SDK
          • Connecting to Kubeflow Pipelines using the SDK client
          • Build a Pipeline
          • Building Components
          • Building Python function-based components
          • Best Practices for Designing Components
          • Pipeline Parameters
          • Visualize Results in the Pipelines UI
          • Pipeline Metrics
          • DSL Static Type Checking
          • DSL Recursion
          • Using environment variables in pipelines
          • GCP-specific Uses of the SDK
          • Kubeflow Pipelines SDK for Tekton
          • Manipulate Kubernetes Resources as Part of a Pipeline
          • Python Based Visualizations (Deprecated)
        • Multi-user Isolation for Pipelines
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        • Upgrading
        • Samples and Tutorials
          • Using the Kubeflow Pipelines Benchmark Scripts
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          • Run a Cloud-specific Pipelines Tutorial
        • Troubleshooting
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            • Pipelines API Reference
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      • KFServing
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      • Katib
        • Introduction to Katib
        • Getting Started with Katib
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        • Overview of Trial Templates
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      • Training Operators
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      • Multi-Tenancy
        • Introduction to Multi-user Isolation
        • Design for Multi-user Isolation
        • Getting Started with Multi-user Isolation
    • External Add-Ons
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        • Overview of Kubeflow Fairing
        • Install Kubeflow Fairing
        • Configure Kubeflow Fairing
        • Fairing on Azure
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          • Configure Kubeflow Fairing with Access to GCP
          • GCP Samples and Tutorials
            • Train and Deploy on GCP from a Local Notebook
            • Train and Deploy on GCP from a Kubeflow Notebook
        • Tutorials
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        • Reference
          • Kubeflow Fairing SDK Reference
      • Feature Store
        • Introduction to Feast
        • Getting started with Feast
      • Tools for Serving
        • Overview
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        • BentoML
        • NVIDIA Triton Inference Server
        • TensorFlow Serving
        • TensorFlow Batch Prediction
    • Distributions
      • Kubeflow on AWS
        • Deployment
          • AWS Features for Kubeflow
          • Install Kubeflow
          • Amazon EKS and Kubeflow Compatibility
          • Uninstall Kubeflow
        • Customizing Kubeflow on AWS
          • Customizing Kubeflow on AWS
          • Logging
          • Custom Domain
          • Private Access
          • Storage Options
          • Configure Kubeflow with Amazon RDS
        • Authentication and Authorization
          • Authentication and Authorization
          • Authentication using OIDC
        • Optimized Jupyter Notebooks on AWS
        • Kubeflow Pipelines on AWS
        • End-to-end Kubeflow on AWS
        • Troubleshooting Kubeflow on Amazon EKS
      • Kubeflow on Azure
        • Deployment
          • Install Kubeflow
          • Initial cluster setup for existing cluster
          • Uninstall Kubeflow
        • Authentication using OIDC in Azure
        • Azure Machine Learning Components
        • End-to-End Pipeline Example on Azure
        • Access Control for Azure Deployment
        • Configure Azure MySQL database to store metadata
        • Troubleshooting Deployments on Azure AKS
      • Kubeflow on Google Cloud
        • Deployment
          • Overview
          • Set up Project
          • Set up OAuth client
          • Deploy Management cluster
          • Deploy Kubeflow cluster
          • Upgrade Kubeflow
          • Monitor Cloud IAP Setup
          • Delete Kubeflow
          • Deploy using UI
        • Pipelines on Google Cloud
          • Connecting to Kubeflow Pipelines on Google Cloud using the SDK
          • Authenticating Pipelines to Google Cloud
          • Upgrading
          • Enabling GPU and TPU
          • Using Preemptible VMs and GPUs on Google Cloud
        • Customize Kubeflow on GKE
        • Using Your Own Domain
        • Authenticating Kubeflow to Google Cloud
        • Securing Your Clusters
        • Troubleshooting Deployments on GKE
        • Kubeflow On-premises on Anthos
      • Kubeflow on IBM Cloud
        • Create or access an IBM Cloud Kubernetes cluster
        • Create or access an IBM Cloud Kubernetes cluster on a VPC
        • Kubeflow Deployment on IBM Cloud
          • Kubeflow Deployment Process
          • Install Kubeflow on IKS
          • Install Kubeflow on OpenShift
          • Securing the Kubeflow authentication with HTTPS
          • Uninstall Kubeflow
        • Pipelines on IBM Cloud Kubernetes Service (IKS)
        • Using IBM Cloud Container Registry (ICR)
        • End-to-end Kubeflow on IBM Cloud
      • Arrikto Enterprise Kubeflow
      • Arrikto MiniKF
        • MiniKF on laptop/desktop
        • MiniKF on AWS Marketplace
        • MiniKF on GCP Marketplace
      • Kubeflow Charmed Operators
        • Installing Kubeflow with Charmed Operators
      • Kubeflow Operator
        • Introduction
        • Installing Kubeflow Operator
        • Installing Kubeflow
        • Uninstalling Kubeflow
        • Uninstalling Kubeflow Operator
        • Troubleshooting
      • MicroK8s Kubeflow add-on
        • Kubeflow on MicroK8s
      • Kubeflow on OpenShift
        • Install Kubeflow on OpenShift
        • Uninstall Kubeflow
    • Tutorials, Samples, and Shared Resources
      • Kubeflow Samples
      • Codelabs, Workshops, and Tutorials
      • Blog Posts
      • Videos
      • Shared Resources and Components
    • Further Setup and Troubleshooting
      • Deploying Kubeflow behind a proxy server
      • Kubeflow On-prem in a Multi-node Kubernetes Cluster
      • Frequently Asked Questions
      • Support
      • Integrations
        • Data Management
    • Reference
      • Reference Overview
      • Kubeflow Versioning Policies
      • Dockerfile Locations
      • Katib Reference
        • Katib v1beta1
          • Katib
        • Katib v1alpha3
          • Katib
      • MPIJob Reference
        • MPIJob v1alpha2
          • MPIJob
      • Notebook CRD Reference
        • Notebook CRD V1 Reference
      • PyTorchJob Reference
        • PyTorchJob v1
          • PyTorchJob
        • PyTorchJob v1beta2
          • PyTorchJob
      • TFJob Reference
        • TFJob v1
          • TFJob Common
          • TFJob TensorFlow
        • TFJob v1beta2
          • TFJob Common
          • TFJob TensorFlow
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