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Kubeflow v1.1 Documentation
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Google Cloud for Kubeflow

 来源:Kubeflow 浏览 285 扫码 分享 2021-07-11 09:49:49
  • Google Cloud for Kubeflow

    Google Cloud for Kubeflow

    Get Kubeflow running on Google Cloud Platform (GCP)

    For details on setting up your GCP environment and deploying Kubeflow on Kubernetes Engine (GKE), refer to the deployment section of the Kubeflow GCP documentation.

    Last modified 19.10.2020: Remove out of date message from reference docs and GCP getting started (#2277) (403b546b)

    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
      • Kubeflow
      • Use Cases
      • Contributing to Kubeflow
      • Community
      • Google Summer of Code
      • Docs
      • Style Guide for the Kubeflow Docs
      • Events Calendar
    • Getting Started
      • Kubeflow Overview
      • Installing Kubeflow
      • Cloud Installation
        • AWS for Kubeflow
        • Azure for Kubeflow
        • Google Cloud for Kubeflow
        • IBM Cloud for Kubeflow
      • Kubernetes Installation
        • Overview of Deployment on Existing Clusters
        • Kubeflow Deployment with kfctl_k8s_istio
        • Multi-user, auth-enabled Kubeflow with kfctl_existing_arrikto
        • Multi-user, auth-enabled Kubeflow with kfctl_istio_dex
      • Workstation Installation
        • Kubeflow on Linux
        • Kubeflow on macOS
        • Kubeflow on Windows
        • MiniKF
        • Deploy Kubeflow using MiniKF on Google Cloud
        • Deploying with minikube on a single node
        • Kubeflow on MicroK8s
    • Components of Kubeflow
      • Central Dashboard
        • Central Dashboard
        • Registration Flow
      • Metadata
      • Jupyter Notebooks
      • Fairing
        • Overview of Kubeflow Fairing
        • Install Kubeflow Fairing
        • Configure Kubeflow Fairing
        • Fairing on Azure
        • Fairing on GCP
          • 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
          • Other Samples and Tutorials
        • Reference
          • Kubeflow Fairing SDK Reference
      • Feature Store
        • Introduction to Feast
        • Getting started with Feast
      • Frameworks for Training
        • Chainer Training
        • MPI Training
        • MXNet Training
        • PyTorch Training
        • TensorFlow Training (TFJob)
      • Hyperparameter Tuning
        • Introduction to Katib
        • Getting started with Katib
        • Running an experiment
        • Katib Configuration Overview
        • Environment Variables for Katib Components
      • Pipelines
        • Pipelines
      • Tools for Serving
        • Overview
        • KFServing
        • Seldon Core Serving
        • BentoML
        • NVIDIA Triton Inference Server
        • TensorFlow Serving
        • TensorFlow Batch Prediction
      • Multi-Tenancy in Kubeflow
        • Introduction to Multi-user Isolation
        • Design for Multi-user Isolation
        • Getting Started with Multi-user Isolation
      • Miscellaneous
        • Nuclio functions
    • Jupyter Notebooks
      • Overview of Jupyter Notebooks in Kubeflow
      • Set Up Your Notebooks
      • Create a Custom Jupyter Image
      • Submit Kubernetes Resources
      • Build a Docker Image on GCP
      • Troubleshooting Guide
    • 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
          • Component
          • Graph
          • Experiment
          • Run and Recurring Run
          • Run Trigger
          • Step
          • Output Artifact
      • Building Pipelines with the SDK
        • Introduction to the Pipelines SDK
        • Install the Kubeflow Pipelines SDK
        • Build Components and Pipelines
        • Create Reusable Components
        • Building Python function-based components
        • Best Practices for Designing Components
        • Pipeline Parameters
        • Python Based Visualizations
        • 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
        • Manipulate Kubernetes Resources as Part of a Pipeline
        • https://v1-1-branch.kubeflow.org/docs/pipelines/sdk/owners/
      • Multi-user Isolation for Pipelines
      • Caching
      • Upgrading
      • Samples and Tutorials
        • Using the Kubeflow Pipelines Benchmark Scripts
        • Using the Kubeflow Pipelines SDK
        • Experiment with the Kubeflow Pipelines API
        • Experiment with the Pipelines Samples
        • Run a Cloud-specific Pipelines Tutorial
      • Troubleshooting
      • Reference
        • Component Specification
          • Pipelines API Reference
        • Pipelines SDK Reference
    • Kubeflow on AWS
      • Deployment
        • Install Kubeflow
        • Uninstall Kubeflow
      • Customizing Kubeflow on AWS
      • AWS IAM Role for Service Account
      • Logging
      • Private Access
      • Authentication and Authorization
      • Authentication using OIDC
      • Configure Kubeflow Pipelines on AWS
      • Custom Domain
      • Optimized Jupyter Notebooks on AWS
      • Storage Options
      • Configure External Database Using Amazon RDS
      • Troubleshooting Deployments on Amazon EKS
      • Kubeflow on AWS Features
      • End-to-end Kubeflow on AWS
    • Kubeflow on Azure
      • Deployment
        • Install Kubeflow
        • Initial cluster setup for existing cluster
        • Uninstall Kubeflow
      • Authentication using OIDC in Azure
      • End-to-End Pipeline Example on Azure
      • Access Control for Azure Deployment
      • Troubleshooting Deployments on Azure AKS
    • Kubeflow on GCP
      • Deploying Kubeflow
        • Set up a Google Cloud Project
        • Set up OAuth for Cloud IAP
        • Management cluster setup
        • Deploy using kubectl and kpt
        • Monitor Cloud IAP Setup
        • Delete using CLI
        • Features of Kubeflow on GCP
        • Deploy using UI
      • Kubeflow On-premises on Anthos GKE
      • Pipelines on GCP
        • Connecting to Kubeflow Pipelines on Google Cloud using the SDK
        • Authenticating Pipelines to GCP
        • Upgrading
        • Enabling GPU and TPU
        • Using Preemptible VMs and GPUs on GCP
      • Customizing Kubeflow on GKE
      • Using Your Own Domain
      • Authenticating Kubeflow to GCP
      • Using Cloud Filestore
      • Securing Your Clusters
      • Troubleshooting Deployments on GKE
      • Tutorial: End-to-end Kubeflow on GCP
      • Logging and monitoring
    • Kubeflow on IBM Cloud
      • Deployment
        • Install Kubeflow
        • Securing the Kubeflow authentication with HTTPS
        • Uninstall Kubeflow
      • Create an IBM Cloud cluster
      • Initial cluster setup for existing cluster
      • Using IBM Cloud Container Registry (ICR)
      • Pipelines on IBM Cloud Kubernetes Service (IKS)
      • End-to-end Kubeflow on IBM Cloud
    • Kubeflow Operator
      • Introduction
      • Installing Kubeflow Operator
      • Installing Kubeflow
      • Uninstalling Kubeflow
      • Uninstalling Kubeflow Operator
      • Troubleshooting
    • 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
      • Configuring Kubeflow with kfctl and kustomize
      • Kubeflow On-prem in a Multi-node Kubernetes Cluster
      • Usage Reporting
      • Istio Usage in Kubeflow
      • Job Scheduling
      • Troubleshooting
      • Frequently Asked Questions
      • Support
      • Integrations
        • Data Management
    • Upgrading Kubeflow
    • Reference
      • Reference Overview
      • Kubeflow Versioning Policies
      • Dockerfile Locations
      • Katib Reference
        • 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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