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Kubeflow Operations Guide
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Kubeflow Operations Guide
by Austin Harris, Michael Katzenellenbogen, Josh Patterson
Kubeflow Operations Guide
1. Introduction to Kubeflow
Machine Learning on Kubernetes
The Evolution of Machine Learning in the Enterprise
It’s Harder Than Ever to Run Enterprise Infrastructure
Identifying Next Generation Infrastructure Core Principles
Enter: Kubeflow
Origin of Kubeflow
Who Uses Kubeflow?
Common Kubeflow Use Cases
Running Notebooks on GPUs
Shared Multi-Tennant Machine Learning Environment
Example: Building a Transfer Learning Pipeline
Deploying Models to Production for Application Integration
Components of Kubeflow
Jupyter Notebooks
Machine Learning Model Training Components
Hyperparameter Tuning
Pipelines
Machine Learning Model Inference Serving
An Overview of Kubernetes
Core Kubenetes Concepts
Summary
2. Planning a Kubeflow Installation
Users
Profiling Users
Varying Skillsets
Kubeflow Components
Components that Extend the Kubernetes API
Components running atop of Kubernetes
Workloads
Cluster Utilization
Data Patterns
GPU Planning
Planning for GPUs
Models that Benefit from GPUs
Infrastructure Planning
Kubernetes Considerations
On-Premise
Cloud
Placement
Container Management
Security
Background & Motivation
Control Plane
Kubeflow and Deployed Applications
Multitenancy & Isolation
Integration
Sizing & Growing
Forecasting
Storage
Scaling
3. Running Kubeflow on Google Cloud
Installing on a Public Cloud
Managed Kubernetes in the Cloud
Overview of the Google Cloud Platform
Storage
Google Cloud Security and the Cloud Identity-Aware Proxy
GCP Projects for Application Deployments
GCP Service Accounts
Google Compute Engine
Managed Kubernetes on GKE
Signing Up for Google Cloud Platform
Installing the Google Cloud SDK
Update Python
Download and Install Google Cloud SDK
Installing Kubeflow on Google Cloud Platform
Create a Project in the GCP Console
Enabling APIs for a Project
Set up OAuth for GCP Cloud IAP
Deploy Kubeflow Using the Command-Line Interface
Accessing the Kubeflow UI Post-Installation
Understanding How the Deployment Process Works
Understanding What Was Deployed on GCP
Creating Managed Kubernetes Clusters on GKE
Common Operations for Google Cloud and GKE
Resizing a Cluster
Deleting a Cluster
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Kubeflow Operations Guide
Kubeflow Operations Guide
Josh Patterson, Michael Katzenellenbogen,
and Austin Harris
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