PrimeHub
  • Introduction
  • Installation
  • Tiers and Licenses
  • End-to-End Tutorial
    • 1 - MLOps Introduction and Scoping the Project
    • 2 - Train and Manage the Model
    • 3 - Compare, Register and Deploy the Model
    • 4 - Build the Web Application
    • 5 - Summary
  • User Guide
    • User Portal
    • Notebook
      • Notebook Tips
      • Advanced Settings
      • PrimeHub Notebook Extension
      • Submit Notebook as Job
    • Jobs
      • Job Artifacts
      • Tutorial
        • (Part1) MNIST classifier training
        • (Part2) MNIST classifier training
        • (Advanced) Use Job Submission to Tune Hyperparameters
        • (Advanced) Model Serving by Seldon
        • Job Artifacts Simple Usecase
    • Models
      • Manage and Deploy Model
      • Model Management Configuration
    • Deployments
      • Pre-packaged servers
        • TensorFlow server
        • PyTorch server
        • SKLearn server
        • Customize Pre-packaged Server
        • Run Pre-packaged Server Locally
      • Package from Language Wrapper
        • Model Image for Python
        • Model Image for R
        • Reusable Base Image
      • Prediction APIs
      • Model URI
      • Tutorial
        • Model by Pre-packaged Server
        • Model by Pre-packaged Server (PHFS)
        • Model by Image built from Language Wrapper
    • Shared Files
    • Datasets
    • Apps
      • Label Studio
      • MATLAB
      • MLflow
      • Streamlit
      • Tutorial
        • Create Your Own App
        • Create an MLflow server
        • Label Dataset by Label Studio
        • Code Server
    • Group Admin
      • Images
      • Settings
    • Generate an PrimeHub API Token
    • Python SDK
    • SSH Server Feature
      • VSCode SSH Notebook Remotely
      • Generate SSH Key Pair
      • Permission Denied
      • Connection Refused
    • Advanced Tutorial
      • Labeling the data
      • Notebook as a Job
      • Custom build the Seldon server
      • PrimeHub SDK/CLI Tools
  • Administrator Guide
    • Admin Portal
      • Create User
      • Create Group
      • Assign Group Admin
      • Create/Plan Instance Type
      • Add InfuseAI Image
      • Add Image
      • Build Image
      • Gitsync Secret for GitHub
      • Pull Secret for GitLab
    • System Settings
    • User Management
    • Group Management
    • Instance Type Management
      • NodeSelector
      • Toleration
    • Image Management
      • Custom Image Guideline
    • Volume Management
      • Upload Server
    • Secret Management
    • App Settings
    • Notebooks Admin
    • Usage Reports
  • Reference
    • Jupyter Images
      • repo2docker image
      • RStudio image
    • InfuseAI Images List
    • Roadmap
  • Developer Guide
    • GitHub
    • Design
      • PrimeHub File System (PHFS)
      • PrimeHub Store
      • Log Persistence
      • PrimeHub Apps
      • Admission
      • Notebook with kernel process
      • JupyterHub
      • Image Builder
      • Volume Upload
      • Job Scheduler
      • Job Submission
      • Job Monitoring
      • Install Helper
      • User Portal
      • Meta Chart
      • PrimeHub Usage
      • Job Artifact
      • PrimeHub Apps
    • Concept
      • Architecture
      • Data Model
      • CRDs
      • GraphQL
      • Persistence Storages
      • Persistence
      • Resources Quota
      • Privilege
    • Configuration
      • How to configure PrimeHub
      • Multiple Jupyter Notebook Kernels
      • Configure SSH Server
      • Configure Job Submission
      • Configure Custom Image Build
      • Configure Model Deployment
      • Setup Self-Signed Certificate for PrimeHub
      • Chart Configuration
      • Configure PrimeHub Store
    • Environment Variables
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  • Key Capabilities
  • User Portal
  • Admin Portal

Introduction

Platform Introduction

NextInstallation

Last updated 2 years ago

PrimeHub is a Kubernetes-based platform designed for groups of data scientists. It aims to be an all-in-one, enterprise-level, machine learning platform that provides a seamless MLOps experience.

PrimeHub adopts a group-centric design, which accelerates collaborative development. In PrimeHub, scientists can share datasets, artifacts, and seamlessly collaborate on projects in groups. Models can be developed, deployed, and monitored with full control in a transparent group environment.

Using PrimeHub’s granular controls, administrators can configure access control settings, manage resources, and adjust resource quotas for groups - All facilitating efficient resource utilization.

With the addition of 3rd-party app integration, PrimeHub’s capabilities can be augmented on demand, accelerating the machine learning workflow. These 3rd-party apps also benefit from the access control and resource configurability that is available through PrimeHub, making for a true, all-in-one, MLOps solution.

Key Capabilities

  • Cluster Computing

  • One-Click Research Environments

  • Easy Dataset Loading

  • Management of Resource & Quota Privileges

  • Custom Deep Learning Environments

  • Enterprise-Class Account Management

  • Capability Augmentation via 3rd-party Apps


PrimeHub is composed of a User Portal and an Admin Portal. The User Portal provides features aimed at data scientists and team members, and the Admin Portal provides configuration options relevant to platform administrators.

User Portal

Landing Page Layout

  1. User features

  2. Group switch

  3. Group context

Admin Portal

Landing Page Layout

  1. Platform administrator features

  2. Feature context

The provides access to a full MLOps feature set. Data scientists can turn workflows into automated pipelines via Jobs/Recurring Jobs; prepare data and develop trained models from Notebooks; deploy container-wrapped models as services via Model Deployment, and more.

Group admin features (Viewable only to the )

Admin Portal entry (Viewable only to the )

The enables platform administrators to manage all aspects of PrimeHub, such as access-control, resources and quota control, building custom environments via image builder etc.

User Portal
Admin Portal
group admin
platform admin