PrimeHub
v4.1
v4.1
  • 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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On this page
  • Download Report
  • Detailed Report
  • Summary Report
  1. Administrator Guide

Usage Reports

PreviousNotebooks AdminNextJupyter Images

From PrimeHub v3.1, the new feature, Usage Reports, is introduced that administrators can have a overall insight of who/what consumed resources monthly.

Usage is defined by allocated resources, not by actual utilization. For example, when an user opens an Jupyter notebook, the record of the allocated resources is logged in the usage report, even if the user doesn't run any program actually on it. The each record includes the lifetime of a pod, and CPU/GPU/Memory are allocated/occupied for a pod.

Download Report

Click Detailed Report or Summary Report of the month for downloading a csv file or search specific year-month by the format YYYY/M (e.g. 2020/7, 2020/12) in Date search field.

You even can download the report of the current month which is not over yet. It will have a pop-up to inform you that the data of current month is not intact. Just click Confirm for downloading.

Detailed Report

There are some insightful data of usage:

Item
Description

report_month

the report is for which year and month

group

which group which component runs at

user

which user uses resources

component

such as job, notebook, model_deploy

component_name

the name of the component

cpu_core_hours

hours if the computing work runs in a CPU

gpu_core_hours

hours if the computing work runs in a GPU

gb_memory_hours

hours if the computing work uses 1 GB memory

usage_hours

hours the computing work has done

instance_type

instance type

instance_cpu_core

vCPU cores of the instance

instance_gpu_core

GPU cores of instance

instance_memory_gb

memory of the instance

pod_name

name of the pod

k8s_uid

Kubernetes object id

start_time

time pod began running

end_time

time pod finished running

running

if it's still running

Summary Report

There are some insightful data of usage:

Item
Description

report_month

the report is for which year and month

group

which group which component runs at

user

which user uses resources

component

such as job, notebook, model_deploy

gpu_core_hours

hours if the computing work runs in a GPU

cpu_core_hours

hours if the computing work runs in a CPU

gb_memory_hours

hours if the computing work uses 1 GB memory

usage_hours

hours the computing work has done

running

if it's still running