Sage Insights Dashboard and Collector

New Customer Link

For all new customers of Sage, please fill out the following link: https://airtable.com/appn1MXE52b4GKKbp/pagSyV3tDuaHDl4hL/form

ANNOUNCEMENT

Due to performance issues, Sage no longer supports csv as an output file. All files must not be in the form of parquet.

Because of this change, a large number of columns had to be reworked to handle the additional of a true schema being saved with the parquet files.

In a decision to keep things easier to maintain in the future, column names have been reworked to use more of the natural naming conventions.

• Actions to take migrating >1.6 or higher (if previously installed).
  • Patch to v1.6 or higher
  • Patch/Update the local code-environment for Sage
  • Rebuild the new Streamlit Code-Studio Template
  • Rename both the original partitioned_data and base_data folders (if wanting to preserve historical data)
    • If you do not want to preserve, drop and delete folders with Drop data selected
  • Run both Init Dashboard and Init Worker Macros
  • Double check that all code-environments properly rebuilt in the extra worker nodes
  • Let scenarios run at scheduled time or manually kick off first time

Contributors

• Author - Stephen Mazzei
• Email - Stephen.Mazzei@dataiku.com
• Version - 1.6.2
• Special Thanks
  • Development
    • Jordan Burke
    • Ben Bourgeois
    • Jonathan Sill
  • Documentation
    • Rob Harris
  • Project Management
    • Arjun Srivatsa

Scope

This dashboard is designed to give Dataiku Admins insights into the DSS instance.

• DSS at a glance
• Individual objects, statistics, graphs
• Maintenance and performance reviews

Tested Versions

1. v14.1.0 (v1.6 and below)
2. v14.0.0 (v1.5 and below)
3. v13.5.5 (v1.5 and below)

Installation Notes

Due to the web application being built on Streamlit, installation requires a bit of dedicated code use. Hoping this changes in later DSS versions.

1. Plugin
   1. Login as an admin account
   2. Migrate to Waffle::Plugins and install from GIT: https://github.com/dataiku/dss-plugin-sage-insights
   3. Build the code-environment, no containers needed
   4. After the plugin is installed, switch to the plugin settings page and fill in the information ("EXAMPLE BELOW")
      1. Sage Github Repo
         1. https://github.com/dataiku/dss-plugin-sage-insights
         2. main
      2. Sage Dashboard Information
         1. SAGE_DASHBOARD
         2. Hostname or IP:Port
         3. Admin Level Api Key
         4. SAGE_WORKER
         5. Ignore certs if needed, Default is False
      3. Sage Worker Information
         1. Fill out each host including the local host if you want to track the local host. Need both Hostname or IP:Port and Admin level API Key
2. Code Studios
   1. Create the template name sage # this name is important
   2. Setup K8s to run on
   3. Add the Sage Dashboard - Streamlit block
   4. Disable permissions for users
   5. Build
3. Create the Sage Dashboard project based off 1.4.2 information
   1. Go to Macros
   2. Filter on Sage Insights: Initialize
   3. Run Initialize Dashboard
   4. Run Initialize Workers
   5. Switch to Code Studios page under the Code tab
      1. Click the checkbox and publish as a Web Application (No API for this)
      2. Start the Web Application (Auto-Start)
      3. Nothing may be available at first while the first day cycle needs to run to gather data

Data Flow Diagrams