Skip to content

Latest commit

 

History

History
51 lines (46 loc) · 2.16 KB

README.md

File metadata and controls

51 lines (46 loc) · 2.16 KB
Raw

QGate-Sln-MLRun

Quality Gate for solution MLRun (and Iguazio). The main aims of the project are:

  • independent quality test (function, integration, acceptance, ... tests)
  • deeper quality checks before full rollout/use in company environments
  • identification of compatibility issues (if any)
  • external and independent test coverage
  • etc.

The tests use these key components:

  • MLRun solution (used in Iguazio solution also), see GIT mlrun
  • Sample meta-data model, see GIT qgate-model
  • This project

Usage

You can easy use this solution in three steps:

  1. Download content of these two GIT repositories to your local environment
  2. Update file qgate-sln-mlrun.env from qgate-model
    • Update variables for MLRun/Iguazio, see MLRUN_DBPATH, V3IO_USERNAME, V3IO_ACCESS_KEY, V3IO_API
      • setting of V3IO_* is needed only in case of Iguazio installation (not for pure free MLRun)
    • Update variables for QGate, see QGATE_*
  3. Run from qgate-sln-mlrun
    • python main.py

Precondition: You have available MLRun or Iguazio solution (MLRun is part of that), see official installation steps

Use cases

Quality Gate covers these use cases:

  • Project
    • UC101: Create project
    • UC102: Delete project
  • Feature set
    • UC201: Create feature sets (with entities, features, targets)
    • UC202: Create feature vector
  • Ingest data
    • UC301: Ingest data to feature sets
  • Feature vector
    • UC401: Get data from one feature set
    • UC402: Join data from two feature sets
    • UC403: Join data from four feature sets

Tested with

The project was test with these versions (see change log):

  • Iguazio (k8s, on-prem with VM with VMware)
    • Iguazio 3.5.3 (with MLRun 1.4.1)
    • Iguazio 3.5.1 (with MLRun 1.3.0)
  • MLRun (in Desktop Docker)
    • MLRun 1.5.1, 1.5.0
    • MLRun 1.4.1
    • MLRun 1.3.0