george0st/qgate-sln-mlrun
MLRun/Iguazio/Nuclio quality gate solution. The solution checks a quality of MLRun implementation/delivery.
This solution helps MLOps engineers and data scientists ensure the quality of their MLRun machine learning implementations. It takes your MLRun projects and configurations as input and produces detailed test reports in HTML or plain text, highlighting any issues with project creation, feature sets, data ingestion, pipelines, and model serving. This is ideal for teams deploying ML models and seeking to prevent compatibility problems or regressions.
303 stars. No commits in the last 6 months. Available on PyPI.
Use this if you are an MLOps engineer or data scientist working with MLRun and need a robust, independent way to test your ML pipelines and deployments before full rollout.
Not ideal if you are not using MLRun or Iguazio for your machine learning workflows.
Stars
303
Forks
11
Language
Python
License
Apache-2.0
Category
Last pushed
Aug 05, 2025
Commits (30d)
0
Dependencies
11
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/mlops/george0st/qgate-sln-mlrun"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
kserve/kserve
Standardized Distributed Generative and Predictive AI Inference Platform for Scalable,...
omegaml/omegaml
MLOps simplified. One-stop AI delivery platform, all the features you need.
awslabs/aiops-modules
AIOps modules is a collection of reusable Infrastructure as Code (IaC) modules for Machine...
GoogleCloudDataproc/dataproc-ml-python
Library to simplify running distributed ML workloads with Apache Spark
jina-ai/serve
☁️ Build multimodal AI applications with cloud-native stack