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mlflow chart version 1.7.3 released

· 2 min read
Burak Ince
Burak Ince
Software Developer

We’re excited to announce the release of the latest version of the mlflow Helm chart — v1.7.3, featuring mlflow app version 3.5.1. Available as of October 23, 2025, this release introduces new functionality and community-driven refinements to make deploying mlflow on Kubernetes even easier.

What's New in 1.7.3​

Here’s what’s included in this chart release:

  • 🔄 Updated: Docker image version for burakince/mlflow upgraded to 3.5.1
    → View on Docker Hub

  • 🗃️ Updated: PostgreSQL dependency bumped from 18.0.15 to 18.1.1
    → View on ArtifactHub

To review all the details and contributions, visit the official release notes on GitHub.

How to Install mlflow 1.7.3​

Getting started with the Helm chart is simple. Whether you’re experimenting locally or rolling out mlflow in a robust cloud-native environment, our installation docs guide you every step of the way.

Highlights include:

  • 🚀 Quick installation using default settings
  • ⚙️ Customization options for different Kubernetes environments
  • 🛡️ Tips for optimizing production deployments

Check out the full mlflow Helm chart documentation to explore configuration options and start your deployment.

Why Use the mlflow Helm Chart?​

The mlflow Helm chart, maintained by the open-source GitHub Community Charts project, offers a powerful yet flexible way to run mlflow on Kubernetes. Here’s why users love it:

  • ✅ Easy setup — get up and running in minutes
  • 🔧 Highly configurable for diverse machine learning workflows
  • 🌍 Backed by a passionate open-source community
  • 📦 Regularly updated for security and reliability

If mlflow is part of your MLOps toolchain, this chart helps ensure smoother operations on Kubernetes.

Join Our Community​

The GitHub Community Charts project thrives because of passionate contributors like you. Whether you’re improving documentation, proposing enhancements, or reporting issues — your input makes a difference.

Here’s how to get involved:

  • 📘 Explore the docs to learn about configuration options.
  • 🛠️ Contribute directly via pull requests.
  • 🐞 Report bugs or request features on our issue tracker.

Thank you for being a part of the mlflow and Kubernetes open-source community. Together, we’re making MLOps more accessible and powerful for everyone.