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mlflow chart version 1.4.0 released

· 2 min read
Burak Ince
Burak Ince
Software Developer

We’re excited to share the release of the latest mlflow Helm chart version 1.4.0, now available as of August 2, 2025. This version ships with mlflow app version 3.1.4 and includes updates to help you deploy and manage mlflow more easily and securely in Kubernetes environments.

What’s New in mlflow Helm Chart 1.4.0​

This release brings notable improvements and added flexibility for cloud-native ML workflows:

  • ✅ New Feature: Support for reading AWS credentials (AWS Access Key ID and AWS Secret Access Key) from an existing Kubernetes secret.

For a full list of updates, check the official release notes on GitHub.

How to Get Started​

Deploying mlflow on Kubernetes has never been simpler. Our mlflow Helm documentation provides everything you need—whether you're just getting started or customizing for production.

Here’s what you’ll find:

  • Instructions for quick installation using default settings.
  • Guides for advanced configuration tailored to your infrastructure.
  • Best practices to ensure stable and secure deployments.

Why Use the mlflow Helm Chart?​

Developed and maintained by the GitHub Community Charts team, the mlflow Helm chart is your go-to solution for running mlflow in Kubernetes. It’s designed to be:

  • 🚀 Easy to Deploy: Spin up your ML platform with minimal effort.
  • 🧩 Highly Flexible: Configure to meet your team’s specific needs.
  • 🤝 Community-Driven: Built in collaboration with contributors worldwide.
  • 🔒 Production-Ready: Tested for reliability and scalability at every update.

Join Our Community​

We're an open-source community, and your involvement helps mlflow and our charts thrive. Here’s how to participate:

  • 📘 Review our mlflow documentation to explore available options.
  • 🛠️ Contribute code or improvements via pull requests to the GitHub repo.
  • 🐞 Report bugs quickly and easily through our issue tracker.
  • 💡 Share feature ideas and enhancements—we’re all ears!

Thank you for being part of the mlflow and Helm chart community. Let’s continue building better tools together for the Kubernetes and ML ecosystems.