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mlflow chart version 1.6.1 released

· 2 min read
Burak Ince
Burak Ince
Software Developer

We’re excited to announce the release of the mlflow Helm chart version 1.6.1, published on 2025-08-25 and powered by mlflow app version 3.3.1. This update introduces several enhancements, improved dependency versions, and continued support from the open-source community to make deploying MLflow on Kubernetes even easier.

What’s new in version 1.6.1​

This release includes updates to both the Helm chart and its dependencies, ensuring greater reliability and smoother integration for Kubernetes users:

  • 🔄 Image Update: Upgraded Docker image to burakince/mlflow:3.3.1
    ➤ View on Docker Hub

  • ⬆️ PostgreSQL Dependency: Upgraded Bitnami PostgreSQL chart from 16.7.21 to 16.7.26
    ➤ View on ArtifactHub

  • ⬆️ MySQL Dependency: Upgraded Bitnami MySQL chart from 14.0.0 to 14.0.3
    ➤ View on ArtifactHub

🔗 For the complete list of changes, review the official release notes on GitHub.

Get started with mlflow 1.6.1​

Deploying mlflow on Kubernetes has never been easier. Check out our installation guides to get up and running quickly:

  • Install using default configurations for a fast setup
  • Customize values to match your specific use case
  • Follow best practices for production environments

📘 Visit the mlflow docs for full configuration options and deployment guidance.

Why use the mlflow Helm chart?​

Maintained by the open-source community via the GitHub Community Charts project, this Helm chart streamlines the mlflow deployment process:

  • ✅ User-Friendly: Deploy with minimal config effort
  • 💡 Community-Powered: Frequent improvements and feedback-driven updates
  • ⚙️ Flexible: Adaptable to various Kubernetes setups
  • 📦 Stable: Tested for resilience in production-grade clusters

Join the mlflow community​

The GitHub Community Charts initiative thrives on collaboration. Whether you're new to Kubernetes or a seasoned devops pro, your contributions are highly valued:

Thank you for being part of the mlflow and Helm chart community. Together, we’re building better tools for deploying machine learning solutions at scale.