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Third-Party Integrations

This section covers connecting third-party tools to Michelangelo. If you are looking for documentation on Michelangelo's own components — the model registry, experiment tracking setup, serving infrastructure, or job scheduler — see the Operator Guides index.

Before configuring any tool below, complete Experiment Tracking Setup — the platform-level guide for network reachability, ConfigMap injection, auth, and the operator/user boundary that applies to all third-party tracking integrations.

GuideDescription
MLflowConnect a self-hosted or Databricks-managed MLflow Tracking Server — network setup, auth, and MLflow vs Michelangelo registry comparison

Next Steps

  • Network & Ingress — configure egress rules, Envoy proxy, ingress, TLS, and multi-cluster networking
  • Authentication — manage secrets, workload identity, and RBAC for credential handling
  • Troubleshooting — diagnose common failure modes with kubectl diagnostic commands