Catalog Systems Training infrastructure MLflow

MLflow

https://mlflow.org/

Databricks-incubated open platform for ML lifecycle — tracking, projects, models, model registry. Standard ML-ops baseline. MLflow 3.0 (2024) added LLM-eval features.

Active · Verified 2026-10-27 · fresh as of 2026-10-27 · 18 cited facts, 2 with a third-party source · 1 recorded change · Suggest a correction

At a glance

Type
Open ML lifecycle platform vendor fix
Tier
T1
Section
Training infrastructure
Created
2018 repo fix
Latest release
v3.17.2 (2026-10-21) — mlflow registry fix
License
Apache-2.0 vendor fix
GitHub
mlflow/mlflow — ~28.6k stars, last commit 2026-10 repo fix
Pricing
searched not found fix
Funding
OSS project — sponsored by Databricks (Databricks raised $43.2B at $62B valuation 2024-12, $10B Series J 2024-12). third-party fix
Freshness
2026-10-27 fix
Layer
model-infra repo fix
Licensing
open-source vendor fix
Deployment locus
hybrid repo fix
Platform vs product
platform repo fix
Developer activity
OpenRank 62.58 (12-mo avg 79.37) · 263 participants — 2026-09 third-party fix

When to use

Optimised for: searched not found

Anti-fit: searched not found

Pros & cons

Pros

searched not found

Cons

searched not found

Claims & capabilities

Default ML-ops scaffold in many enterprises.

Technical surface

API surface
Python SDK, CLI, MCP server
Backend storage
searched not found
Deployment
searched not found
Embedding model
not applicable — not a memory product
Multi-tenancy
searched not found
MCP
yes — built-in MCP server (experimental, mlflow mcp run, MLflow 3.5.1+) exposing trace search, tagging and feedback tools
A2A
searched not found
OpenTelemetry
searched not found

Compare MLflow with…

Similar systems

Other training infrastructure in the catalog, ranked by inbound references.

  • AWS SageMaker T1

    AWS's managed ML platform — Studio, Training, HyperPod (large-scale clusters), Endpoints. Industry-standard for enterprise AWS-hosted training.

  • Weights & Biases T1

    Experiment-tracking and ML-ops platform (metrics, artifacts, sweeps, Weave tracing/evals). Acquired by CoreWeave (completed 2025-05-05, ~$1.7B); now part of CoreWeave Forge.

  • Comet ML T2

    ML experiment tracking + LLM evaluation platform (Opik for LLM eval). Comet competes head-to-head with Weights & Biases.

  • Azure Machine Learning T1

    Microsoft Azure's managed ML platform — pipelines, AutoML, Designer, prompt flow (LLM). Heavy integration with Azure OpenAI and Azure AI Studio.

  • LoRA T3

    Microsoft Research's Low-Rank Adapters method — trains rank-r matrices added to attention weights; 10000x parameter reduction. Foundation of all adapter-style fine-tuning.

  • Argilla T2

    Open-source data-quality platform for LLM training data — human-in-the-loop labelling, RLHF data collection, dataset curation. Acquired by Hugging Face 2024.

Sources (17 cited facts, 2 third-party)

Each fact links to the page it came from; the badge says who published it (how to read sources).

What changed

Changes to this record's lifecycle, licence, release, pricing and hosting facts, from the catalog's git history. Subscribe (Atom)

  1. 2026-10-27
    • Latest release first recorded as “v3.17.2 (2026-10-21) — mlflow” source
    • MCP support first recorded as “yes — built-in MCP server (experimental, mlflow mcp run, MLflow 3.5.1+) exposing trace search, tagging and feedback tools” source
    #272

Related systems

Referenced by (15)

  • Arize Phoenix integrates with — Arize Phoenix docs have a MLflow integration page. (verified 2026-10-29)
  • CrewAI integrates with — CrewAI docs have an MLflow observability integration page. (verified 2026-10-29)
  • DSPy integrates with — DSPy observability tutorial shows MLflow automatic tracing via mlflow.dspy.autolog(). (verified 2026-10-29)
  • Fireworks AI integrates with — Fireworks AI docs integration: MLflow tracing (MLOps & Observability). (verified 2026-10-29)
  • Google Agent Development Kit (ADK) integrates with — ADK integrations catalog has a "MLflow observability for ADK" page (Ingest OpenTelemetry traces for agent runs, tool calls, and model requests). (verified 2026-10-29)
  • Guardrails AI integrates with — Guardrails AI docs have an MLflow GenAI integration page. (verified 2026-10-29)
  • Haystack (framework) integrates with — Haystack integrations directory has an MLflow integration page ("Trace, evaluate, and monitor your Haystack applications with MLflow"). (verified 2026-10-29)
  • LangChain (framework) integrates with — LangChain docs have an MLflow Tracking integration provider page (Experiment tracking and model registry). (verified 2026-10-29)
  • Langfuse integrates with — Langfuse's integrations directory has a MLflow integration page. (verified 2026-10-29)
  • LiteLLM integrates with — LiteLLM docs have an MLflow logging/observability integration page. (verified 2026-10-29)
  • OpenAI Agents SDK integrates with — OpenAI Agents SDK tracing docs list MLflow under external tracing processors. (verified 2026-10-29)
  • Pipecat (Daily) integrates with — Pipecat docs have a MLflow service page. (verified 2026-10-29)
  • Portkey AI integrates with — Portkey docs have an MLflow Tracing tracing provider integration page. (verified 2026-10-29)
  • smolagents (Hugging Face) integrates with — smolagents inspect-runs tutorial has a section on setting up telemetry with MLflow. (verified 2026-10-29)
  • Vercel AI SDK integrates with — AI SDK docs have an MLflow observability integration page. (verified 2026-10-29)