Until Conference Starts: ✓ 10% Team Discount ✓ 4-Day Special✓ Access to Parallel Conferences for $250

Until Conference Starts: ✓ 10% Team Discount ✓ 4-Day Special✓ Access to Parallel Conferences for $250

Only Until Sept 11: ✓ Save up to 450€ ✓ Free devmio Access ✓ Free Gadget

Only Until Sept 11: ✓ Save up to 450€ ✓ Free devmio Access ✓ Free Gadget

Thanks For Another Great Conference Week: ✓ See You in 2026 ✓ Stay Tuned and Register for Our Newsletter

Thanks For Another Great Conference Week: ✓ See You in 2026 ✓ Stay Tuned and Register for Our Newsletter

Thanks For Another Great Conference Week: ✓ See You in 2026 ✓ Stay Tuned and Register for Our Newsletter

Thanks For Another Great Conference Week: ✓ See You in 2026 ✓ Stay Tuned and Register for Our Newsletter

Until the Conference starts: ✓ Team discount ✓ Access to devmio

Until the Conference starts: ✓ Team discount ✓ Access to devmio

From lab to live—operationalize ML and LLMs with confidence

Streamline your ML and LLM deployment lifecycle with reproducible pipelines, CI/CD automation, and secure infrastructure. This track is your roadmap to scaling AI systems securely and reliably.

Speaker Programm Program

MLOps, LLMOps & Pipelines

Learn from Industry Leaders about:

  • CI/CD pipelines for ML & LLM deployment
  • Reproducibility and model versioning with registries
  • Drift monitoring and alerting at scale
  • Infrastructure automation across clouds and clusters
  • Best practices for secure, reliable production AI

Frequently Asked Questions

What is the goal of the MLOps & LLMOps track?

This track teaches how to move models from development to deployment. You’ll master automated CI/CD for ML, drift detection, model versioning, and infrastructure orchestration tailored for both traditional ML and modern LLM workflows.

How is LLMOps different from MLOps?

LLMOps extends MLOps practices to large language models. It focuses on managing prompts, handling scale, monitoring hallucinations, and versioning LLM behaviors—all while ensuring security and consistency.

What tools and platforms are covered?

You’ll work with MLflow, DVC, KServe, Terraform, Helm, and Kubernetes. Each tool is covered in context—helping you build auditable, resilient, and secure AI systems.

How does this track support production-readiness?

By focusing on reproducibility and infrastructure-as-code, this track equips engineers to scale AI while maintaining traceability and compliance. It emphasizes strategies for rollback, drift response, and cross-environment parity.

Track Speakers London 2025

Track Speakers San Diego 2025

San Diego's program will go live soon! Until then, please take a look at

New York's 2024 Program!

Track Speakers Munich 2025

Track Speakers New York 2025

Track Speakers Berlin 2025

Track Program London 2025

Track Highlights San Diego 2025

MLOps Track Program 2025

Track Program New York 2025

Track Program Berlin 2025

We are currently working on this part of the program. Check back soon and have a look at the rest of the current MLCON Munich 2023 program here.