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World Congress 2023 • Nov 10, 2023

MLOps on Kubernetes: Exploring Argo Workflows

Hauke Brammer

How do you scale machine learning models from research to reproducible production? Discover how Argo Workflows orchestrates complex MLOps pipelines natively on Kubernetes clusters.

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#1 about 6 min

Defining MLOps and its role in production systems

How combining software development, data engineering, and machine learning optimizes model lifecycles.

#2 about 3 min

Solving complex pipeline orchestration with Argo Workflows

Why migrating repetitive Python scripts to a Kubernetes-native engine improves deployment scalability.

#3 about 3 min

Understanding the core components of Argo Workflows

How custom resource definitions, controllers, and stateless architectures manage distributed workflow resources.

#4 about 5 min

Translating simple code into Argo YAML configurations

How to map basic sequential programming functions into containerized Argo step configurations.

#5 about 5 min

Managing machine learning data pipelines with Argo artifacts

Moving training data continuously across cloud storage paths using declarative input and output artifacts.

#6 about 5 min

Structuring model training pipelines with directed acyclic graphs

Defining complex training dependencies and parallel execution limits using automated cyclic graph templates.

#7 about 5 min

Ensuring stable batch inference with automated retry strategies

Configuring custom backoff thresholds and retries to handle unpredictable failures in long-running batch predictions.

#8 about 3 min

Evaluating when to adopt Argo Workflows for data pipelines

Why existing Kubernetes maturity and multi-cluster execution needs determine whether Argo is the appropriate framework.

#9 about 2 min

Comparing Argo Workflows with MLflow and Argo CD

How Argo Workflows integrates with delivery protocols and schedules arbitrary containers unlike Python-only alternatives.

Matching moments

2:52 min

Automating discrete component pipelines using Argo Workflows

Anshul Jindal Anshul Jindal · World Congress 2025

2:26 min

Introduction to GitOps and the Argo CD presentation

Liviu Costea · LIVE

2:59 min

Defining LLMOps and its workflow automation benefits

Maxim Salnikov Maxim Salnikov · LIVE

3:56 min

Solving application deployment complexities using LLMOps pipelines

Anshul Jindal Anshul Jindal · World Congress 2025

2:14 min

Differences between traditional MLOps and GenAIOps

Maxim Salnikov Maxim Salnikov · World Congress 2025

2:48 min

Demonstrating an integrated LLMOps cluster deployment environment

Anshul Jindal Anshul Jindal · World Congress 2025

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