WeAreDevelopers Logo WeAreDevelopers
Sign in
For You LIVE
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.

Pause
Mute Enter Fullscreen
#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

More from World Congress 2023

The year 3000, a brief history of Web Development thumbnail
25:30
over 2 years ago

The year 3000, a brief history of Web Development

Lorenzo Pieri

Demografie nutzen um jedem Bewerber das passende Angebot zu machen! thumbnail
8:52
over 2 years ago

Demografie nutzen um jedem Bewerber das passende Angebot zu machen!

Nathalie Gierth

Guided Memory Management: Rust's Ownership Model thumbnail
0:18
almost 3 years ago

Guided Memory Management: Rust's Ownership Model

Stefan Baumgartner

Passwordless future: WebAuthn and Passkeys in practice thumbnail
32:32
almost 3 years ago

Passwordless future: WebAuthn and Passkeys in practice

Clemens Hübner

External Secrets Operator: the secrets management toolbox for self-sufficient teams thumbnail
30:07
almost 3 years ago

External Secrets Operator: the secrets management toolbox for self-sufficient teams

Moritz Johner

Building Reliable Serverless Applications with AWS CDK and Testing thumbnail
25:18
almost 3 years ago

Building Reliable Serverless Applications with AWS CDK and Testing

Raphael Manke

Upcoming sessions on this topic

Open session

World Congress 2026 North America

September 25, 2026 · 12:55–13:25

Stage 9

It’s Alive! Taming the MLOps Franken-Stack: Write, Run, and Serve with Michelangelo

Eric Wang, Paul Zimmerman

Eric Wang
Paul Zimmerman
Open session

World Congress 2026 North America

September 24, 2026 · 17:30–18:00

Stage 6

No Single Model to Rule Them All: Building Resilient AI Agents Across Open & Closed LLMs

Emmanuel Acheampong

Senior Manager Developer Relations at Crusoe AI

Emmanuel Acheampong
Open session

World Congress 2026 North America

September 23, 2026 · 15:45–17:45

Stage 12

Architecting Multi-Agent Teams: Mastering the Orchestration Patterns of ADK 2

Christina Lin

Developer Relations Engineering Manager

Christina Lin
Open session

World Congress 2026 North America

September 24, 2026 · 10:20–10:50

Stage 2

From Static Rules to Reasoning Platforms: Scaling Intelligent Canary Delivery in 2026

Daniel Oh

Senior Principal Developer Advocate

Daniel Oh
Open session

World Congress 2026 North America

September 24, 2026 · 11:40–12:10

Stage 4

Taming Rogue Agents: Observability-Driven Evaluation for Production Reliability

Anagha Rumade, Anjana Umapathy, Apoorva Jaiswal

Anagha Rumade
Anjana Umapathy
Apoorva Jaiswal
Open session

World Congress 2026 North America

September 24, 2026 · 15:30–16:00

Stage 9

Run your agents in Kubernetes: Build once, deploy anywhere. But really?

Michal Salanci

Senior Systems Engineer at ESET Cybersecurity

Michal Salanci

Related videos

LLMOps-driven fine-tuning, evaluation, and inference with NVIDIA NIM & NeMo Microservices thumbnail
29:20
World Congress 2025 • about 1 year ago

LLMOps-driven fine-tuning, evaluation, and inference with NVIDIA NIM & NeMo Microservices

Anshul Jindal

Get ready for operations by pull requests thumbnail
50:02
LIVE • over 5 years ago

Get ready for operations by pull requests

Liviu Costea

The state of MLOps - machine learning in production at enterprise scale thumbnail
47:19
LIVE • over 4 years ago

The state of MLOps - machine learning in production at enterprise scale

Bas Geerdink

DevOps for AI: running LLMs in production with Kubernetes and KubeFlow thumbnail
34:21
LIVE • almost 2 years ago

DevOps for AI: running LLMs in production with Kubernetes and KubeFlow

Aarno Aukia

Effective Machine Learning - Managing Complexity with MLOps thumbnail
45:45
World Congress 2021 • about 5 years ago

Effective Machine Learning - Managing Complexity with MLOps

Simon Stiebellehner

DevOps for Machine Learning thumbnail
44:40
World Congress 2021 • about 5 years ago

DevOps for Machine Learning

Hauke Brammer

Related articles

From learning to earning

Jobs that call for the skills explored in this talk.