CNCF-hosted Co-located Events Europe 2025

Public cloud providers attract organizations with a promise: every computing service you need, neatly packaged under one roof. Yet those seeking to break free from vendor lock-in and build a sovereign infrastructure face a different reality - navigating a maze of specialized tools: Airflow for data pipelines, SLURM for HPC, Spark for analytics, and a variety of solutions for serverless functions - all using a different interface. We're here to challenge this fragmentation. What if Argo Workflows could be your universal scheduling engine? Through practical examples, we'll demonstrate how the Argo ecosystem - with its container-native workflow engine and robust event system - can consolidate most, if not all, of your compute infrastructure. We'll share our journey of integrating and/or replacing most of our existing scheduling systems with Argo, revealing concrete patterns that preserve workload-specific requirements while drastically simplifying our architecture.

If you are starting out on your Argo Workflows journey, you’ll soon find yourself surrounded by the word ‘template’. Templates are a fundamental cornerstone of an Argo Workflow and allow you to define the work to be performed.

In this talk, we'll explore the versatile world of Argo Workflow template types. We'll break down the different types, demystifying their use cases and best practices. While container templates are widely used and referenced in the documentation, we'll delve into the lesser-known but equally powerful template types such as the http template, container sets and resource templates.

Along the way, we’ll also tackle common misconceptions - including the surprising difference between a workflowTemplate and a Workflow Template.

Whether you’re a seasoned professional or new to the world of Argo Workflows, expect to leave with a deeper understanding of Workflow Templates - ready to apply their versatility and power to solve complex workflow challenges.

Time series data is exploding across industries - from IoT sensors and financial markets to application monitoring and user behavior analytics. As organizations grapple with processing these massive datasets, many overlook a powerful solution hiding in plain sight: Argo Workflows. This talk demonstrates how Argo Workflows transforms time series analysis from a resource-intensive challenge into a streamlined, scalable process in Kubernetes environments.

We'll dive deep into real-world architectures that leverage Argo Workflows' DAG-based execution model for efficient time series processing. You'll learn practical patterns for data partitioning, parallel processing, and resource optimization that we've battle-tested with petabyte-scale datasets. Through live demos and code examples, we'll explore how to build resilient pipelines that can handle everything from real-time sensor data to historical trend analysis.