Scaling Time Series Analysis With Argo Workflows: Patterns and Practices

This lightning talk explores how Argo Workflows can be leveraged to transform time series analysis from a resource-intensive challenge into a streamlined, scalable process within Kubernetes environments. Discover practical patterns and practices for handling the explosion of time series data across industries including IoT sensors, financial markets, application monitoring, and user behavior analytics. Learn about real-world architectures that utilize Argo Workflows' DAG-based execution model for efficient processing of massive datasets. Gain insights into data partitioning techniques, parallel processing strategies, and resource optimization approaches that have been battle-tested with petabyte-scale datasets. Through demonstrations and code examples, understand how to build resilient pipelines capable of processing both real-time sensor data and historical trend analysis in Kubernetes environments.