
This is Set Agenda about the training.
Explore the Argo workflow architecture, detailing how the workflow controller reconciles tasks and queues while the Argo server coordinates workers, the UI, the CLI, and APIs across Kubernetes.
Learn to create and run an Argo workflow with YAML in the UI and CLI, including API version, kind, metadata, spec, service account, namespace, entrypoint, and parameters.
Discover how the script type template in Argo workflow runs a script inside a container using the source field. Compare it to container type; explore lab five with Python scripts.
Learn how to use output parameters in Argo workflows to generate data in one step and pass it to subsequent steps, not storing artifacts in S3, enabling flexible, conditional pipelines.
Explore loops in Argo workflows, including with sequence, with items, and JSON object-based iterations, enabling dynamic runs and parameterized templates.
Explore error handling and work management in Argo workflows, detailing retry policy with exponential backoff and limit, plus exit handlers and active deadline seconds for timeouts.
Learn how Argo workflow supports cron workflow scheduling by defining a cron schedule that runs a set of tasks automatically, with options like concurrent policy and timezone.
Argo Workflows is an open-source container-native workflow engine designed for orchestrating parallel jobs on Kubernetes. It allows users to define and manage complex workflows through a YAML-based syntax, enabling the automation of tasks and processes across a Kubernetes cluster.
In this module, we will cover the basic to advanced syntax and options available for Argo Workflows. Each session includes labs that will assist you in gaining a better understanding of the product. This covers all the syntax aspects and use cases as well.
Prior knowledge of Kubernetes is required before you start working on Argo Workflows, as it builds upon Kubernetes concepts and leverages its features for workflow orchestration. The setup must also be performed on Kubernetes.
By the end of this module, you will have a comprehensive understanding of Argo Workflows, enabling you to design, implement, and manage complex workflows on Kubernetes with confidence. These workflows facilitate the use of containers for each step.
Please try all the labs mentioned in the document. The hands-on labs are essential for applying the theoretical knowledge covered in the sessions, ensuring you gain practical experience with Argo Workflows.
If there are any issues with the lab, please contact me at amit@openwriteup.com.