What you'll learn:
- You will learn how to install a minikube cluster with Argo Workflows on your local machine.
- You will get to know the core concepts of Argo Workflows and how to use them creating workflows.
- You will be able to communicate with the Argo server using the kubectl CLI and how to use the Argo Server UI.
This is an introductory course to the full course Hands-On Guide to Argo Workflows on Kubernetes.
Argo Workflows is a container native workflow engine for orchestrating jobs in Kubernetes. This means that complex workflows can be created and executed completely in a Kubernetes cluster.
It provides a mature user interface, which makes operation and monitoring very easy and clear. There is native artifact support, whereby it is possible to use completely different artifact repositories (Minio, AWS S3, Artifactory, HDFS, OSS, HTTP, Git, Google Cloud Service, raw).
Templates and cron workflows can be created, with which individual components can be created and combined into complex workflows. This means that composability is given. Furthermore, workflows can be archived and Argo provides a REST API and an Argo CLI tool, which makes communication with the Argo server easy.
It is also worth mentioning that Argo Workflows can be used to manage thousands of parallel pods and workflows within a Kubernetes cluster. And robust repetition mechanisms ensure a high level of reliability.
There is already a large, global community that is growing steadily. Just to name IBM, SAP and NVIDIA. It is mainly used for machine learning, ETL, Batch - and data processing and for CI / CD. And what is also very important - it is open source and a project of the Cloud Native Computing Foundation.
Upon successful completion of the course, you will be able to create workflows using the core concepts of Argo Workflows. You will be confident to use the kubectl CLI and the Argo Server UI in order to communicate with the Argo Server and manage your workflows.
