Hands-On Guide to Argo Workflows on Kubernetes

Learn to set up a local minikube Kubernetes cluster on Windows 10 with kubectl and hypervisors like VirtualBox or Hyper-V. Consult the project website for Linux or Mac OS setup.

Install kubectl on Windows 10 by downloading the latest release, placing it in a folder, and updating the PATH environment variable. Then verify with kubectl version to confirm installation.

Install minikube on Windows 10 by downloading the latest release from GitHub, running the installer, and verifying the installed version with minikube version on the command line (version 1.16.0).

Select a hypervisor by choosing between Hyper-V and VirtualBox; Hyper-V is an optional Windows feature available only on Windows 10 Enterprise, Pro, and Education, not Home, so pick one.

Enable Hyper-V on Windows 10 by running an administrator command line, checking with system info, setting hypervisorlaunchtype to auto, enabling Hyper-V in Windows features, and rebooting to verify.

Start minikube with Hyper-V on Windows 10 to create a local cluster, then use kubectl to list nodes and confirm they are ready, and finally stop the cluster.

Disable Hyper-V on Windows 10, verify the change with system info, install VirTra Box, then download and install VirtualBox for Windows hosts and launch it.

Learn to start minikube on Windows 10 using VirtualBox, auto-detect the VirtualBox driver, delete any existing cluster, and verify nodes with kubectl before ready to go.

Review the latest changes before installing Argo on Kubernetes: switch the Argo server UI to http and access it at http://localhost:2746.

Install Argo workflows on the Mineka cluster by creating the Aagot namespace, applying the quickstart manifest, and verifying the workflow controller, Argo server, object storage, and database support.

Open the Argo UI via port-forward, explore workflows, templates, and cluster templates, check archived runs, view user info, access API docs and help.

Deploy and run your first Argo workflow in the Kubernetes cluster, monitor its execution in the Argo UI, and review the YAML definition, template, and output artifacts.

Define the core concept of a workflow definition using a human readable language for data serialization, including header, apiVersion, kind, metadata, and the spec with templates and entry point.

Explore template definitions in Argo Workflows on Kubernetes, including container templates, description templates with a script source, resource templates that manage cluster resources, and suspend templates to pause execution.

Create a workflow with a container template in Argo on Kubernetes, defining a unique name and entry point, using a Python 3.8 image and an echo command.

Create a workflow from a script template in Argo Workflows on Kubernetes, define a python 3.8 slim image, and run a script that prints the script template execution was successful.

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Learn to define a resource template to create a workflow that itself spawns another workflow, using a test template and a Python script that prints a message.

Explore argo workflows template invocators and indicators that call templates; use insteps to define tasks as list of lists, with outer lists sequential and analysts parallel via deck dependency graph.

Build an Argo workflow on Kubernetes using the steps template as the entry point, with a script task template using Python 3.8 slim and three sequential steps.

Demonstrate running step two and step three in parallel using the steps template, then execute step four after both finish.

Explore how a suspend template introduces a 10-second delay into an Argo workflow, coordinating serial and parallel steps with a dedicated delay template before step four.

Explore rewriting a workflow from steps to the dag template in Argo Workflows on Kubernetes, defining tasks, naming them, and setting dependencies to create a directed acyclic graph.

Demonstrate four task types in argo workflows on kubernetes, including script templates, standard output tasks, and resource templates, with dependency rules and a five-second suspended template delay.

Build an Argo workflow on Kubernetes with a dag-based deck template, featuring script, container, and resource tasks, plus a five-second delay and dependencies.

Learn how to archive workflow logs to MinIO object storage using Argo Workflows, including configuring artifact repositories, setting archive logs to true, and resubmitting workflows to generate and store artifacts.

Learn to install the Argo Seelie CLI on Windows, Mac, and Linux by following the Argo releases instructions, set environment variables, and verify the installation with argo version.

Explore using input parameters in Argo workflows by defining task and deck templates with inputs, passing values via arguments, and overriding with terminal flags or parameter files.

Learn to pass the output of a script template as input to another task in an Argo workflow, using a script template, printing results, and reusing outputs.

Learn to explicitly define and use output parameters in Argo workflows on Kubernetes, enabling a task's output to become another task's input.

Demonstrates exchanging parameters between tasks in an Argo workflow by writing a file in one task and reading it as input in subsequent tasks.

Save files as artifacts to object storage and wire them as inputs in an Argo workflow, demonstrating artifact creation, passing, and retrieval.

Learn to create a Kubernetes secret from a file and reference it as an environment variable in Argo Workflows, enabling secure access to a password during workflow execution.

Learn to mount a Kubernetes secret as a volume in an Argo workflow, configure a secret volume, and access the secret data from a container to print it.

Rename the workflow to workflow loop and implement a parallel loop over a list of elements using a task template with input parameters in Argo Workflows.

Loop over a list of dictionaries to assign an extractor for each table and print the chosen extractor, demonstrating Argo Workflows looping with sets.

Adapt Argo workflows on Kubernetes by using an input parameter named list instead of hard-coded values, with JSON-formatted values to loop over sets or dictionaries.

Create a dynamic loop inside an Argo workflow by generating a list in a task, then iterate over it with a task template, and wire dependencies to process each item.

Learn to use conditionals in Argo Workflows to route execution based on a decision task, selecting task a or task b and printing the outcome.

Explore the depends logic in Argo workflows on Kubernetes. Replace static dependencies with depends, and trigger task execution based on statuses like succeeded, failed, or skipped, using templates.

Explore defense logic in Argo workflows by using task results such as succeeded, failed, and skipped with depends and operators, and note dependencies cannot be in the same task group.

Explore how to implement a retry strategy in Argo workflows on Kubernetes by configuring max retries, backoff settings, and max duration to automatically re-run failed tasks.

Explore recursion in Argo Workflows on Kubernetes by simulating dice rolls with a deck of templates, a roll dice task, and a conditional re-run until a six is achieved.

Build an Argo workflow on Kubernetes that reads emails and detects a keyword to trigger an email notification. Manage secrets and artifacts, processing emails in parallel.

Demonstrate building and executing an argo workflow on kubernetes, including creating a bucket source, secret with keys, reading emails, looping results, and producing artifacts and notifications.

Explore resource types in Argo workflows on Kubernetes, including executable workflows, workflow templates, Chron workflows, and cluster workflow templates. Learn how templates define and instantiate workflows across namespaces.

discover how to create and use workflow templates in argo by renaming a deck to a template, submitting workflows, and updating templates via delete-and-recreate or apply.

Learn to configure a cron workflow in Argo on Kubernetes by editing the workflow template, setting the schedule, concurrency policy, and starting deadline, and managing with the CLI and UI.

Create and compare cluster workflow templates in Argo on Kubernetes, showing how cluster templates access all namespaces versus namespace-scoped workflow templates, and illustrating commands and UI steps.

Learn to reference workflow templates from a cron workflow using workflow template ref, set a one-minute schedule, and deploy to run as a combined workflow.

Create a master Argo workflow on Kubernetes that schedules hourly runs, triggers two workflow templates, and orchestrates nested workflows with success and failure conditions.

Demonstrates configuring AWS S3 as the artifact repository for Argo Workflows on Kubernetes, including creating a bucket, managing credentials, and wiring secrets to store workflow outputs.

Configure Argo Workflows on Kubernetes to use an AWS S3 bucket as the default repository for logging and artifacts, then submit the workflow and confirm logs and artifacts are stored.

Archive workflows by submitting a workflow artifact template and review archived items in the UI. The archived data resides in a PostgreSQL secret database, configurable via the persistence archive setting.

Learn how to manage workflows in specific namespaces using argo submit, with or without namespace flags, and enforce namespace via yaml metadata.

Learn how to configure kubernetes service accounts for argo workflows, bind roles to grant permissions, and choose between command-line or spec-based service account usage to ensure secure workflow execution.

Create a master chron workflow that runs daily at 10 a.m., executing three tasks: two call a workflow template exercise with bomb and attack, then detect click in C3 email.

Demonstrates solving exercise 3 by building an Argo workflow on Kubernetes, converting to a workflow template, with templates and parameters to detect bombs, attack, and click in emails.

Master core Argo workflows on Kubernetes by applying inputs, parameters, artifacts, and secrets as environment variables and mounted volumes, with loops, conditionals, and retries, then leverage templates, namespaces, and logging.