argo-workflows | Workflow engine for Kubernetes | BPM library

I am trying to format my workflow per these instructions (https://argoproj.github.io/argo-workflows/workflow-inputs/#using-previous-step-outputs-as-inputs) but cannot seem to get it right. Specifically, I am trying to imitate "Using Previous Step Outputs As Inputs"

I have included my workflow below. In this version, I have added a path to the inputs.artifacts because the error requests one. The error I am now receiving is:

I am trying to install argo workflows and looking at the documentation I can see 3 different types of installation https://argoproj.github.io/argo-workflows/installation/.

Can anybody give some clarity on the namespace install vs managed namespace install? If its a managed namespace, how can I tell the managed namespace? Should I edit the k8's manifest for deployment? What benefit it can provide compared to simple namespace install ?

General question here, wondering if anyone has any ideas or experience trying to achieve something I am right now. I'm not entirely sure if its even possible in the argo workflow system...

I'm wondering if it is possible to continue a workflow regardless if a dynamic fanout has finished. By dynamic fanout I mean that B1/B2/B3 can go to B30 potentially.

I want to see if C1 can start when B1 has finished. The B stage is creating a small file which then in C stage I need to run an api request that it has finished and upload said file. But in this scenario B2/B3 still are processing.

And finally, D1 would have to wait for all of C1/2/3-C# to finish to complete

Diagram what I'm trying to achieve

I am new to the argo universe and was trying to set up Argo Workflows https://github.com/argoproj/argo-workflows/blob/master/docs/quick-start.md#install-argo-workflows .

I have installed the argo CLI from the page : https://github.com/argoproj/argo-workflows/releases/latest . I was trying it in my minikube setup and I have my kubectl already configured to the minikube cluster. I am able to hit argo commands without any issues after putting it in my local bin folder.

How does it work? Where do the argo CLI is connecting to operate?

Is there a way to provide an image name for the container template dynamically based on its input parameters?

We have more than 30 different tasks each with its own image and that should be invoked identically in a workflow. The number may vary each run depending on the output of a previous task. So we don't want to or even can't just hardcode them inside workflow YAML.

An easy solution would be to provide the image field for the container depending on the input parameter and have the same template for each of these tasks. But looks like it's impossible. This workflow doesn't work:

One of our Argo Workflow steps may hit a rate limit and I want to be able to tell argo how long it should wait until the next retry.

Is there a way to do it?

I've seen Retries on the documentation but it only talks about retry count and backoff strategies and it doesn't look like it could be parameterized.

I have an Argo workflow with dynamic fan-out tasks that do some map operation (in a Map-Reduce meaning context). I want to create a reducer that aggregates their results. It's possible to do that when the outputs of each mapper are small and can be put as an output parameter. See this SO question-answer for the description of how to do it.

But how to aggregate output artifacts with Argo without writing custom logic of writing them to some storage in each mapper and read from it in reducer?

I am trying to delete (and recreate) the Argo namespace, but it won't fully delete because I tried launching an eventsource and eventbus there. Now these will not delete.

I have tried to delete them via yaml and individually - no success yet.

The frustrating result is that I cannot re-launch argo

The main question is if there is a way to finish a pod from the client-go sdk, I'm not trying to delete a pod, I just want to finish it with a Phase-Status: Completed.

In the code, I'm trying to update the pod phase but It doesn't work, It does not return an error or panic but The pod does not finish. My code: