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Asked: 2024-09-27T08:05:12+05:30 In:

I’m experiencing an issue where my Argo workflows are remaining in a pending state and not progressing to execution. I’ve reviewed the configurations and logs, but can’t seem to identify the root cause. Has anyone else encountered this problem and found a solution? Any insights or troubleshooting steps would be greatly appreciated.

I’ve run into a bit of a snag with my Argo workflows, and it’s driving me a little crazy. I’ve got these workflows sitting in a pending state, and no matter what I do, they just won’t budge toward execution. It’s like they’re just stuck in limbo!

I’ve gone through the usual checks—looked over my configurations several times, double-checked the resource quotas, and scoured the logs for any red flags. Everything seems to be in order at first glance, but the workflows just won’t kick off. It’s very frustrating because I’m not sure if it’s an environment issue, a configuration misstep on my part, or possibly something else.

One thing I noticed is that the pods related to the workflows are not being created. I’ve tried restarting the Argo controller, assuming that maybe it was just a momentary glitch, but that didn’t help either. My Kubernetes cluster seems to be running fine, and other pods are being created without any issue, which leads me to believe that the problem is isolated to the workflows.

I’ve considered the possibility that it might be a permissions issue. I’ve checked the service account associated with the workflows, and everything appears to check out. But who knows? Maybe I’m missing something obvious here. The documentation suggests that various conditions must be satisfied for a workflow to start, but I’m not sure if there’s something specific I should be looking for.

So, has anyone else run into this kind of problem with Argo workflows? What did you do to get your workflows out of that annoying pending state? Any tips or troubleshooting steps would be super helpful. I’d love to hear about any experiences you’ve had, or suggestions you might have that could help me solve this mystery. It’s definitely becoming a bit of a headache, so any insights would be greatly appreciated!

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    2 Answers

    1. Hey there!

      So, I totally get where you’re coming from with those Argo workflows being stuck in pending mode. It’s super annoying when everything looks good, but things just don’t want to budge. Here are a few things I’d suggest checking out:

      • Workflow Conditions: Sometimes, there are specific conditions that have to be met for workflows to start. You might want to check if any of the conditions in your workflows are blocking them from starting.
      • Resource Requests: Double-check the resource requests in your workflow specs. If they’re asking for more resources than your cluster has available, that could definitely keep them in a pending state.
      • Service Account Permissions: Even if the service account looks fine at first glance, ensure it has the right permissions to create pods. Maybe check if any RBAC policies could be interfering?
      • Namespace Quotas: You mentioned checking resource quotas, so just make sure that you’re looking at the right namespace! Sometimes it can be easy to overlook that.
      • Event Logs: Besides logs, check out the events for the workflows using `kubectl describe workflow `. It might give you some clues as to why they can’t start.
      • Workflow Controller Logs: If you’ve restarted the controller and it didn’t help, maybe check the logs one more time for any hidden errors or warnings that could give you a hint about what’s going on.

      If all else fails, it might be worth posting your setup details on forums or GitHub discussions for Argo. People there are usually super helpful!

      Good luck!

    2. The issue you’re experiencing with your Argo workflows being stuck in a pending state can be frustrating, especially when you’ve already done a thorough check of configurations and resource quotas. One area you might want to dig deeper into is the Argo controller’s logs specifically for any warnings or errors related to workflow scheduling. If you haven’t already, ensure that the `` service is up and running correctly. Sometimes, problems can occur if the controller isn’t communicating well with the Kubernetes API or if its resource requests are too high for the cluster to allocate. Additionally, make sure that the namespaces used in your workflows aren’t facing restrictions that could prevent the workflows from running, such as role-based access control (RBAC) issues.

      Another angle to consider would be the potential for unsatisfied workflow dependencies, particularly if your workflows rely on other resources being in a ready state before they can start. You should check if there are any pre-requisites or other workflows that need to finish executing. Furthermore, reviewing the version compatibility between Argo Workflows and your Kubernetes setup might unveil underlying issues, especially if recent upgrades have occurred. If you suspect permissions may be the cause, using tools like `kubectl auth can-i` can help confirm whether the service account has the necessary permissions to create and manage workflow-related resources. Lastly, engaging with the Argo community through forums or GitHub issues could provide insights or similar experiences from other users that might shine a light on your dilemma.

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