argo restful api get workflow pod name

Daniel Parker

3 min read

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01-03-2025

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Getting the pod name associated with a specific step in an Argo Workflow can be crucial for debugging, monitoring, or interacting directly with containers. This article details how to retrieve this information using the Argo Workflows RESTful API. We'll cover the necessary API calls, potential challenges, and best practices.

Understanding Argo Workflows and Pods

Argo Workflows orchestrates complex workflows by defining a series of steps, often represented as containers running within Kubernetes pods. Each step (or template) in your workflow executes within its own pod. Accessing the pod name allows you to examine logs, execute commands within the container, or monitor resource usage.

Retrieving Pod Names: The API Approach

The Argo Workflows API doesn't directly expose a single endpoint to fetch a pod name by workflow step. Instead, we need a multi-step approach leveraging the /workflows and /pods endpoints.

Step 1: Identify the Workflow and Step

First, you need the unique name of your Argo workflow and the specific step (template name) whose pod you want to inspect. This information is usually available from the Argo UI or through other API calls related to workflow status.

Step 2: Fetch Workflow Details

Use the Argo Workflows API to retrieve details about the specified workflow. This endpoint will provide information about the workflow's execution, including its nodes (steps).

curl -s -H "Content-Type: application/json" \
     http://<argo-server-url>/api/v1/workflows/<workflow-name> | jq

Replace <argo-server-url> with your Argo server URL and <workflow-name> with your workflow's name. The JSON response will include a status section containing information on the workflow's nodes.

Step 3: Locate the Pod Information

The JSON response from Step 2 will show nodes representing the workflow's steps. Each node containing a running container will have information to locate the pod. This usually involves parsing the nodeName field in the startedAt block (if the step has started) and then referencing it using Argo's pod API. The exact structure might vary slightly depending on the Argo version.

Step 4: Access the Pod Information using the Pod API

Once you've found the nodeName from Step 3 (often within the startedAt field), you can fetch the pod information.

curl -s -H "Content-Type: application/json" \
     http://<argo-server-url>/api/v1/pods/<nodeName> | jq

Replace <argo-server-url> with your Argo server URL and <nodeName> with the value you obtained in Step 3. The response should contain the pod name, along with various other details.

Example Scenario: Parsing the JSON

The exact JSON structure will depend on your Argo version and workflow configuration. However, you’ll typically need tools like jq to parse the JSON response and extract the relevant nodeName from the node's startedAt field. If a step has already finished, it might show up in the finishedAt field.

Handling Asynchronous Operations

Remember that workflow steps might not be running immediately. The API response will reflect the current state. You may need to poll the API periodically if you need real-time updates.

Alternative Approaches and Considerations

• Argo UI: For simpler workflows, directly inspecting the Argo UI is often the quickest way to find the pod name.

• kubectl: If you have Kubernetes access, kubectl can be a powerful tool to directly interact with pods. You could use labels or other identifiers to locate the pod.

• Error Handling: Always include robust error handling in your scripts. Workflows might fail or steps might not have associated pods.

Conclusion

Retrieving the pod name associated with an Argo Workflow step requires a combination of API calls and JSON parsing. While not a single direct API endpoint, this multi-step approach provides the needed information. Remember to handle asynchronous behavior and potential errors for a robust solution. By combining the API calls with tools like jq and careful parsing, you can effectively monitor and manage your Argo workflows.