@Marvin I just installed prefect on kuberenetes with helm on a selfhosted remote server. How to sent a flow to that prefect server

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Great question — you’re almost there. In Prefect 3.x, “sending a flow” to your self-hosted Server means 1) pointing your local environment at that API, 2) creating a work pool, 3) running a worker that polls that pool, and 4) creating a deployment for your flow. Quick questions to tailor the steps: - Do you have only the Prefect Server/UI installed via Helm, or did you also install a Kubernetes worker? - What URL do you use to access your Prefect UI (e.g., https://prefect.example.com or http//<ip>4200)? Assuming you have only the Server/UI installed, here’s the minimal path: 1) Point your local Prefect to your remote Server - Set the API URL on your machine so CLI and Python calls talk to your server:

prefect config set PREFECT_API_URL="http://<your-host-or-domain>:4200/api"

Docs: Self-hosted Server on Kubernetes (Helm) 2) Create a Kubernetes work pool (one-time)

prefect work-pool create my-k8s --type kubernetes

Concepts: Work pools and Workers 3) Start a worker that polls that pool - Best practice: run the worker inside your cluster (via Helm). If you haven’t installed a worker yet, install the Prefect Kubernetes worker Helm chart and configure it with: - PREFECT_API_URL pointing to your server (e.g., http//<host>4200/api) - The work pool name you created (e.g., my-k8s) - Reference: Deploy a worker using Helm (Kubernetes) - For a quick test (with kubeconfig and permissions), you can also start a worker from your machine:

prefect worker start -p my-k8s

4) Create and register a deployment for your flow Option A: Python API (works anywhere, minimal config)

from prefect import flow
from prefect.flows import Flow

@flow
def my_flow():
    print("hello from k8s")

# Run this once to register the deployment with your server
deployment_id = Flow.from_source(
    source="<https://github.com/<owner>/<repo>>",
    entrypoint="flows/my_flow.py:my_flow",
).deploy(
    name="k8s",
    work_pool_name="my-k8s",
)

print("Deployment created:", deployment_id)

Option B: CLI from your project root (prefect.yaml-based) - From your project root, you can run:

prefect deploy ./flows/my_flow.py:my_flow --name k8s

- If your project config doesn’t set a default work pool, the CLI will prompt you to choose one; select

my-k8s

. Docs: prefect.yaml and deployments 5) Trigger a run

prefect deployment run "my_flow/k8s" --watch

You should see the flow run queuing in your Server UI and picked up by the worker. Troubleshooting checklist - If the run stays “Scheduled”: confirm a worker is running and polling the correct pool (

my-k8s

). - If you don’t see deployments: ensure

PREFECT_API_URL

is set both in your local env (for deploy) and in the worker environment (so it can talk to the server). - Networking: verify your Server’s API is reachable at

http(s)://<host-or-domain>:4200/api

(or your Ingress URL). For quick local access, you can also port-forward:

kubectl -n <namespace> port-forward svc/prefect-server 4200:4200

If you share your Server URL and whether you’ve installed a worker already, I can provide an exact Helm values snippet for the worker to point at your server and pool.

how to authenticate to the repote server