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# GCP Environment Workflow

This workflow provisions and configures a complete GCP-based Kubernetes environment using the `koreo.dev` workflow engine and custom `ResourceFunction` and `ValueFunction` modules.
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This doesn't actually create a GKE cluster though, just the network environment needed for one, so this description is a bit misleading I think.

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ope, good catch, that is leftover from when I split it out

- rangeName: servicesrange
ipCidrRange: 10.11.0.0/16
- rangeName: clusterrange
ipCidrRange: 10.12.0.0/16
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Should the secondary ranges be made inputs as well?

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# Federated GKE Workflow

This workflow provisions and configures a complete GCP-based Kubernetes environment using the `koreo.dev` workflow engine and custom `ResourceFunction` and `ValueFunction` modules.
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This description should probably mention what we mean by "federated" here, i.e. it sets up a GKE cluster that Koreo itself can manage resources within from a remote cluster.

- Each resource function should be implemented to create or reconcile its respective GCP or K8s object.
- The `metadata` step centralizes naming and labeling to ensure consistent tagging and traceability.

### Notes
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Can we just combine the two notes sections?


### Notes
- Ensure Koreo service account has permissions to edit IAM policy
- I made it owner of the account, but this could be restricted I am sure.
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Or did you intend to clean these notes up to be more consumable?


for pod in pykube.Pod.objects(api).filter(namespace="kube-system"):
print(pod.name)
```
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Are you planning to open source the sidecar you wrote that does this?

name: federatedgke.example.koreo.dev
spec:
scope: Namespaced
group: acme.example.com
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I think you changed this to example.koreo.dev in the other example?

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---
apiVersion: example.koreo.dev/v1
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Your CRD uses acme

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3 participants