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For the cons side of a large shared cluster, the article mentions cluster-wide services like DNS and shared resources like CPU and memory. I would like to propose mentioning also that certain Kubernetes resource kinds are not namespaced and therefore cannot be administered in isolation.
Example use case for custom resource definition (CRD) resource kind:
Two users are working in separate namespaces in a shared cluster. Users would like to deploy a particular version of operator "SampleDB". The operator requires installation of CRDs, which are not namespaced and therefore cannot be managed independently by the users working on the shared cluster. The deployment and version upgrades need to be done by the cluster administrator in coordination with the users.
The text was updated successfully, but these errors were encountered:
@tsaarni, thanks for the suggestions. This is definitely an important point that we missed. We will check and then attempt to include it in the article.
Thank you for very informational and clearly written article https://learnk8s.io/how-many-clusters.
For the cons side of a large shared cluster, the article mentions cluster-wide services like DNS and shared resources like CPU and memory. I would like to propose mentioning also that certain Kubernetes resource kinds are not namespaced and therefore cannot be administered in isolation.
Example use case for custom resource definition (CRD) resource kind:
Two users are working in separate namespaces in a shared cluster. Users would like to deploy a particular version of operator "SampleDB". The operator requires installation of CRDs, which are not namespaced and therefore cannot be managed independently by the users working on the shared cluster. The deployment and version upgrades need to be done by the cluster administrator in coordination with the users.
The text was updated successfully, but these errors were encountered: