GKE Core platform updates and enhancements #82
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arueth
requested review from
ferrarimarco,
laurentgrangeau,
kenthua and
gushob21
| enable_private_nodes = true | ||
| } | ||
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| name = "default-pool" |
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Is it possible to have a variable here? It will be useful for the federated learning use case.
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This has to be default-pool, it gets deleted because remove_default_node_pool = true
| node_config { | ||
| machine_type = "e2-standard-4" | ||
| machine_type = var.cluster_system_node_pool_machine_type | ||
| service_account = google_service_account.cluster.email |
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Is it possible to have a variable here and use google_service_account.cluster.email is the user didn't specify anything? This will be useful for the federated learning use case
| cluster = google_container_cluster.cluster.name | ||
| initial_node_count = 1 | ||
| location = var.cluster_region | ||
| name = "system" |
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Is it possible to have a variable here in order to customize the name? It will be useful for the federated learning use case. Thanks
| node_config { | ||
| machine_type = "e2-standard-4" | ||
| machine_type = var.cluster_system_node_pool_machine_type |
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Just checking: we're reusing the same variable as we're using in the system node pool below.
| enable_private_nodes = true | ||
| } | ||
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| name = "default-pool" | ||
| node_config { |
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Is it possible to add variables to specify custom labels and taints for this node pool? This will be useful for the federated learning use case.
| location = var.cluster_region | ||
| name = local.cluster_name | ||
| project = var.cluster_project_id | ||
| node_config { |
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Is it possible to add variables to specify custom labels and taints for this node pool? This will be useful for the federated learning use case.
| "resource-type" : "system" | ||
| } | ||
| machine_type = var.cluster_system_node_pool_machine_type | ||
| service_account = google_service_account.cluster.email |
There was a problem hiding this comment.
Is it possible to have a variable here and use google_service_account.cluster.email is the user didn't specify anything? This will be useful for the federated learning use case
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