gke-a3-megagpu.yaml

# Copyright 2024 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
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---

blueprint_name: gke-a3-mega

vars:
  project_id:  ## Set GCP Project ID Here ##
  deployment_name: gke-a3-mega
  region: us-central1
  zone: us-central1-c

  # Cidr block containing the IP of the machine calling terraform.
  # The following line must be updated for this example to work.
  authorized_cidr: <your-ip-address>/32

deployment_groups:
- group: primary
  modules:
  - id: network1
    source: modules/network/vpc
    settings:
      subnetwork_name: gke-subnet-a3-mega
      secondary_ranges:
        gke-subnet-a3-mega:
        - range_name: pods
          ip_cidr_range: 10.4.0.0/14
        - range_name: services
          ip_cidr_range: 10.0.32.0/20

  - id: gke_service_account
    source: community/modules/project/service-account
    settings:
      name: gke-sa
      project_roles:
      - logging.logWriter
      - monitoring.metricWriter
      - monitoring.viewer
      - stackdriver.resourceMetadata.writer
      - storage.objectViewer
      - artifactregistry.reader

  - id: gpunets
    source: modules/network/multivpc
    settings:
      network_name_prefix: $(vars.deployment_name)-gpunet
      global_ip_address_range: 192.169.0.0/16
      network_count: 8
      subnetwork_cidr_suffix: 24

  - id: gke_cluster
    source: modules/scheduler/gke-cluster
    use: [network1, gpunets, gke_service_account]
    settings:
      enable_private_endpoint: false  # Allows for access from authorized public IPs
      master_authorized_networks:
      - cidr_block: $(vars.authorized_cidr)  # Allows your machine run kubectl command. It's required for the multi-network setup.
        display_name: "kubectl-access-network"
    outputs: [instructions]

  - id: a3_megagpu_pool
    source: modules/compute/gke-node-pool
    use: [gke_cluster, gpunets, gke_service_account]
    settings:
      machine_type: a3-megagpu-8g
      autoscaling_total_min_nodes: 2
      zones: [$(vars.zone)]
    outputs: [instructions]

  - id: workload_manager_install
    source: modules/management/kubectl-apply
    use: [gke_cluster]
    settings:
      kueue:
        install: true
      jobset:
        install: true