| #!/usr/bin/python3 |
| |
| # ***************************************************************************** |
| # |
| # Licensed to the Apache Software Foundation (ASF) under one |
| # or more contributor license agreements. See the NOTICE file |
| # distributed with this work for additional information |
| # regarding copyright ownership. The ASF licenses this file |
| # to you under the Apache License, Version 2.0 (the |
| # "License"); you may not use this file except in compliance |
| # with the License. You may obtain a copy of the License at |
| # |
| # 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, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| # KIND, either express or implied. See the License for the |
| # specific language governing permissions and limitations |
| # under the License. |
| # |
| # ****************************************************************************** |
| |
| import datalab.fab |
| import datalab.actions_lib |
| import datalab.meta_lib |
| import json |
| import logging |
| import os |
| import sys |
| import traceback |
| import subprocess |
| from fabric import * |
| |
| if __name__ == "__main__": |
| instance_class = 'notebook' |
| local_log_filename = "{}_{}_{}.log".format(os.environ['conf_resource'], os.environ['project_name'], |
| os.environ['request_id']) |
| local_log_filepath = "/logs/" + os.environ['conf_resource'] + "/" + local_log_filename |
| logging.basicConfig(format='%(levelname)-8s [%(asctime)s] %(message)s', |
| level=logging.DEBUG, |
| filename=local_log_filepath) |
| try: |
| GCPMeta = datalab.meta_lib.GCPMeta() |
| GCPActions = datalab.actions_lib.GCPActions() |
| print('Generating infrastructure names and tags') |
| notebook_config = dict() |
| notebook_config['service_base_name'] = (os.environ['conf_service_base_name']) |
| notebook_config['edge_user_name'] = (os.environ['edge_user_name']) |
| notebook_config['project_name'] = (os.environ['project_name']).replace('_', '-').lower() |
| notebook_config['project_tag'] = notebook_config['project_name'] |
| notebook_config['endpoint_name'] = os.environ['endpoint_name'].replace('_', '-').lower() |
| notebook_config['endpoint_tag'] = notebook_config['endpoint_name'] |
| notebook_config['region'] = os.environ['gcp_region'] |
| notebook_config['zone'] = os.environ['gcp_zone'] |
| |
| edge_status = GCPMeta.get_instance_status('{0}-{1}-{2}-edge'.format(notebook_config['service_base_name'], |
| notebook_config['project_name'], |
| notebook_config['endpoint_tag'])) |
| if edge_status != 'RUNNING': |
| logging.info('ERROR: Edge node is unavailable! Aborting...') |
| print('ERROR: Edge node is unavailable! Aborting...') |
| ssn_hostname = GCPMeta.get_private_ip_address(notebook_config['service_base_name'] + '-ssn') |
| datalab.fab.put_resource_status('edge', 'Unavailable', os.environ['ssn_datalab_path'], |
| os.environ['conf_os_user'], |
| ssn_hostname) |
| datalab.fab.append_result("Edge node is unavailable") |
| sys.exit(1) |
| |
| try: |
| if os.environ['gcp_vpc_name'] == '': |
| raise KeyError |
| else: |
| notebook_config['vpc_name'] = os.environ['gcp_vpc_name'] |
| except KeyError: |
| notebook_config['vpc_name'] = '{}-vpc'.format(notebook_config['service_base_name']) |
| try: |
| notebook_config['exploratory_name'] = (os.environ['exploratory_name']).replace('_', '-').lower() |
| except: |
| notebook_config['exploratory_name'] = '' |
| notebook_config['subnet_name'] = '{0}-{1}-{2}-subnet'.format(notebook_config['service_base_name'], |
| notebook_config['project_name'], |
| notebook_config['endpoint_tag']) |
| notebook_config['instance_size'] = os.environ['gcp_notebook_instance_size'] |
| notebook_config['ssh_key_path'] = '{0}{1}.pem'.format(os.environ['conf_key_dir'], os.environ['conf_key_name']) |
| notebook_config['notebook_service_account_name'] = '{}-{}-{}-ps-sa'.format(notebook_config['service_base_name'], |
| notebook_config['project_name'], |
| notebook_config['endpoint_name']) |
| |
| if os.environ['conf_os_family'] == 'debian': |
| notebook_config['initial_user'] = 'ubuntu' |
| notebook_config['sudo_group'] = 'sudo' |
| if os.environ['conf_os_family'] == 'redhat': |
| notebook_config['initial_user'] = 'ec2-user' |
| notebook_config['sudo_group'] = 'wheel' |
| notebook_config['instance_name'] = '{0}-{1}-{2}-nb-{3}'.format(notebook_config['service_base_name'], |
| notebook_config['project_name'], |
| notebook_config['endpoint_name'], |
| notebook_config['exploratory_name']) |
| notebook_config['primary_disk_size'] = (lambda x: '60' if x == 'deeplearning' else '20')( |
| os.environ['application']) |
| notebook_config['secondary_disk_size'] = os.environ['notebook_disk_size'] |
| |
| notebook_config['shared_image_enabled'] = os.environ['conf_shared_image_enabled'] |
| if notebook_config['shared_image_enabled'] == 'false': |
| notebook_config['expected_primary_image_name'] = '{}-{}-{}-{}-primary-image'.format( |
| notebook_config['service_base_name'], notebook_config['project_name'], notebook_config['endpoint_tag'], |
| os.environ['application']).lower() |
| notebook_config['expected_secondary_image_name'] = '{}-{}-{}-{}-secondary-image'.format( |
| notebook_config['service_base_name'], notebook_config['project_name'], notebook_config['endpoint_tag'], |
| os.environ['application']).lower() |
| else: |
| notebook_config['expected_primary_image_name'] = '{}-{}-{}-primary-image'.format( |
| notebook_config['service_base_name'], notebook_config['endpoint_name'], os.environ['application']).lower() |
| notebook_config['expected_secondary_image_name'] = '{}-{}-{}-secondary-image'.format( |
| notebook_config['service_base_name'], notebook_config['endpoint_name'], os.environ['application']).lower() |
| notebook_config['notebook_primary_image_name'] = (lambda x: '{0}-{1}-{2}-{3}-primary-image-{4}'.format( |
| notebook_config['service_base_name'], notebook_config['project_name'], notebook_config['endpoint_name'], |
| os.environ['application'], os.environ['notebook_image_name'].replace('_', '-').lower()) if (x != 'None' and x != '') |
| else notebook_config['expected_primary_image_name'])(str(os.environ.get('notebook_image_name'))) |
| print('Searching pre-configured images') |
| |
| if os.environ['conf_deeplearning_cloud_ami'] == 'true' and os.environ['application'] == 'deeplearning': |
| notebook_config['primary_image_name'] = GCPMeta.get_deeplearning_image_by_family(os.environ['notebook_image_name']) |
| if notebook_config['primary_image_name']: |
| deeplearning_ami = 'true' |
| else: |
| notebook_config['primary_image_name'] = GCPMeta.get_image_by_name(notebook_config['notebook_primary_image_name']) |
| deeplearning_ami = 'false' |
| if notebook_config['primary_image_name'] == '': |
| notebook_config['primary_image_name'] = os.environ['gcp_{}_image_name'.format(os.environ['conf_os_family'])] |
| else: |
| print('Pre-configured primary image found. Using: {}'.format( |
| notebook_config['primary_image_name'].get('name'))) |
| if deeplearning_ami == 'true': |
| notebook_config['primary_image_name'] = 'projects/deeplearning-platform-release/global/images/{}'.format( |
| notebook_config['primary_image_name'].get('name')) |
| else: |
| notebook_config['primary_image_name'] = 'global/images/{}'.format( |
| notebook_config['primary_image_name'].get('name')) |
| notebook_config['notebook_secondary_image_name'] = (lambda x: '{0}-{1}-{2}-{3}-secondary-image-{4}'.format( |
| notebook_config['service_base_name'], notebook_config['project_name'], notebook_config['endpoint_name'], |
| os.environ['application'], os.environ['notebook_image_name'].replace('_', '-').lower()) if (x != 'None' and x != '') |
| else notebook_config['expected_secondary_image_name'])(str(os.environ.get('notebook_image_name'))) |
| if notebook_config['notebook_secondary_image_name'][:63].endswith('-'): |
| notebook_config['notebook_secondary_image_name'] = notebook_config['notebook_secondary_image_name'][:63][:-1] |
| notebook_config['secondary_image_name'] = GCPMeta.get_image_by_name( |
| notebook_config['notebook_secondary_image_name'][:63]) |
| if notebook_config['secondary_image_name'] == '': |
| notebook_config['secondary_image_name'] = 'None' |
| else: |
| print('Pre-configured secondary image found. Using: {}'.format( |
| notebook_config['secondary_image_name'].get('name'))) |
| notebook_config['secondary_image_name'] = 'global/images/{}'.format( |
| notebook_config['secondary_image_name'].get('name')) |
| |
| notebook_config['gpu_accelerator_type'] = 'None' |
| notebook_config['gpu_accelerator_count'] = 'None' |
| |
| if os.environ['application'] in ('tensor', 'tensor-rstudio', 'deeplearning') or os.environ['gpu_enabled'] == 'True': |
| if os.environ['gpuType'] != '': |
| notebook_config['gpu_accelerator_type'] = os.environ['gpuType'] |
| notebook_config['gpu_accelerator_count'] = os.environ['gpuCount'] |
| else: |
| notebook_config['gpu_accelerator_type'] = os.environ['gcp_gpu_accelerator_type'] |
| |
| notebook_config['network_tag'] = '{0}-{1}-{2}-ps'.format(notebook_config['service_base_name'], |
| notebook_config['project_name'], |
| notebook_config['endpoint_name']) |
| |
| with open('/root/result.json', 'w') as f: |
| data = {"notebook_name": notebook_config['instance_name'], "error": ""} |
| json.dump(data, f) |
| |
| print('Additional tags will be added: {}'.format(os.environ['tags'])) |
| additional_tags = os.environ['tags'].replace("': '", ":").replace("', '", ",").replace("{'", "" ).replace( |
| "'}", "").lower() |
| |
| print('Additional tags will be added: {}'.format(additional_tags)) |
| notebook_config['labels'] = {"name": notebook_config['instance_name'], |
| "sbn": notebook_config['service_base_name'], |
| "product": "datalab" |
| } |
| |
| for tag in additional_tags.split(','): |
| label_key = tag.split(':')[0] |
| label_value = tag.split(':')[1].replace('_', '-') |
| if '@' in label_value: |
| label_value = label_value[:label_value.find('@')] |
| if label_value != '': |
| notebook_config['labels'].update({label_key: label_value}) |
| except Exception as err: |
| datalab.fab.append_result("Failed to generate variables dictionary.", str(err)) |
| sys.exit(1) |
| # launching instance for notebook server |
| try: |
| logging.info('[CREATE NOTEBOOK INSTANCE]') |
| print('[CREATE NOTEBOOK INSTANCE]') |
| params = "--instance_name {0} --region {1} --zone {2} --vpc_name {3} --subnet_name {4} --instance_size {5} " \ |
| "--ssh_key_path {6} --initial_user {7} --service_account_name {8} --image_name {9} " \ |
| "--secondary_image_name {10} --instance_class {11} --primary_disk_size {12} " \ |
| "--secondary_disk_size {13} --gpu_accelerator_type {14} --gpu_accelerator_count {15} --network_tag {16} --labels '{17}' " \ |
| "--service_base_name {18}".\ |
| format(notebook_config['instance_name'], notebook_config['region'], notebook_config['zone'], |
| notebook_config['vpc_name'], notebook_config['subnet_name'], notebook_config['instance_size'], |
| notebook_config['ssh_key_path'], notebook_config['initial_user'], |
| notebook_config['notebook_service_account_name'], notebook_config['primary_image_name'], |
| notebook_config['secondary_image_name'], 'notebook', notebook_config['primary_disk_size'], |
| notebook_config['secondary_disk_size'], notebook_config['gpu_accelerator_type'], |
| notebook_config['gpu_accelerator_count'], notebook_config['network_tag'], |
| json.dumps(notebook_config['labels']), notebook_config['service_base_name']) |
| try: |
| subprocess.run("~/scripts/{}.py {}".format('common_create_instance', params), shell=True, check=True) |
| except: |
| traceback.print_exc() |
| raise Exception |
| except Exception as err: |
| datalab.fab.append_result("Failed to create instance.", str(err)) |
| GCPActions.remove_disk(notebook_config['instance_name'], notebook_config['zone']) |
| GCPActions.remove_instance(notebook_config['instance_name'], notebook_config['zone']) |
| sys.exit(1) |
