394 lines
14 KiB
Python
394 lines
14 KiB
Python
# Copyright 2018 AT&T Intellectual Property. All other rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import copy
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import pprint
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import logging
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import time
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from urllib.parse import urlparse
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from airflow.exceptions import AirflowException
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from airflow.plugins_manager import AirflowPlugin
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from airflow.utils.decorators import apply_defaults
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import drydock_provisioner.drydock_client.client as client
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import drydock_provisioner.drydock_client.session as session
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from drydock_provisioner import error as errors
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try:
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import service_endpoint
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except ImportError:
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from shipyard_airflow.plugins import service_endpoint
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try:
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from service_token import shipyard_service_token
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except ImportError:
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from shipyard_airflow.plugins.service_token import shipyard_service_token
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try:
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from ucp_base_operator import UcpBaseOperator
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except ImportError:
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from shipyard_airflow.plugins.ucp_base_operator import UcpBaseOperator
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try:
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from drydock_errors import (
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DrydockClientUseFailureException,
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DrydockTaskFailedException,
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DrydockTaskNotCreatedException,
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DrydockTaskTimeoutException
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)
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except ImportError:
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from shipyard_airflow.plugins.drydock_errors import (
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DrydockClientUseFailureException,
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DrydockTaskFailedException,
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DrydockTaskNotCreatedException,
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DrydockTaskTimeoutException
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)
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LOG = logging.getLogger(__name__)
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class DrydockBaseOperator(UcpBaseOperator):
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"""Drydock Base Operator
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All drydock related workflow operators will use the drydock
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base operator as the parent and inherit attributes and methods
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from this class
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"""
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@apply_defaults
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def __init__(self,
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drydock_client=None,
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drydock_task_id=None,
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node_filter=None,
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redeploy_server=None,
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svc_session=None,
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svc_token=None,
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*args, **kwargs):
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"""Initialization of DrydockBaseOperator object.
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:param drydockclient: An instance of drydock client
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:param drydock_task_id: Drydock Task ID
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:param node_filter: A filter for narrowing the scope of the task.
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Valid fields are 'node_names', 'rack_names',
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'node_tags'. Note that node filter is turned
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off by default, i.e. all nodes will be deployed.
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:param redeploy_server: Server to be redeployed
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:param svc_session: Keystone Session
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:param svc_token: Keystone Token
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The Drydock operator assumes that prior steps have set xcoms for
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the action and the deployment configuration
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"""
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super(DrydockBaseOperator,
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self).__init__(
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pod_selector_pattern=[{'pod_pattern': 'drydock-api',
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'container': 'drydock-api'}],
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*args, **kwargs)
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self.drydock_client = drydock_client
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self.drydock_task_id = drydock_task_id
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self.node_filter = node_filter
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self.redeploy_server = redeploy_server
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self.svc_session = svc_session
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self.svc_token = svc_token
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def run_base(self, context):
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# Logs uuid of action performed by the Operator
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LOG.info("DryDock Operator for action %s", self.action_info['id'])
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# Skip workflow if health checks on Drydock failed and continue-on-fail
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# option is turned on
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if self.xcom_puller.get_check_drydock_continue_on_fail():
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LOG.info("Skipping %s as health checks on Drydock have "
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"failed and continue-on-fail option has been "
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"turned on", self.__class__.__name__)
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# Set continue processing to False
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self.continue_processing = False
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return
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# Retrieve information of the server that we want to redeploy if user
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# executes the 'redeploy_server' dag
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# Set node filter to be the server that we want to redeploy
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if self.action_info['dag_id'] == 'redeploy_server':
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self.redeploy_server = (
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self.action_info['parameters']['server-name'])
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if self.redeploy_server:
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LOG.info("Server to be redeployed is %s",
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self.redeploy_server)
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self.node_filter = self.redeploy_server
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else:
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raise AirflowException('%s was unable to retrieve the '
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'server to be redeployed.'
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% self.__class__.__name__)
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# Retrieve Endpoint Information
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self.drydock_svc_endpoint = self.endpoints.endpoint_by_name(
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service_endpoint.DRYDOCK
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)
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LOG.info("Drydock endpoint is %s", self.drydock_svc_endpoint)
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# Parse DryDock Service Endpoint
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drydock_url = urlparse(self.drydock_svc_endpoint)
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# Build a DrydockSession with credentials and target host
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# information.
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# The DrydockSession will care for TCP connection pooling
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# and header management
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LOG.info("Build DryDock Session")
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dd_session = session.DrydockSession(drydock_url.hostname,
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port=drydock_url.port,
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auth_gen=self._auth_gen)
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# Raise Exception if we are not able to set up the session
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if dd_session:
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LOG.info("Successfully Set Up DryDock Session")
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else:
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raise DrydockClientUseFailureException(
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"Failed to set up Drydock Session!"
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)
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# Use the DrydockSession to build a DrydockClient that can
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# be used to make one or more API calls
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LOG.info("Create DryDock Client")
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self.drydock_client = client.DrydockClient(dd_session)
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# Raise Exception if we are not able to build the client
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if self.drydock_client:
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LOG.info("Successfully Set Up DryDock client")
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else:
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raise DrydockClientUseFailureException(
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"Failed to set up Drydock Client!"
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)
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@shipyard_service_token
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def _auth_gen(self):
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# Generator method for the Drydock Session to use to get the
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# auth headers necessary
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return [('X-Auth-Token', self.svc_token)]
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def create_task(self, task_action):
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# Initialize Variables
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create_task_response = {}
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# Node Filter
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LOG.info("Nodes Filter List: %s", self.node_filter)
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try:
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# Create Task
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create_task_response = self.drydock_client.create_task(
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design_ref=self.design_ref,
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task_action=task_action,
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node_filter=self.node_filter)
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except errors.ClientError as client_error:
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# Dump logs from Drydock pods
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self.get_k8s_logs()
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raise DrydockClientUseFailureException(client_error)
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# Retrieve Task ID
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self.drydock_task_id = create_task_response['task_id']
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LOG.info('Drydock %s task ID is %s',
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task_action, self.drydock_task_id)
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# Raise Exception if we are not able to get the task_id from
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# Drydock
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if self.drydock_task_id:
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return self.drydock_task_id
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else:
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raise DrydockTaskNotCreatedException("Unable to create task!")
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def query_task(self, interval, time_out):
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# Calculate number of times to execute the 'for' loop
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# Convert 'time_out' and 'interval' from string into integer
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# The result from the division will be a floating number which
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# We will round off to nearest whole number
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end_range = round(int(time_out) / int(interval))
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LOG.info('Task ID is %s', self.drydock_task_id)
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task_result = None
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# Query task status
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for i in range(0, end_range + 1):
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task_status = None
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try:
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# Retrieve current task state
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task_state = self.get_task_dict(task_id=self.drydock_task_id)
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task_status = task_state['status']
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task_result = task_state['result']['status']
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LOG.info("Current status of task id %s is %s",
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self.drydock_task_id, task_status)
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except DrydockClientUseFailureException:
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self.get_k8s_logs()
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raise
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except:
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# There can be situations where there are intermittent network
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# issues that prevents us from retrieving the task state. We
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# will want to retry in such situations.
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LOG.warning("Unable to retrieve task state. Retrying...")
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# Raise Time Out Exception
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if task_status == 'running' and i == end_range:
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self.task_failure(False)
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# Exit 'for' loop if the task is in 'complete' or 'terminated'
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# state
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if task_status in ['complete', 'terminated']:
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LOG.info('Task result is %s', task_result)
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break
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else:
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time.sleep(int(interval))
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# Get final task result
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if task_result == 'success':
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LOG.info('Task id %s has been successfully completed',
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self.drydock_task_id)
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else:
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self.task_failure(True)
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def get_task_dict(self, task_id):
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"""Retrieve task output in its raw dictionary format
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:param task_id: The id of the task to retrieve
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Raises DrydockClientUseFailureException if the client raises an
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exception
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See:
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http://att-comdev-drydock.readthedocs.io/en/latest/task.html#task-status-schema
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"""
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try:
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return self.drydock_client.get_task(task_id=task_id)
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except errors.ClientError as client_error:
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# Dump logs from Drydock pods
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raise DrydockClientUseFailureException(client_error)
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def task_failure(self, _task_failure):
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# Dump logs from Drydock pods
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self.get_k8s_logs()
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LOG.info('Retrieving all tasks records from Drydock...')
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try:
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# Get all tasks records
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all_tasks = self.drydock_client.get_tasks()
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# Create a dictionary of tasks records with 'task_id' as key
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self.all_task_ids = {t['task_id']: t for t in all_tasks}
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except errors.ClientError as client_error:
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raise DrydockClientUseFailureException(client_error)
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# Retrieve the failed parent task and assign it to list
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failed_parent_task = (
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[x for x in all_tasks if x['task_id'] == self.drydock_task_id])
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# Print detailed information of failed parent task in json output
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# Since there is only 1 failed parent task, we will print index 0
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# of the list
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if failed_parent_task:
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LOG.error("%s task has either failed or timed out",
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failed_parent_task[0]['action'])
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LOG.error(pprint.pprint(failed_parent_task[0]))
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# Get the list of subtasks belonging to the failed parent task
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parent_subtask_id_list = failed_parent_task[0]['subtask_id_list']
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# Check for failed subtasks
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self.check_subtask_failure(parent_subtask_id_list)
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# Raise Exception to terminate workflow
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if _task_failure:
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raise DrydockTaskFailedException(
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"Failed to Execute/Complete Task!"
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)
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else:
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raise DrydockTaskTimeoutException(
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"Task Execution Timed Out!"
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)
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def check_subtask_failure(self, subtask_id_list):
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LOG.info("Printing information of failed sub-tasks...")
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while subtask_id_list:
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# Copies the current list (a layer)
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children_subtask_id_list = copy.copy(subtask_id_list)
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# Reset subtask_id_list for each layer
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# The last layer will be an empty list
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subtask_id_list = []
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# Print detailed information of failed step(s) under each
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# subtask. This will help to provide additional information
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# for troubleshooting purpose.
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for subtask_id in children_subtask_id_list:
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LOG.info("Retrieving details of subtask %s...", subtask_id)
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# Retrieve task information
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task = self.all_task_ids.get(subtask_id)
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if task:
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# Print subtask action and state
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LOG.info("%s subtask is in %s state",
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task['action'],
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task['result']['status'])
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# Check for subtasks and extend the list
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subtask_id_list.extend(task['subtask_id_list'])
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# Check if error count is greater than 0
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if task['result']['details']['errorCount'] > 0:
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# Get message list
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message_list = (
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task['result']['details']['messageList'] or [])
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# Print information of failed steps
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for message in message_list:
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is_error = message['error'] is True
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if is_error:
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LOG.error(pprint.pprint(message))
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else:
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LOG.info("No failed step detected for subtask %s",
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subtask_id)
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else:
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raise DrydockClientUseFailureException(
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"Unable to retrieve subtask info!"
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)
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class DrydockBaseOperatorPlugin(AirflowPlugin):
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"""Creates DrydockBaseOperator in Airflow."""
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name = 'drydock_base_operator_plugin'
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operators = [DrydockBaseOperator]
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