shipyard/src/bin/shipyard_airflow/shipyard_airflow/plugins/drydock_nodes.py

457 lines
19 KiB
Python

# Copyright 2018 AT&T Intellectual Property. All other rights reserved.
#
# Licensed 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.
"""Prepare and deploy nodes using Drydock
Uses the deployment strategy named in the deployment-configuration to
progress through preparation and deployment of nodes in a group-based fashion.
In the case of no specified deployment strategy, an "all-at-once" approach is
taken, by which all nodes are deployed together.
Historical Note: This operator replaces the function of drydock_prepare_nodes
and drydock_deploy_nodes operators that existed previously.
"""
import logging
import time
from airflow.exceptions import AirflowException
from airflow.plugins_manager import AirflowPlugin
from shipyard_airflow.common.deployment_group.deployment_group import Stage
from shipyard_airflow.common.deployment_group.deployment_group_manager import \
DeploymentGroupManager
from shipyard_airflow.common.deployment_group.node_lookup import NodeLookup
try:
import check_k8s_node_status
from drydock_base_operator import DrydockBaseOperator
from drydock_base_operator import gen_node_name_filter
from drydock_errors import (
DrydockTaskFailedException,
DrydockTaskTimeoutException
)
except ImportError:
from shipyard_airflow.plugins import check_k8s_node_status
from shipyard_airflow.plugins.drydock_base_operator import \
DrydockBaseOperator
from shipyard_airflow.plugins.drydock_base_operator import \
gen_node_name_filter
from shipyard_airflow.plugins.drydock_errors import (
DrydockTaskFailedException,
DrydockTaskTimeoutException
)
LOG = logging.getLogger(__name__)
DOCUMENT_INFO = 'document_info'
class DrydockNodesOperator(DrydockBaseOperator):
"""Drydock Nodes Operator
Using a deployment strategy to calculate the deployment sequence,
deploy a series of baremetal nodes using Drydock.
"""
def do_execute(self):
self._setup_configured_values()
# setup self.strategy
self.strategy = self.get_deployment_strategy()
dgm = _get_deployment_group_manager(
self.strategy['groups'],
_get_node_lookup(self.drydock_client, self.design_ref)
)
_process_deployment_groups(dgm,
self._execute_prepare,
self._execute_deployment)
# All groups "complete" (as they're going to be). Report summary
dgm.report_group_summary()
dgm.report_node_summary()
self._gen_summary_notes(dgm)
if dgm.critical_groups_failed():
raise AirflowException(
"One or more deployment groups marked as critical have failed"
)
else:
LOG.info("All critical groups have met their success criteria")
def _gen_summary_notes(self, dgm):
"""Generate notes for the step summarizing the deployment results
:param dgm: The deployment group manager containing results
"""
# Assemble the nodes into a note
stages = [Stage.NOT_STARTED, Stage.DEPLOYED, Stage.FAILED]
nodes_by_stage = []
for stage in stages:
nodes = dgm.get_nodes(stage=stage)
if nodes:
nodes_by_stage.append("{}: {}".format(
stage, ", ".join(nodes)))
if nodes_by_stage:
self.notes_helper.make_step_note(
action_id=self.action_id,
step_id=self.task_id,
note_val="; ".join(nodes_by_stage),
subject=self.main_dag_name,
sub_type="Node Deployment",
verbosity=1)
# assemble the group info into a note
# rotate list into a dict by stage
groups_stages = {}
for group in dgm.group_list():
if group.stage not in groups_stages:
groups_stages[group.stage] = []
groups_stages[group.stage].append("{}{}".format(
group.name, "(critical)" if group.critical else ""))
# iterate stage keyed dictionary for text summary
groups_by_stage = [
"{}: {}".format(stage, ", ".join(group_list))
for stage, group_list in groups_stages.items()
]
if groups_by_stage:
self.notes_helper.make_step_note(
action_id=self.action_id,
step_id=self.task_id,
note_val="; ".join(groups_by_stage),
subject=self.main_dag_name,
sub_type="Deployment Groups",
verbosity=1)
def _setup_configured_values(self):
"""Sets self.<name> values from the deployment configuration"""
# Retrieve query intervals and timeouts
# Intervals - How often will something be queried for status.
self.dep_interval = self.dc['physical_provisioner.deploy_interval']
self.node_st_interval = self.dc['kubernetes.node_status_interval']
self.prep_interval = self.dc[
'physical_provisioner.prepare_node_interval'
]
# Timeouts - Time Shipyard waits for completion of a task.
self.dep_timeout = self.dc['physical_provisioner.deploy_timeout']
self.node_st_timeout = self.dc['kubernetes.node_status_timeout']
self.prep_timeout = self.dc[
'physical_provisioner.prepare_node_timeout'
]
# The time to wait before querying k8s nodes after Drydock deploy nodes
self.join_wait = self.dc['physical_provisioner.join_wait']
def _execute_prepare(self, group):
"""Executes the prepare nodes step for the group.
:param group: the DeploymentGroup to prepare
Returns a QueryTaskResult object
"""
LOG.info("Group %s is preparing nodes", group.name)
self.node_filter = gen_node_name_filter(group.actionable_nodes)
return self._execute_task('prepare_nodes',
self.prep_interval,
self.prep_timeout)
def _execute_deployment(self, group, successful_prepared_nodes):
"""Execute the deployment of nodes for the group.
:param group: The DeploymentGroup to deploy
:param successful_prepared_nodes: Nodes for this group that are
successfully prepared by the prepare nodes step.
Returns a QueryTaskResult object
"""
LOG.info("Group %s is deploying nodes", group.name)
s_nodes = list(successful_prepared_nodes)
self.node_filter = gen_node_name_filter(s_nodes)
task_result = self._execute_task('deploy_nodes',
self.dep_interval,
self.dep_timeout)
if not task_result.successes:
# if there are no successes from Drydock, there is no need to
# wait and check on the results from node status.
LOG.info("There are no nodes indicated as successful from Drydock."
" Skipping waiting for Kubernetes node join and "
"proceeding to validation")
return task_result
# It takes time for the cluster join process to be triggered across
# all the nodes in the cluster. Hence there is a need to back off
# and wait before checking the state of the cluster join process.
LOG.info("Nodes <%s> reported as deployed in MAAS",
", ".join(task_result.successes))
LOG.info("Waiting for %d seconds before checking node state...",
self.join_wait)
time.sleep(self.join_wait)
# Check that cluster join process is completed before declaring
# deploy_node as 'completed'.
# This should only include nodes that drydock has indicated as
# successful and has passed the join script to.
# Anything not ready in the timeout needs to be considered a failure
not_ready_list = check_k8s_node_status.check_node_status(
self.node_st_timeout,
self.node_st_interval,
expected_nodes=task_result.successes
)
for node in not_ready_list:
# Remove nodes that are not ready from the list of successes, since
# they did not complete deployment successfully.
try:
LOG.info("Node %s failed to join the Kubernetes cluster or was"
" not timely enough", node)
task_result.successes.remove(node)
except (ValueError, KeyError):
# This node is not joined, but was not one that we were
# looking for either.
LOG.info("%s failed to join Kubernetes, but was not in the "
"Drydock results: %s",
node,
", ".join(task_result.successes))
return task_result
def _execute_task(self, task_name, interval, timeout):
"""Execute the Drydock task requested
:param task_name: 'prepare_nodes', 'deploy_nodes'
:param interval: The time between checking status on the task
:param timeout: The total time allowed for the task
Wraps the query_task method in the base class, capturing
AirflowExceptions and summarizing results into a response
QueryTaskResult object
Note: It does not matter if the task ultimately succeeds or fails in
Drydock - the base class will handle all the logging and etc for
the purposes of troubleshooting. What matters is the node successes.
Following any result of query_task, this code will re-query the task
results from Drydock to gather the node successes placing them into
the successes list in the response object. In the case of a failure to
get the task results, this workflow must assume that the result is a
total loss, and pass back no successes
"""
self.create_task(task_name)
result = QueryTaskResult(self.drydock_task_id, task_name)
try:
self.query_task(interval, timeout)
except DrydockTaskFailedException:
# Task failure may be successful enough based on success criteria.
# This should not halt the overall flow of this workflow step.
LOG.warn(
"Task %s has failed. Logs contain details of the failure. "
"Some nodes may be succesful, processing continues", task_name
)
except DrydockTaskTimeoutException:
# Task timeout may be successful enough based on success criteria.
# This should not halt the overall flow of this workflow step.
LOG.warn(
"Task %s has timed out after %s seconds. Logs contain details "
"of the failure. Some nodes may be succesful, processing "
"continues", task_name, timeout
)
# Other AirflowExceptions will fail the whole task - let them do this.
# find successes
result.successes = self.get_successes_for_task(self.drydock_task_id)
return result
def get_deployment_strategy(self):
"""Determine the deployment strategy
Uses the specified strategy from the deployment configuration
or returns a default configuration of 'all-at-once'
"""
if self.target_nodes:
# Set up a strategy with one group with the list of nodes, so those
# nodes are the only nodes processed.
LOG.info("Seting up deployment strategy using targeted nodes")
strat_name = 'targeted nodes'
strategy = gen_simple_deployment_strategy(name='target-group',
nodes=self.target_nodes)
else:
# Otherwise, do a strategy for the site - either from the
# configdocs or a default "everything".
strat_name = self.dc['physical_provisioner.deployment_strategy']
if strat_name:
# if there is a deployment strategy specified, use it
schema_fallback = 'shipyard/DeploymentStrategy/v1'
schema = self.config.get(DOCUMENT_INFO,
'deployment_strategy_schema',
fallback=schema_fallback)
strategy = self.get_unique_doc(name=strat_name, schema=schema)
else:
# The default behavior is to deploy all nodes, and fail if
# any nodes fail to deploy.
strat_name = 'all-at-once (defaulted)'
strategy = gen_simple_deployment_strategy()
LOG.info("Strategy Name: %s has %s groups",
strat_name,
len(strategy.get('groups', [])))
return strategy
#
# Functions supporting the nodes operator class
#
def gen_simple_deployment_strategy(name=None, nodes=None):
"""Generates a single group deployment strategy
:param name: the name of the single group. Defaults to 'default'
:param nodes: the list of node_names to be used. Defaults to []
"""
target_name = name or 'default'
target_nodes = list(nodes) if nodes else []
return {
'groups': [
{
'name': target_name,
'critical': True,
'depends_on': [],
'selectors': [
{
'node_names': target_nodes,
'node_labels': [],
'node_tags': [],
'rack_names': [],
},
],
'success_criteria': {
'percent_successful_nodes': 100
},
}
]
}
def _get_node_lookup(drydock_client, design_ref):
"""Return a NodeLookup suitable for the DeploymentGroupManager
:param drydock_client: the drydock_client object
:param design_ref: the design_ref for the NodeLookup
"""
return NodeLookup(drydock_client, design_ref).lookup
def _get_deployment_group_manager(groups_dict_list, node_lookup):
"""Return a DeploymentGroupManager suitable for managing this deployment
:param groups_dict_list: the list of group dictionaries to use
:param node_lookup: a NodeLookup object that will be used by this
DeploymentGroupManager
"""
return DeploymentGroupManager(groups_dict_list, node_lookup)
def _process_deployment_groups(dgm, prepare_func, deploy_func):
"""Executes the deployment group deployments
:param dgm: the DeploymentGroupManager object that manages the
dependency chain of groups
:param prepare_func: a function that accepts a DeploymentGroup and returns
a QueryTaskResult with the purpose of preparing nodes
:param deploy_func: a function that accepts a DeploymentGroup and returns
a QueryTaskResult with the purpose of deploying nodes
"""
complete = False
while not complete:
# Find the next group to be prepared. Prepare and deploy it.
group = dgm.get_next_group(Stage.PREPARED)
if group is None:
LOG.info("There are no more groups eligible to process")
# whether or not really complete, the processing loop is done.
complete = True
continue
LOG.info("*** Deployment Group: %s is being processed ***", group.name)
if not group.actionable_nodes:
LOG.info("There were no actionable nodes for group %s. It is "
"possible that all nodes: [%s] have previously been "
"deployed. Group will be immediately checked "
"against its success criteria", group.name,
", ".join(group.full_nodes))
# In the case of a group having no actionable nodes, since groups
# prepare -> deploy in direct sequence, we can check against
# deployment, since all nodes would need to be deployed or have
# been attempted. Need to follow the state-transition, so
# PREPARED -> DEPLOYED
dgm.evaluate_group_succ_criteria(group.name, Stage.PREPARED)
dgm.evaluate_group_succ_criteria(group.name, Stage.DEPLOYED)
# success or failure, move on to next group
continue
LOG.info("%s has actionable nodes: [%s]", group.name,
", ".join(group.actionable_nodes))
if len(group.actionable_nodes) < len(group.full_nodes):
LOG.info("Some nodes are not actionable because they were "
"included in a prior group, but will be considered in "
"the success critera calculation for this group")
# Group has actionable nodes.
# Prepare Nodes for group, store QueryTaskResults
prep_qtr = prepare_func(group)
# Mark successes as prepared
for node_name in prep_qtr.successes:
dgm.mark_node_prepared(node_name)
dgm.fail_unsuccessful_nodes(group, prep_qtr.successes)
should_deploy = dgm.evaluate_group_succ_criteria(group.name,
Stage.PREPARED)
if not should_deploy:
# group has failed, move on to next group. Current group has
# been marked as failed.
continue
if prep_qtr.successes:
# Continue with deployment, only for successfully prepared nodes
dep_qtr = deploy_func(group, prep_qtr.successes)
# Mark successes as deployed
for node_name in dep_qtr.successes:
dgm.mark_node_deployed(node_name)
dgm.fail_unsuccessful_nodes(group, dep_qtr.successes)
else:
# TODO(bryan-strassner) Update this message if Drydock provides
# a way to cancel a task, and that method is employed by
# Shipyard upon timeout.
LOG.info("There were no nodes successfully prepared. "
"Deployment will not be attempted for group %s. "
"Success criteria will be immediately checked. "
"If a timeout in the prepare step has occured, it is "
"possible that Drydock is still attempting the prepare "
"task.",
group.name)
dgm.evaluate_group_succ_criteria(group.name, Stage.DEPLOYED)
class QueryTaskResult:
"""Represents a summarized query result from a task"""
def __init__(self, task_id, task_name):
self.task_id = task_id
self.task_name = task_name
# The succeeded node names
self.successes = []
class DrydockNodesOperatorPlugin(AirflowPlugin):
"""Creates DrydockPrepareNodesOperator in Airflow."""
name = 'drydock_nodes_operator'
operators = [DrydockNodesOperator]