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#!/usr/bin/python
# This file is part of Ansible
#
# Ansible is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Ansible is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Ansible. If not, see <http://www.gnu.org/licenses/>.
ANSIBLE_METADATA = {'metadata_version': '1.1',
'status': ['stableinterface'],
'supported_by': 'certified'}
DOCUMENTATION = """
---
module: ec2_asg
short_description: Create or delete AWS Autoscaling Groups
description:
- Can create or delete AWS Autoscaling Groups
- Works with the ec2_lc module to manage Launch Configurations
version_added: "1.6"
author: "Gareth Rushgrove (@garethr)"
requirements: [ "boto3", "botocore" ]
options:
state:
description:
- register or deregister the instance
choices: ['present', 'absent']
default: present
name:
description:
- Unique name for group to be created or deleted
required: true
load_balancers:
description:
- List of ELB names to use for the group. Use for classic load balancers.
target_group_arns:
description:
- List of target group ARNs to use for the group. Use for application load balancers.
version_added: "2.4"
availability_zones:
description:
- List of availability zone names in which to create the group. Defaults to all the availability zones in the region if vpc_zone_identifier is not set.
launch_config_name:
description:
- Name of the Launch configuration to use for the group. See the ec2_lc module for managing these.
If unspecified then the current group value will be used.
required: true
min_size:
description:
- Minimum number of instances in group, if unspecified then the current group value will be used.
max_size:
description:
- Maximum number of instances in group, if unspecified then the current group value will be used.
placement_group:
description:
- Physical location of your cluster placement group created in Amazon EC2.
version_added: "2.3"
desired_capacity:
description:
- Desired number of instances in group, if unspecified then the current group value will be used.
replace_all_instances:
description:
- In a rolling fashion, replace all instances with an old launch configuration with one from the current launch configuration.
version_added: "1.8"
default: 'no'
replace_batch_size:
description:
- Number of instances you'd like to replace at a time. Used with replace_all_instances.
required: false
version_added: "1.8"
default: 1
replace_instances:
description:
- List of instance_ids belonging to the named ASG that you would like to terminate and be replaced with instances matching the current launch
configuration.
version_added: "1.8"
lc_check:
description:
- Check to make sure instances that are being replaced with replace_instances do not already have the current launch_config.
version_added: "1.8"
default: 'yes'
vpc_zone_identifier:
description:
- List of VPC subnets to use
tags:
description:
- A list of tags to add to the Auto Scale Group. Optional key is 'propagate_at_launch', which defaults to true.
version_added: "1.7"
health_check_period:
description:
- Length of time in seconds after a new EC2 instance comes into service that Auto Scaling starts checking its health.
required: false
default: 500 seconds
version_added: "1.7"
health_check_type:
description:
- The service you want the health status from, Amazon EC2 or Elastic Load Balancer.
required: false
default: EC2
version_added: "1.7"
choices: ['EC2', 'ELB']
default_cooldown:
description:
- The number of seconds after a scaling activity completes before another can begin.
default: 300 seconds
version_added: "2.0"
wait_timeout:
description:
- How long to wait for instances to become viable when replaced. If you experience the error "Waited too long for ELB instances to be healthy",
try increasing this value.
default: 300
version_added: "1.8"
wait_for_instances:
description:
- Wait for the ASG instances to be in a ready state before exiting. If instances are behind an ELB, it will wait until the ELB determines all
instances have a lifecycle_state of "InService" and a health_status of "Healthy".
version_added: "1.9"
default: 'yes'
termination_policies:
description:
- An ordered list of criteria used for selecting instances to be removed from the Auto Scaling group when reducing capacity.
- For 'Default', when used to create a new autoscaling group, the "Default"i value is used. When used to change an existent autoscaling group, the
current termination policies are maintained.
default: Default
choices: ['OldestInstance', 'NewestInstance', 'OldestLaunchConfiguration', 'ClosestToNextInstanceHour', 'Default']
version_added: "2.0"
notification_topic:
description:
- A SNS topic ARN to send auto scaling notifications to.
version_added: "2.2"
notification_types:
description:
- A list of auto scaling events to trigger notifications on.
default:
- 'autoscaling:EC2_INSTANCE_LAUNCH'
- 'autoscaling:EC2_INSTANCE_LAUNCH_ERROR'
- 'autoscaling:EC2_INSTANCE_TERMINATE'
- 'autoscaling:EC2_INSTANCE_TERMINATE_ERROR'
required: false
version_added: "2.2"
suspend_processes:
description:
- A list of scaling processes to suspend.
default: []
choices: ['Launch', 'Terminate', 'HealthCheck', 'ReplaceUnhealthy', 'AZRebalance', 'AlarmNotification', 'ScheduledActions', 'AddToLoadBalancer']
version_added: "2.3"
metrics_collection:
description:
- Enable ASG metrics collection
type: bool
default: 'no'
version_added: "2.6"
metrics_granularity:
description:
- When metrics_collection is enabled this will determine granularity of metrics collected by CloudWatch
default: "1minute"
version_added: "2.6"
metrics_list:
description:
- List of autoscaling metrics to collect when enabling metrics_collection
default:
- 'GroupMinSize'
- 'GroupMaxSize'
- 'GroupDesiredCapacity'
- 'GroupInServiceInstances'
- 'GroupPendingInstances'
- 'GroupStandbyInstances'
- 'GroupTerminatingInstances'
- 'GroupTotalInstances'
version_added: "2.6"
extends_documentation_fragment:
- aws
- ec2
"""
EXAMPLES = '''
# Basic configuration
- ec2_asg:
name: special
load_balancers: [ 'lb1', 'lb2' ]
availability_zones: [ 'eu-west-1a', 'eu-west-1b' ]
launch_config_name: 'lc-1'
min_size: 1
max_size: 10
desired_capacity: 5
vpc_zone_identifier: [ 'subnet-abcd1234', 'subnet-1a2b3c4d' ]
tags:
- environment: production
propagate_at_launch: no
# Rolling ASG Updates
# Below is an example of how to assign a new launch config to an ASG and terminate old instances.
#
# All instances in "myasg" that do not have the launch configuration named "my_new_lc" will be terminated in
# a rolling fashion with instances using the current launch configuration, "my_new_lc".
#
# This could also be considered a rolling deploy of a pre-baked AMI.
#
# If this is a newly created group, the instances will not be replaced since all instances
# will have the current launch configuration.
- name: create launch config
ec2_lc:
name: my_new_lc
image_id: ami-lkajsf
key_name: mykey
region: us-east-1
security_groups: sg-23423
instance_type: m1.small
assign_public_ip: yes
- ec2_asg:
name: myasg
launch_config_name: my_new_lc
health_check_period: 60
health_check_type: ELB
replace_all_instances: yes
min_size: 5
max_size: 5
desired_capacity: 5
region: us-east-1
# To only replace a couple of instances instead of all of them, supply a list
# to "replace_instances":
- ec2_asg:
name: myasg
launch_config_name: my_new_lc
health_check_period: 60
health_check_type: ELB
replace_instances:
- i-b345231
- i-24c2931
min_size: 5
max_size: 5
desired_capacity: 5
region: us-east-1
'''
RETURN = '''
---
auto_scaling_group_name:
description: The unique name of the auto scaling group
returned: success
type: str
sample: "myasg"
auto_scaling_group_arn:
description: The unique ARN of the autoscaling group
returned: success
type: str
sample: "arn:aws:autoscaling:us-east-1:123456789012:autoScalingGroup:6a09ad6d-eeee-1234-b987-ee123ced01ad:autoScalingGroupName/myasg"
availability_zones:
description: The availability zones for the auto scaling group
returned: success
type: list
sample: [
"us-east-1d"
]
created_time:
description: Timestamp of create time of the auto scaling group
returned: success
type: str
sample: "2017-11-08T14:41:48.272000+00:00"
default_cooldown:
description: The default cooldown time in seconds.
returned: success
type: int
sample: 300
desired_capacity:
description: The number of EC2 instances that should be running in this group.
returned: success
type: int
sample: 3
healthcheck_period:
description: Length of time in seconds after a new EC2 instance comes into service that Auto Scaling starts checking its health.
returned: success
type: int
sample: 30
healthcheck_type:
description: The service you want the health status from, one of "EC2" or "ELB".
returned: success
type: str
sample: "ELB"
healthy_instances:
description: Number of instances in a healthy state
returned: success
type: int
sample: 5
in_service_instances:
description: Number of instances in service
returned: success
type: int
sample: 3
instance_facts:
description: Dictionary of EC2 instances and their status as it relates to the ASG.
returned: success
type: dict
sample: {
"i-0123456789012": {
"health_status": "Healthy",
"launch_config_name": "public-webapp-production-1",
"lifecycle_state": "InService"
}
}
instances:
description: list of instance IDs in the ASG
returned: success
type: list
sample: [
"i-0123456789012"
]
launch_config_name:
description: >
Name of launch configuration associated with the ASG. Same as launch_configuration_name,
provided for compatibility with ec2_asg module.
returned: success
type: str
sample: "public-webapp-production-1"
load_balancers:
description: List of load balancers names attached to the ASG.
returned: success
type: list
sample: ["elb-webapp-prod"]
max_size:
description: Maximum size of group
returned: success
type: int
sample: 3
min_size:
description: Minimum size of group
returned: success
type: int
sample: 1
pending_instances:
description: Number of instances in pending state
returned: success
type: int
sample: 1
tags:
description: List of tags for the ASG, and whether or not each tag propagates to instances at launch.
returned: success
type: list
sample: [
{
"key": "Name",
"value": "public-webapp-production-1",
"resource_id": "public-webapp-production-1",
"resource_type": "auto-scaling-group",
"propagate_at_launch": "true"
},
{
"key": "env",
"value": "production",
"resource_id": "public-webapp-production-1",
"resource_type": "auto-scaling-group",
"propagate_at_launch": "true"
}
]
target_group_arns:
description: List of ARNs of the target groups that the ASG populates
returned: success
type: list
sample: [
"arn:aws:elasticloadbalancing:ap-southeast-2:123456789012:targetgroup/target-group-host-hello/1a2b3c4d5e6f1a2b",
"arn:aws:elasticloadbalancing:ap-southeast-2:123456789012:targetgroup/target-group-path-world/abcd1234abcd1234"
]
target_group_names:
description: List of names of the target groups that the ASG populates
returned: success
type: list
sample: [
"target-group-host-hello",
"target-group-path-world"
]
termination_policies:
description: A list of termination policies for the group.
returned: success
type: str
sample: ["Default"]
unhealthy_instances:
description: Number of instances in an unhealthy state
returned: success
type: int
sample: 0
viable_instances:
description: Number of instances in a viable state
returned: success
type: int
sample: 1
vpc_zone_identifier:
description: VPC zone ID / subnet id for the auto scaling group
returned: success
type: str
sample: "subnet-a31ef45f"
metrics_collection:
description: List of enabled AutosSalingGroup metrics
returned: success
type: list
sample: [
{
"Granularity": "1Minute",
"Metric": "GroupInServiceInstances"
}
]
'''
import time
import traceback
from ansible.module_utils._text import to_native
from ansible.module_utils.basic import AnsibleModule
from ansible.module_utils.ec2 import boto3_conn, ec2_argument_spec, HAS_BOTO3, camel_dict_to_snake_dict, get_aws_connection_info, AWSRetry
try:
import botocore
except ImportError:
pass # will be detected by imported HAS_BOTO3
ASG_ATTRIBUTES = ('AvailabilityZones', 'DefaultCooldown', 'DesiredCapacity',
'HealthCheckGracePeriod', 'HealthCheckType', 'LaunchConfigurationName',
'LoadBalancerNames', 'MaxSize', 'MinSize', 'AutoScalingGroupName', 'PlacementGroup',
'TerminationPolicies', 'VPCZoneIdentifier')
INSTANCE_ATTRIBUTES = ('instance_id', 'health_status', 'lifecycle_state', 'launch_config_name')
backoff_params = dict(tries=10, delay=3, backoff=1.5)
@AWSRetry.backoff(**backoff_params)
def describe_autoscaling_groups(connection, group_name):
pg = connection.get_paginator('describe_auto_scaling_groups')
return pg.paginate(AutoScalingGroupNames=[group_name]).build_full_result().get('AutoScalingGroups', [])
@AWSRetry.backoff(**backoff_params)
def deregister_lb_instances(connection, lb_name, instance_id):
connection.deregister_instances_from_load_balancer(LoadBalancerName=lb_name, Instances=[dict(InstanceId=instance_id)])
@AWSRetry.backoff(**backoff_params)
def describe_instance_health(connection, lb_name, instances):
params = dict(LoadBalancerName=lb_name)
if instances:
params.update(Instances=instances)
return connection.describe_instance_health(**params)
@AWSRetry.backoff(**backoff_params)
def describe_target_health(connection, target_group_arn, instances):
return connection.describe_target_health(TargetGroupArn=target_group_arn, Targets=instances)
@AWSRetry.backoff(**backoff_params)
def suspend_asg_processes(connection, asg_name, processes):
connection.suspend_processes(AutoScalingGroupName=asg_name, ScalingProcesses=processes)
@AWSRetry.backoff(**backoff_params)
def resume_asg_processes(connection, asg_name, processes):
connection.resume_processes(AutoScalingGroupName=asg_name, ScalingProcesses=processes)
@AWSRetry.backoff(**backoff_params)
def describe_launch_configurations(connection, launch_config_name):
pg = connection.get_paginator('describe_launch_configurations')
return pg.paginate(LaunchConfigurationNames=[launch_config_name]).build_full_result()
@AWSRetry.backoff(**backoff_params)
def create_asg(connection, **params):
connection.create_auto_scaling_group(**params)
@AWSRetry.backoff(**backoff_params)
def put_notification_config(connection, asg_name, topic_arn, notification_types):
connection.put_notification_configuration(
AutoScalingGroupName=asg_name,
TopicARN=topic_arn,
NotificationTypes=notification_types
)
@AWSRetry.backoff(**backoff_params)
def del_notification_config(connection, asg_name, topic_arn):
connection.delete_notification_configuration(
AutoScalingGroupName=asg_name,
TopicARN=topic_arn
)
@AWSRetry.backoff(**backoff_params)
def attach_load_balancers(connection, asg_name, load_balancers):
connection.attach_load_balancers(AutoScalingGroupName=asg_name, LoadBalancerNames=load_balancers)
@AWSRetry.backoff(**backoff_params)
def detach_load_balancers(connection, asg_name, load_balancers):
connection.detach_load_balancers(AutoScalingGroupName=asg_name, LoadBalancerNames=load_balancers)
@AWSRetry.backoff(**backoff_params)
def attach_lb_target_groups(connection, asg_name, target_group_arns):
connection.attach_load_balancer_target_groups(AutoScalingGroupName=asg_name, TargetGroupARNs=target_group_arns)
@AWSRetry.backoff(**backoff_params)
def detach_lb_target_groups(connection, asg_name, target_group_arns):
connection.detach_load_balancer_target_groups(AutoScalingGroupName=asg_name, TargetGroupARNs=target_group_arns)
@AWSRetry.backoff(**backoff_params)
def update_asg(connection, **params):
connection.update_auto_scaling_group(**params)
@AWSRetry.backoff(**backoff_params)
def delete_asg(connection, asg_name, force_delete):
connection.delete_auto_scaling_group(AutoScalingGroupName=asg_name, ForceDelete=force_delete)
@AWSRetry.backoff(**backoff_params)
def terminate_asg_instance(connection, instance_id, decrement_capacity):
connection.terminate_instance_in_auto_scaling_group(InstanceId=instance_id,
ShouldDecrementDesiredCapacity=decrement_capacity)
def enforce_required_arguments():
''' As many arguments are not required for autoscale group deletion
they cannot be mandatory arguments for the module, so we enforce
them here '''
missing_args = []
for arg in ('min_size', 'max_size', 'launch_config_name'):
if module.params[arg] is None:
missing_args.append(arg)
if missing_args:
module.fail_json(msg="Missing required arguments for autoscaling group create/update: %s" % ",".join(missing_args))
def get_properties(autoscaling_group):
properties = dict()
properties['healthy_instances'] = 0
properties['in_service_instances'] = 0
properties['unhealthy_instances'] = 0
properties['pending_instances'] = 0
properties['viable_instances'] = 0
properties['terminating_instances'] = 0
instance_facts = dict()
autoscaling_group_instances = autoscaling_group.get('Instances')
if autoscaling_group_instances:
properties['instances'] = [i['InstanceId'] for i in autoscaling_group_instances]
for i in autoscaling_group_instances:
instance_facts[i['InstanceId']] = {'health_status': i['HealthStatus'],
'lifecycle_state': i['LifecycleState'],
'launch_config_name': i.get('LaunchConfigurationName')}
if i['HealthStatus'] == 'Healthy' and i['LifecycleState'] == 'InService':
properties['viable_instances'] += 1
if i['HealthStatus'] == 'Healthy':
properties['healthy_instances'] += 1
else:
properties['unhealthy_instances'] += 1
if i['LifecycleState'] == 'InService':
properties['in_service_instances'] += 1
if i['LifecycleState'] == 'Terminating':
properties['terminating_instances'] += 1
if i['LifecycleState'] == 'Pending':
properties['pending_instances'] += 1
else:
properties['instances'] = []
properties['auto_scaling_group_name'] = autoscaling_group.get('AutoScalingGroupName')
properties['auto_scaling_group_arn'] = autoscaling_group.get('AutoScalingGroupARN')
properties['availability_zones'] = autoscaling_group.get('AvailabilityZones')
properties['created_time'] = autoscaling_group.get('CreatedTime')
properties['instance_facts'] = instance_facts
properties['load_balancers'] = autoscaling_group.get('LoadBalancerNames')
properties['launch_config_name'] = autoscaling_group.get('LaunchConfigurationName')
properties['tags'] = autoscaling_group.get('Tags')
properties['min_size'] = autoscaling_group.get('MinSize')
properties['max_size'] = autoscaling_group.get('MaxSize')
properties['desired_capacity'] = autoscaling_group.get('DesiredCapacity')
properties['default_cooldown'] = autoscaling_group.get('DefaultCooldown')
properties['healthcheck_grace_period'] = autoscaling_group.get('HealthCheckGracePeriod')
properties['healthcheck_type'] = autoscaling_group.get('HealthCheckType')
properties['default_cooldown'] = autoscaling_group.get('DefaultCooldown')
properties['termination_policies'] = autoscaling_group.get('TerminationPolicies')
properties['target_group_arns'] = autoscaling_group.get('TargetGroupARNs')
properties['vpc_zone_identifier'] = autoscaling_group.get('VPCZoneIdentifier')
properties['metrics_collection'] = autoscaling_group.get('EnabledMetrics')
if properties['target_group_arns']:
region, ec2_url, aws_connect_params = get_aws_connection_info(module, boto3=True)
elbv2_connection = boto3_conn(module,
conn_type='client',
resource='elbv2',
region=region,
endpoint=ec2_url,
**aws_connect_params)
tg_paginator = elbv2_connection.get_paginator('describe_target_groups')
tg_result = tg_paginator.paginate(TargetGroupArns=properties['target_group_arns']).build_full_result()
target_groups = tg_result['TargetGroups']
else:
target_groups = []
properties['target_group_names'] = [tg['TargetGroupName'] for tg in target_groups]
return properties
def elb_dreg(asg_connection, group_name, instance_id):
region, ec2_url, aws_connect_params = get_aws_connection_info(module, boto3=True)
as_group = describe_autoscaling_groups(asg_connection, group_name)[0]
wait_timeout = module.params.get('wait_timeout')
count = 1
if as_group['LoadBalancerNames'] and as_group['HealthCheckType'] == 'ELB':
elb_connection = boto3_conn(module,
conn_type='client',
resource='elb',
region=region,
endpoint=ec2_url,
**aws_connect_params)
else:
return
for lb in as_group['LoadBalancerNames']:
deregister_lb_instances(elb_connection, lb, instance_id)
module.debug("De-registering %s from ELB %s" % (instance_id, lb))
wait_timeout = time.time() + wait_timeout
while wait_timeout > time.time() and count > 0:
count = 0
for lb in as_group['LoadBalancerNames']:
lb_instances = describe_instance_health(elb_connection, lb, [])
for i in lb_instances['InstanceStates']:
if i['InstanceId'] == instance_id and i['State'] == "InService":
count += 1
module.debug("%s: %s, %s" % (i['InstanceId'], i['State'], i['Description']))
time.sleep(10)
if wait_timeout <= time.time():
# waiting took too long
module.fail_json(msg="Waited too long for instance to deregister. {0}".format(time.asctime()))
def elb_healthy(asg_connection, elb_connection, group_name):
healthy_instances = set()
as_group = describe_autoscaling_groups(asg_connection, group_name)[0]
props = get_properties(as_group)
# get healthy, inservice instances from ASG
instances = []
for instance, settings in props['instance_facts'].items():
if settings['lifecycle_state'] == 'InService' and settings['health_status'] == 'Healthy':
instances.append(dict(InstanceId=instance))
module.debug("ASG considers the following instances InService and Healthy: %s" % instances)
module.debug("ELB instance status:")
lb_instances = list()
for lb in as_group.get('LoadBalancerNames'):
# we catch a race condition that sometimes happens if the instance exists in the ASG
# but has not yet show up in the ELB
try:
lb_instances = describe_instance_health(elb_connection, lb, instances)
except botocore.exceptions.ClientError as e:
if e.response['Error']['Code'] == 'InvalidInstance':
return None
module.fail_json(msg="Failed to get load balancer.",
exception=traceback.format_exc(), **camel_dict_to_snake_dict(e.response))
except botocore.exceptions.BotoCoreError as e:
module.fail_json(msg="Failed to get load balancer.",
exception=traceback.format_exc())
for i in lb_instances.get('InstanceStates'):
if i['State'] == "InService":
healthy_instances.add(i['InstanceId'])
module.debug("ELB Health State %s: %s" % (i['InstanceId'], i['State']))
return len(healthy_instances)
def tg_healthy(asg_connection, elbv2_connection, group_name):
healthy_instances = set()
as_group = describe_autoscaling_groups(asg_connection, group_name)[0]
props = get_properties(as_group)
# get healthy, inservice instances from ASG
instances = []
for instance, settings in props['instance_facts'].items():
if settings['lifecycle_state'] == 'InService' and settings['health_status'] == 'Healthy':
instances.append(dict(Id=instance))
module.debug("ASG considers the following instances InService and Healthy: %s" % instances)
module.debug("Target Group instance status:")
tg_instances = list()
for tg in as_group.get('TargetGroupARNs'):
# we catch a race condition that sometimes happens if the instance exists in the ASG
# but has not yet show up in the ELB
try:
tg_instances = describe_target_health(elbv2_connection, tg, instances)
except botocore.exceptions.ClientError as e:
if e.response['Error']['Code'] == 'InvalidInstance':
return None
module.fail_json(msg="Failed to get target group.",
exception=traceback.format_exc(), **camel_dict_to_snake_dict(e.response))
except botocore.exceptions.BotoCoreError as e:
module.fail_json(msg="Failed to get target group.",
exception=traceback.format_exc())
for i in tg_instances.get('TargetHealthDescriptions'):
if i['TargetHealth']['State'] == "healthy":
healthy_instances.add(i['Target']['Id'])
module.debug("Target Group Health State %s: %s" % (i['Target']['Id'], i['TargetHealth']['State']))
return len(healthy_instances)
def wait_for_elb(asg_connection, group_name):
region, ec2_url, aws_connect_params = get_aws_connection_info(module, boto3=True)
wait_timeout = module.params.get('wait_timeout')
# if the health_check_type is ELB, we want to query the ELBs directly for instance
# status as to avoid health_check_grace period that is awarded to ASG instances
as_group = describe_autoscaling_groups(asg_connection, group_name)[0]
if as_group.get('LoadBalancerNames') and as_group.get('HealthCheckType') == 'ELB':
module.debug("Waiting for ELB to consider instances healthy.")
elb_connection = boto3_conn(module,
conn_type='client',
resource='elb',
region=region,
endpoint=ec2_url,
**aws_connect_params)
wait_timeout = time.time() + wait_timeout
healthy_instances = elb_healthy(asg_connection, elb_connection, group_name)
while healthy_instances < as_group.get('MinSize') and wait_timeout > time.time():
healthy_instances = elb_healthy(asg_connection, elb_connection, group_name)
module.debug("ELB thinks %s instances are healthy." % healthy_instances)
time.sleep(10)
if wait_timeout <= time.time():
# waiting took too long
module.fail_json(msg="Waited too long for ELB instances to be healthy. %s" % time.asctime())
module.debug("Waiting complete. ELB thinks %s instances are healthy." % healthy_instances)
def wait_for_target_group(asg_connection, group_name):
region, ec2_url, aws_connect_params = get_aws_connection_info(module, boto3=True)
wait_timeout = module.params.get('wait_timeout')
# if the health_check_type is ELB, we want to query the ELBs directly for instance
# status as to avoid health_check_grace period that is awarded to ASG instances
as_group = describe_autoscaling_groups(asg_connection, group_name)[0]
if as_group.get('TargetGroupARNs') and as_group.get('HealthCheckType') == 'ELB':
module.debug("Waiting for Target Group to consider instances healthy.")
elbv2_connection = boto3_conn(module,
conn_type='client',
resource='elbv2',
region=region,
endpoint=ec2_url,
**aws_connect_params)
wait_timeout = time.time() + wait_timeout
healthy_instances = tg_healthy(asg_connection, elbv2_connection, group_name)
while healthy_instances < as_group.get('MinSize') and wait_timeout > time.time():
healthy_instances = tg_healthy(asg_connection, elbv2_connection, group_name)
module.debug("Target Group thinks %s instances are healthy." % healthy_instances)
time.sleep(10)
if wait_timeout <= time.time():
# waiting took too long
module.fail_json(msg="Waited too long for ELB instances to be healthy. %s" % time.asctime())
module.debug("Waiting complete. Target Group thinks %s instances are healthy." % healthy_instances)
def suspend_processes(ec2_connection, as_group):
suspend_processes = set(module.params.get('suspend_processes'))
try:
suspended_processes = set([p['ProcessName'] for p in as_group['SuspendedProcesses']])
except AttributeError:
# New ASG being created, no suspended_processes defined yet
suspended_processes = set()
if suspend_processes == suspended_processes:
return False
resume_processes = list(suspended_processes - suspend_processes)
if resume_processes:
resume_asg_processes(ec2_connection, module.params.get('name'), resume_processes)
if suspend_processes:
suspend_asg_processes(ec2_connection, module.params.get('name'), list(suspend_processes))
return True
def create_autoscaling_group(connection):
group_name = module.params.get('name')
load_balancers = module.params['load_balancers']
target_group_arns = module.params['target_group_arns']
availability_zones = module.params['availability_zones']
launch_config_name = module.params.get('launch_config_name')
min_size = module.params['min_size']
max_size = module.params['max_size']
placement_group = module.params.get('placement_group')
desired_capacity = module.params.get('desired_capacity')
vpc_zone_identifier = module.params.get('vpc_zone_identifier')
set_tags = module.params.get('tags')
health_check_period = module.params.get('health_check_period')
health_check_type = module.params.get('health_check_type')
default_cooldown = module.params.get('default_cooldown')
wait_for_instances = module.params.get('wait_for_instances')
wait_timeout = module.params.get('wait_timeout')
termination_policies = module.params.get('termination_policies')
notification_topic = module.params.get('notification_topic')
notification_types = module.params.get('notification_types')
metrics_collection = module.params.get('metrics_collection')
metrics_granularity = module.params.get('metrics_granularity')
metrics_list = module.params.get('metrics_list')
try:
as_groups = describe_autoscaling_groups(connection, group_name)
except (botocore.exceptions.ClientError, botocore.exceptions.BotoCoreError) as e:
module.fail_json(msg="Failed to describe auto scaling groups.",
exception=traceback.format_exc())
if not vpc_zone_identifier and not availability_zones:
region, ec2_url, aws_connect_params = get_aws_connection_info(module, boto3=True)
ec2_connection = boto3_conn(module,
conn_type='client',
resource='ec2',
region=region,
endpoint=ec2_url,
**aws_connect_params)
elif vpc_zone_identifier:
vpc_zone_identifier = ','.join(vpc_zone_identifier)
asg_tags = []
for tag in set_tags:
for k, v in tag.items():
if k != 'propagate_at_launch':
asg_tags.append(dict(Key=k,
Value=to_native(v),
PropagateAtLaunch=bool(tag.get('propagate_at_launch', True)),
ResourceType='auto-scaling-group',
ResourceId=group_name))
if not as_groups:
if not vpc_zone_identifier and not availability_zones:
availability_zones = module.params['availability_zones'] = [zone['ZoneName'] for
zone in ec2_connection.describe_availability_zones()['AvailabilityZones']]
enforce_required_arguments()
try:
launch_configs = describe_launch_configurations(connection, launch_config_name)
except (botocore.exceptions.ClientError, botocore.exceptions.BotoCoreError) as e:
module.fail_json(msg="Failed to describe launch configurations",
exception=traceback.format_exc())
if len(launch_configs['LaunchConfigurations']) == 0:
module.fail_json(msg="No launch config found with name %s" % launch_config_name)
if desired_capacity is None:
desired_capacity = min_size
ag = dict(
AutoScalingGroupName=group_name,
LaunchConfigurationName=launch_configs['LaunchConfigurations'][0]['LaunchConfigurationName'],
MinSize=min_size,
MaxSize=max_size,
DesiredCapacity=desired_capacity,
Tags=asg_tags,
HealthCheckGracePeriod=health_check_period,
HealthCheckType=health_check_type,
DefaultCooldown=default_cooldown,
TerminationPolicies=termination_policies)
if vpc_zone_identifier:
ag['VPCZoneIdentifier'] = vpc_zone_identifier
if availability_zones:
ag['AvailabilityZones'] = availability_zones
if placement_group:
ag['PlacementGroup'] = placement_group
if load_balancers:
ag['LoadBalancerNames'] = load_balancers
if target_group_arns:
ag['TargetGroupARNs'] = target_group_arns
try:
create_asg(connection, **ag)
if metrics_collection:
connection.enable_metrics_collection(AutoScalingGroupName=group_name, Granularity=metrics_granularity, Metrics=metrics_list)
all_ag = describe_autoscaling_groups(connection, group_name)
if len(all_ag) == 0:
module.fail_json(msg="No auto scaling group found with the name %s" % group_name)
as_group = all_ag[0]
suspend_processes(connection, as_group)
if wait_for_instances:
wait_for_new_inst(connection, group_name, wait_timeout, desired_capacity, 'viable_instances')
if load_balancers:
wait_for_elb(connection, group_name)
# Wait for target group health if target group(s)defined
if target_group_arns:
wait_for_target_group(connection, group_name)
if notification_topic:
put_notification_config(connection, group_name, notification_topic, notification_types)
as_group = describe_autoscaling_groups(connection, group_name)[0]
asg_properties = get_properties(as_group)
changed = True
return changed, asg_properties
except botocore.exceptions.ClientError as e:
module.fail_json(msg="Failed to create Autoscaling Group.",
exception=traceback.format_exc(), **camel_dict_to_snake_dict(e.response))
except botocore.exceptions.BotoCoreError as e:
module.fail_json(msg="Failed to create Autoscaling Group.",
exception=traceback.format_exc())
else:
as_group = as_groups[0]
initial_asg_properties = get_properties(as_group)
changed = False
if suspend_processes(connection, as_group):
changed = True
# process tag changes
if len(set_tags) > 0:
have_tags = as_group.get('Tags')
want_tags = asg_tags
dead_tags = []
have_tag_keyvals = [x['Key'] for x in have_tags]
want_tag_keyvals = [x['Key'] for x in want_tags]
for dead_tag in set(have_tag_keyvals).difference(want_tag_keyvals):
changed = True
dead_tags.append(dict(ResourceId=as_group['AutoScalingGroupName'],
ResourceType='auto-scaling-group', Key=dead_tag))
have_tags = [have_tag for have_tag in have_tags if have_tag['Key'] != dead_tag]
if dead_tags:
connection.delete_tags(Tags=dead_tags)
zipped = zip(have_tags, want_tags)
if len(have_tags) != len(want_tags) or not all(x == y for x, y in zipped):
changed = True
connection.create_or_update_tags(Tags=asg_tags)
# Handle load balancer attachments/detachments
# Attach load balancers if they are specified but none currently exist
if load_balancers and not as_group['LoadBalancerNames']:
changed = True
try:
attach_load_balancers(connection, group_name, load_balancers)
except botocore.exceptions.ClientError as e:
module.fail_json(msg="Failed to update Autoscaling Group.",
exception=traceback.format_exc(), **camel_dict_to_snake_dict(e.response))
except botocore.exceptions.BotoCoreError as e:
module.fail_json(msg="Failed to update Autoscaling Group.",
exception=traceback.format_exc())
# Update load balancers if they are specified and one or more already exists
elif as_group['LoadBalancerNames']:
change_load_balancers = load_balancers is not None
# Get differences
if not load_balancers:
load_balancers = list()
wanted_elbs = set(load_balancers)
has_elbs = set(as_group['LoadBalancerNames'])
# check if all requested are already existing
if has_elbs - wanted_elbs and change_load_balancers:
# if wanted contains less than existing, then we need to delete some
elbs_to_detach = has_elbs.difference(wanted_elbs)
if elbs_to_detach:
changed = True
try:
detach_load_balancers(connection, group_name, list(elbs_to_detach))
except (botocore.exceptions.ClientError, botocore.exceptions.BotoCoreError) as e:
module.fail_json(msg="Failed to detach load balancers %s: %s." % (elbs_to_detach, to_native(e)),
exception=traceback.format_exc())
if wanted_elbs - has_elbs:
# if has contains less than wanted, then we need to add some
elbs_to_attach = wanted_elbs.difference(has_elbs)
if elbs_to_attach:
changed = True
try:
attach_load_balancers(connection, group_name, list(elbs_to_attach))
except (botocore.exceptions.ClientError, botocore.exceptions.BotoCoreError) as e:
module.fail_json(msg="Failed to attach load balancers %s: %s." % (elbs_to_attach, to_native(e)),
exception=traceback.format_exc())
# Handle target group attachments/detachments
# Attach target groups if they are specified but none currently exist
if target_group_arns and not as_group['TargetGroupARNs']:
changed = True
try:
attach_lb_target_groups(connection, group_name, target_group_arns)
except botocore.exceptions.ClientError as e:
module.fail_json(msg="Failed to update Autoscaling Group.",
exception=traceback.format_exc(), **camel_dict_to_snake_dict(e.response))
except botocore.exceptions.BotoCoreError as e:
module.fail_json(msg="Failed to update Autoscaling Group.",
exception=traceback.format_exc())
# Update target groups if they are specified and one or more already exists
elif target_group_arns is not None and as_group['TargetGroupARNs']:
# Get differences
wanted_tgs = set(target_group_arns)
has_tgs = set(as_group['TargetGroupARNs'])
# check if all requested are already existing
if has_tgs.issuperset(wanted_tgs):
# if wanted contains less than existing, then we need to delete some
tgs_to_detach = has_tgs.difference(wanted_tgs)
if tgs_to_detach:
changed = True
try:
detach_lb_target_groups(connection, group_name, list(tgs_to_detach))
except (botocore.exceptions.ClientError, botocore.exceptions.BotoCoreError) as e:
module.fail_json(msg="Failed to detach load balancer target groups %s: %s" % (tgs_to_detach, to_native(e)),
exception=traceback.format_exc())
if wanted_tgs.issuperset(has_tgs):
# if has contains less than wanted, then we need to add some
tgs_to_attach = wanted_tgs.difference(has_tgs)
if tgs_to_attach:
changed = True
try:
attach_lb_target_groups(connection, group_name, list(tgs_to_attach))
except (botocore.exceptions.ClientError, botocore.exceptions.BotoCoreError) as e:
module.fail_json(msg="Failed to attach load balancer target groups %s: %s" % (tgs_to_attach, to_native(e)),
exception=traceback.format_exc())
# check for attributes that aren't required for updating an existing ASG
# check if min_size/max_size/desired capacity have been specified and if not use ASG values
if min_size is None:
min_size = as_group['MinSize']
if max_size is None:
max_size = as_group['MaxSize']
if desired_capacity is None:
desired_capacity = as_group['DesiredCapacity']
launch_config_name = launch_config_name or as_group['LaunchConfigurationName']
try:
launch_configs = describe_launch_configurations(connection, launch_config_name)
except (botocore.exceptions.ClientError, botocore.exceptions.BotoCoreError) as e:
module.fail_json(msg="Failed to describe launch configurations",
exception=traceback.format_exc())
if len(launch_configs['LaunchConfigurations']) == 0:
module.fail_json(msg="No launch config found with name %s" % launch_config_name)
ag = dict(
AutoScalingGroupName=group_name,
LaunchConfigurationName=launch_configs['LaunchConfigurations'][0]['LaunchConfigurationName'],
MinSize=min_size,
MaxSize=max_size,
DesiredCapacity=desired_capacity,
HealthCheckGracePeriod=health_check_period,
HealthCheckType=health_check_type,
DefaultCooldown=default_cooldown,
TerminationPolicies=termination_policies)
if availability_zones:
ag['AvailabilityZones'] = availability_zones
if vpc_zone_identifier:
ag['VPCZoneIdentifier'] = vpc_zone_identifier
try:
update_asg(connection, **ag)
if metrics_collection:
connection.enable_metrics_collection(AutoScalingGroupName=group_name, Granularity=metrics_granularity, Metrics=metrics_list)
else:
connection.disable_metrics_collection(AutoScalingGroupName=group_name, Metrics=metrics_list)
except (botocore.exceptions.ClientError, botocore.exceptions.BotoCoreError) as e:
module.fail_json(msg="Failed to update autoscaling group: %s" % to_native(e),
exception=traceback.format_exc())
if notification_topic:
try:
put_notification_config(connection, group_name, notification_topic, notification_types)
except botocore.exceptions.ClientError as e:
module.fail_json(msg="Failed to update Autoscaling Group notifications.",
exception=traceback.format_exc(), **camel_dict_to_snake_dict(e.response))
except botocore.exceptions.BotoCoreError as e:
module.fail_json(msg="Failed to update Autoscaling Group notifications.",
exception=traceback.format_exc())
if wait_for_instances:
wait_for_new_inst(connection, group_name, wait_timeout, desired_capacity, 'viable_instances')
# Wait for ELB health if ELB(s)defined
if load_balancers:
module.debug('\tWAITING FOR ELB HEALTH')
wait_for_elb(connection, group_name)
# Wait for target group health if target group(s)defined
if target_group_arns:
module.debug('\tWAITING FOR TG HEALTH')
wait_for_target_group(connection, group_name)
try:
as_group = describe_autoscaling_groups(connection, group_name)[0]
asg_properties = get_properties(as_group)
if asg_properties != initial_asg_properties:
changed = True
except botocore.exceptions.ClientError as e:
module.fail_json(msg="Failed to read existing Autoscaling Groups.",
exception=traceback.format_exc(), **camel_dict_to_snake_dict(e.response))
except botocore.exceptions.BotoCoreError as e:
module.fail_json(msg="Failed to read existing Autoscaling Groups.",
exception=traceback.format_exc())
return changed, asg_properties
def delete_autoscaling_group(connection):
group_name = module.params.get('name')
notification_topic = module.params.get('notification_topic')
wait_for_instances = module.params.get('wait_for_instances')
wait_timeout = module.params.get('wait_timeout')
if notification_topic:
del_notification_config(connection, group_name, notification_topic)
groups = describe_autoscaling_groups(connection, group_name)
if groups:
wait_timeout = time.time() + wait_timeout
if not wait_for_instances:
delete_asg(connection, group_name, force_delete=True)
else:
updated_params = dict(AutoScalingGroupName=group_name, MinSize=0, MaxSize=0, DesiredCapacity=0)
update_asg(connection, **updated_params)
instances = True
while instances and wait_for_instances and wait_timeout >= time.time():
tmp_groups = describe_autoscaling_groups(connection, group_name)
if tmp_groups:
tmp_group = tmp_groups[0]
if not tmp_group.get('Instances'):
instances = False
time.sleep(10)
if wait_timeout <= time.time():
# waiting took too long
module.fail_json(msg="Waited too long for old instances to terminate. %s" % time.asctime())
delete_asg(connection, group_name, force_delete=False)
while describe_autoscaling_groups(connection, group_name) and wait_timeout >= time.time():
time.sleep(5)
if wait_timeout <= time.time():
# waiting took too long
module.fail_json(msg="Waited too long for ASG to delete. %s" % time.asctime())
return True
return False
def get_chunks(l, n):
for i in range(0, len(l), n):
yield l[i:i + n]
def update_size(connection, group, max_size, min_size, dc):
module.debug("setting ASG sizes")
module.debug("minimum size: %s, desired_capacity: %s, max size: %s" % (min_size, dc, max_size))
updated_group = dict()
updated_group['AutoScalingGroupName'] = group['AutoScalingGroupName']
updated_group['MinSize'] = min_size
updated_group['MaxSize'] = max_size
updated_group['DesiredCapacity'] = dc
update_asg(connection, **updated_group)
def replace(connection):
batch_size = module.params.get('replace_batch_size')
wait_timeout = module.params.get('wait_timeout')
group_name = module.params.get('name')
max_size = module.params.get('max_size')
min_size = module.params.get('min_size')
desired_capacity = module.params.get('desired_capacity')
lc_check = module.params.get('lc_check')
replace_instances = module.params.get('replace_instances')
replace_all_instances = module.params.get('replace_all_instances')
as_group = describe_autoscaling_groups(connection, group_name)[0]
if desired_capacity is None:
desired_capacity = as_group['DesiredCapacity']
wait_for_new_inst(connection, group_name, wait_timeout, as_group['MinSize'], 'viable_instances')
props = get_properties(as_group)
instances = props['instances']
if replace_all_instances:
# If replacing all instances, then set replace_instances to current set
# This allows replace_instances and replace_all_instances to behave same
replace_instances = instances
if replace_instances:
instances = replace_instances
# check to see if instances are replaceable if checking launch configs
new_instances, old_instances = get_instances_by_lc(props, lc_check, instances)
num_new_inst_needed = desired_capacity - len(new_instances)
if lc_check:
if num_new_inst_needed == 0 and old_instances:
module.debug("No new instances needed, but old instances are present. Removing old instances")
terminate_batch(connection, old_instances, instances, True)
as_group = describe_autoscaling_groups(connection, group_name)[0]
props = get_properties(as_group)
changed = True
return(changed, props)
# we don't want to spin up extra instances if not necessary
if num_new_inst_needed < batch_size:
module.debug("Overriding batch size to %s" % num_new_inst_needed)
batch_size = num_new_inst_needed
if not old_instances:
changed = False
return(changed, props)
# check if min_size/max_size/desired capacity have been specified and if not use ASG values
if min_size is None:
min_size = as_group['MinSize']
if max_size is None:
max_size = as_group['MaxSize']
# set temporary settings and wait for them to be reached
# This should get overwritten if the number of instances left is less than the batch size.
as_group = describe_autoscaling_groups(connection, group_name)[0]
update_size(connection, as_group, max_size + batch_size, min_size + batch_size, desired_capacity + batch_size)
wait_for_new_inst(connection, group_name, wait_timeout, as_group['MinSize'] + batch_size, 'viable_instances')
wait_for_elb(connection, group_name)
wait_for_target_group(connection, group_name)
as_group = describe_autoscaling_groups(connection, group_name)[0]
props = get_properties(as_group)
instances = props['instances']
if replace_instances:
instances = replace_instances
module.debug("beginning main loop")
for i in get_chunks(instances, batch_size):
# break out of this loop if we have enough new instances
break_early, desired_size, term_instances = terminate_batch(connection, i, instances, False)
wait_for_term_inst(connection, term_instances)
wait_for_new_inst(connection, group_name, wait_timeout, desired_size, 'viable_instances')
wait_for_elb(connection, group_name)
wait_for_target_group(connection, group_name)
as_group = describe_autoscaling_groups(connection, group_name)[0]
if break_early:
module.debug("breaking loop")
break
update_size(connection, as_group, max_size, min_size, desired_capacity)
as_group = describe_autoscaling_groups(connection, group_name)[0]
asg_properties = get_properties(as_group)
module.debug("Rolling update complete.")
changed = True
return(changed, asg_properties)
def get_instances_by_lc(props, lc_check, initial_instances):
new_instances = []
old_instances = []
# old instances are those that have the old launch config
if lc_check:
for i in props['instances']:
if props['instance_facts'][i]['launch_config_name'] == props['launch_config_name']:
new_instances.append(i)
else:
old_instances.append(i)
else:
module.debug("Comparing initial instances with current: %s" % initial_instances)
for i in props['instances']:
if i not in initial_instances:
new_instances.append(i)
else:
old_instances.append(i)
module.debug("New instances: %s, %s" % (len(new_instances), new_instances))
module.debug("Old instances: %s, %s" % (len(old_instances), old_instances))
return new_instances, old_instances
def list_purgeable_instances(props, lc_check, replace_instances, initial_instances):
instances_to_terminate = []
instances = (inst_id for inst_id in replace_instances if inst_id in props['instances'])
# check to make sure instances given are actually in the given ASG
# and they have a non-current launch config
if lc_check:
for i in instances:
if props['instance_facts'][i]['launch_config_name'] != props['launch_config_name']:
instances_to_terminate.append(i)
else:
for i in instances:
if i in initial_instances:
instances_to_terminate.append(i)
return instances_to_terminate
def terminate_batch(connection, replace_instances, initial_instances, leftovers=False):
batch_size = module.params.get('replace_batch_size')
min_size = module.params.get('min_size')
desired_capacity = module.params.get('desired_capacity')
group_name = module.params.get('name')
lc_check = module.params.get('lc_check')
decrement_capacity = False
break_loop = False
as_group = describe_autoscaling_groups(connection, group_name)[0]
if desired_capacity is None:
desired_capacity = as_group['DesiredCapacity']
props = get_properties(as_group)
desired_size = as_group['MinSize']
new_instances, old_instances = get_instances_by_lc(props, lc_check, initial_instances)
num_new_inst_needed = desired_capacity - len(new_instances)
# check to make sure instances given are actually in the given ASG
# and they have a non-current launch config
instances_to_terminate = list_purgeable_instances(props, lc_check, replace_instances, initial_instances)
module.debug("new instances needed: %s" % num_new_inst_needed)
module.debug("new instances: %s" % new_instances)
module.debug("old instances: %s" % old_instances)
module.debug("batch instances: %s" % ",".join(instances_to_terminate))
if num_new_inst_needed == 0:
decrement_capacity = True
if as_group['MinSize'] != min_size:
updated_params = dict(AutoScalingGroupName=as_group['AutoScalingGroupName'], MinSize=min_size)
update_asg(connection, **updated_params)
module.debug("Updating minimum size back to original of %s" % min_size)
# if are some leftover old instances, but we are already at capacity with new ones
# we don't want to decrement capacity
if leftovers:
decrement_capacity = False
break_loop = True
instances_to_terminate = old_instances
desired_size = min_size
module.debug("No new instances needed")
if num_new_inst_needed < batch_size and num_new_inst_needed != 0:
instances_to_terminate = instances_to_terminate[:num_new_inst_needed]
decrement_capacity = False
break_loop = False
module.debug("%s new instances needed" % num_new_inst_needed)
module.debug("decrementing capacity: %s" % decrement_capacity)
for instance_id in instances_to_terminate:
elb_dreg(connection, group_name, instance_id)
module.debug("terminating instance: %s" % instance_id)
terminate_asg_instance(connection, instance_id, decrement_capacity)
# we wait to make sure the machines we marked as Unhealthy are
# no longer in the list
return break_loop, desired_size, instances_to_terminate
def wait_for_term_inst(connection, term_instances):
wait_timeout = module.params.get('wait_timeout')
group_name = module.params.get('name')
as_group = describe_autoscaling_groups(connection, group_name)[0]
count = 1
wait_timeout = time.time() + wait_timeout
while wait_timeout > time.time() and count > 0:
module.debug("waiting for instances to terminate")
count = 0
as_group = describe_autoscaling_groups(connection, group_name)[0]
props = get_properties(as_group)
instance_facts = props['instance_facts']
instances = (i for i in instance_facts if i in term_instances)
for i in instances:
lifecycle = instance_facts[i]['lifecycle_state']
health = instance_facts[i]['health_status']
module.debug("Instance %s has state of %s,%s" % (i, lifecycle, health))
if lifecycle.startswith('Terminating') or health == 'Unhealthy':
count += 1
time.sleep(10)
if wait_timeout <= time.time():
# waiting took too long
module.fail_json(msg="Waited too long for old instances to terminate. %s" % time.asctime())
def wait_for_new_inst(connection, group_name, wait_timeout, desired_size, prop):
# make sure we have the latest stats after that last loop.
as_group = describe_autoscaling_groups(connection, group_name)[0]
props = get_properties(as_group)
module.debug("Waiting for %s = %s, currently %s" % (prop, desired_size, props[prop]))
# now we make sure that we have enough instances in a viable state
wait_timeout = time.time() + wait_timeout
while wait_timeout > time.time() and desired_size > props[prop]:
module.debug("Waiting for %s = %s, currently %s" % (prop, desired_size, props[prop]))
time.sleep(10)
as_group = describe_autoscaling_groups(connection, group_name)[0]
props = get_properties(as_group)
if wait_timeout <= time.time():
# waiting took too long
module.fail_json(msg="Waited too long for new instances to become viable. %s" % time.asctime())
module.debug("Reached %s: %s" % (prop, desired_size))
return props
def asg_exists(connection):
group_name = module.params.get('name')
as_group = describe_autoscaling_groups(connection, group_name)
return bool(len(as_group))
def main():
argument_spec = ec2_argument_spec()
argument_spec.update(
dict(
name=dict(required=True, type='str'),
load_balancers=dict(type='list'),
target_group_arns=dict(type='list'),
availability_zones=dict(type='list'),
launch_config_name=dict(type='str'),
min_size=dict(type='int'),
max_size=dict(type='int'),
placement_group=dict(type='str'),
desired_capacity=dict(type='int'),
vpc_zone_identifier=dict(type='list'),
replace_batch_size=dict(type='int', default=1),
replace_all_instances=dict(type='bool', default=False),
replace_instances=dict(type='list', default=[]),
lc_check=dict(type='bool', default=True),
wait_timeout=dict(type='int', default=300),
state=dict(default='present', choices=['present', 'absent']),
tags=dict(type='list', default=[]),
health_check_period=dict(type='int', default=300),
health_check_type=dict(default='EC2', choices=['EC2', 'ELB']),
default_cooldown=dict(type='int', default=300),
wait_for_instances=dict(type='bool', default=True),
termination_policies=dict(type='list', default='Default'),
notification_topic=dict(type='str', default=None),
notification_types=dict(type='list', default=[
'autoscaling:EC2_INSTANCE_LAUNCH',
'autoscaling:EC2_INSTANCE_LAUNCH_ERROR',
'autoscaling:EC2_INSTANCE_TERMINATE',
'autoscaling:EC2_INSTANCE_TERMINATE_ERROR'
]),
suspend_processes=dict(type='list', default=[]),
metrics_collection=dict(type='bool', default=False),
metrics_granularity=dict(type='str', default='1Minute'),
metrics_list=dict(type='list', default=[
'GroupMinSize',
'GroupMaxSize',
'GroupDesiredCapacity',
'GroupInServiceInstances',
'GroupPendingInstances',
'GroupStandbyInstances',
'GroupTerminatingInstances',
'GroupTotalInstances'
])
),
)
global module
module = AnsibleModule(
argument_spec=argument_spec,
mutually_exclusive=[['replace_all_instances', 'replace_instances']]
)
if not HAS_BOTO3:
module.fail_json(msg='boto3 required for this module')
state = module.params.get('state')
replace_instances = module.params.get('replace_instances')
replace_all_instances = module.params.get('replace_all_instances')
region, ec2_url, aws_connect_params = get_aws_connection_info(module, boto3=True)
connection = boto3_conn(module,
conn_type='client',
resource='autoscaling',
region=region,
endpoint=ec2_url,
**aws_connect_params)
changed = create_changed = replace_changed = False
exists = asg_exists(connection)
if state == 'present':
create_changed, asg_properties = create_autoscaling_group(connection)
elif state == 'absent':
changed = delete_autoscaling_group(connection)
module.exit_json(changed=changed)
# Only replace instances if asg existed at start of call
if exists and (replace_all_instances or replace_instances):
replace_changed, asg_properties = replace(connection)
if create_changed or replace_changed:
changed = True
module.exit_json(changed=changed, **asg_properties)
if __name__ == '__main__':
main()