Python AutoScaleConnection.get_all_policies方法代码示例

# 需要导入模块: from boto.ec2.autoscale import AutoScaleConnection [as 别名]
# 或者: from boto.ec2.autoscale.AutoScaleConnection import get_all_policies [as 别名]
class BotoScaleInterface(ScaleInterface):
    conn = None
    saveclcdata = False

    def __init__(self, clc_host, access_id, secret_key, token):
        self.access_id = access_id
        self.secret_key = secret_key
        self.token = token
        self.set_endpoint(clc_host)

    def set_endpoint(self, endpoint):
        #boto.set_stream_logger('scale')
        path = '/services/AutoScaling'
        reg = RegionInfo(name='eucalyptus', endpoint=endpoint)
        port = 8773
        if endpoint[len(endpoint)-13:] == 'amazonaws.com':
            endpoint = endpoint.replace('ec2', 'autoscaling', 1)
            path = '/'
            reg = RegionInfo(endpoint=endpoint)
            port = 443
        self.conn = AutoScaleConnection(self.access_id, self.secret_key, region=reg,
                                  port=port, path=path,
                                  is_secure=True, security_token=self.token, debug=0)
        self.conn.APIVersion = '2011-01-01'
        if not(endpoint[len(endpoint)-13:] == 'amazonaws.com'):
            self.conn.auth_region_name = 'Eucalyptus'
        self.conn.https_validate_certificates = False
        self.conn.http_connection_kwargs['timeout'] = 30

    def __save_json__(self, obj, name):
        f = open(name, 'w')
        json.dump(obj, f, cls=BotoJsonScaleEncoder, indent=2)
        f.close()

    ##
    # autoscaling methods
    ##
    def create_auto_scaling_group(self, as_group):
        return self.conn.create_auto_scaling_group(as_group)

    def delete_auto_scaling_group(self, name, force_delete=False):
        return self.conn.delete_auto_scaling_group(name, force_delete)

    def get_all_groups(self, names=None, max_records=None, next_token=None):
        obj = self.conn.get_all_groups(names, max_records, next_token)
        if self.saveclcdata:
            self.__save_json__(obj, "mockdata/AS_Groups.json")
        return obj

    def get_all_autoscaling_instances(self, instance_ids=None, max_records=None, next_token=None):
        obj = self.conn.get_all_autoscaling_instances(instance_ids, max_records, next_token)
        if self.saveclcdata:
            self.__save_json__(obj, "mockdata/AS_Instances.json")
        return obj

    def set_desired_capacity(self, group_name, desired_capacity, honor_cooldown=False):
        group = self.conn.get_all_groups([group_name])[0];
        # notice, honor_cooldown not supported.
        return group.set_capacity(desired_capacity)

    def set_instance_health(self, instance_id, health_status, should_respect_grace_period=True):
        return self.conn.set_instance_health(instance_id, health_status,
                                             should_respect_grace_period)

    def terminate_instance(self, instance_id, decrement_capacity=True):
        return self.conn.terminate_instance(instance_id, decrement_capacity)

    def update_autoscaling_group(self, as_group):
        as_group.connection = self.conn
        return as_group.update()

    def create_launch_configuration(self, launch_config):
        return self.conn.create_launch_configuration(launch_config)

    def delete_launch_configuration(self, launch_config_name):
        return self.conn.delete_launch_configuration(launch_config_name)

    def get_all_launch_configurations(self, config_names=None, max_records=None, next_token=None):
        obj = self.conn.get_all_launch_configurations(names=config_names, max_records=max_records,
                                                      next_token=next_token)
        if self.saveclcdata:
            self.__save_json__(obj, "mockdata/AS_LaunchConfigs.json")
        return obj

    # policy related
    def delete_policy(self, policy_name, autoscale_group=None):
        return self.conn.delete_policy(policy_name, autoscale_group)

    def get_all_policies(self, as_group=None, policy_names=None, max_records=None, next_token=None):
        obj = self.conn.get_all_policies(as_group, policy_names, max_records, next_token)
        if self.saveclcdata:
            self.__save_json__(obj, "mockdata/AS_Policies.json")
        return obj

    def execute_policy(self, policy_name, as_group=None, honor_cooldown=None):
        return self.conn.execute_policy(policy_name, as_group, honor_cooldown)

    def create_scaling_policy(self, scaling_policy):
        return self.conn.create_scaling_policy(scaling_policy)

#.........这里部分代码省略.........

# 需要导入模块: from boto.ec2.autoscale import AutoScaleConnection [as 别名]
# 或者: from boto.ec2.autoscale.AutoScaleConnection import get_all_policies [as 别名]
def create_autoscaling(ami_id, sns_arn):
    """
    Creates the autoscaling group for proxy instances
    Inspired by boto autoscaling tutorial.
    """
    con = AutoScaleConnection(aws_secret_access_key=AWS_SECRET_ACCESS_KEY,
                              aws_access_key_id=AWS_ACCESS_KEY,
                              region=RegionInfo(name=REGION,
                                               endpoint='autoscaling.%s.amazonaws.com' % REGION))



    print "Creating autoscaling configuration.."
    config = LaunchConfiguration(name=AUTOSCALING_GROUP_NAME,
                                 image_id=ami_id,
                                 key_name=KEY_NAME,
                                 security_groups=[EC2_SECURITY_GROUP_NAME],
                                 instance_type=INSTANCE_TYPE)

    con.create_launch_configuration(config)


    print "Create autoscaling group..."
    ag = AutoScalingGroup(name=AUTOSCALING_GROUP_NAME,
                          launch_config=config,
                          availability_zones=["{0}a".format(REGION)],
                          load_balancers=[ELB_NAME],
                          min_size=AUTOSCALING_MIN_INSTANCES,
                          max_size=AUTOSCALING_MAX_INSTANCES,
                          group_name=AUTOSCALING_GROUP_NAME)
    con.create_auto_scaling_group(ag)

    # fetch the autoscale group after it is created (unused but may be necessary)
    _ = con.get_all_groups(names=[AUTOSCALING_GROUP_NAME])[0]

    # Create tag name for autoscaling-created machines
    as_tag = Tag(key='Name', value=AUTOSCALING_GROUP_NAME, propagate_at_launch=True, resource_id=AUTOSCALING_GROUP_NAME)
    con.create_or_update_tags([as_tag])


    print "Creating autoscaling policy..."
    scaleup_policy = ScalingPolicy(name='scale_up',
                                   adjustment_type='ChangeInCapacity',
                                   as_name=AUTOSCALING_GROUP_NAME,
                                   scaling_adjustment=1,
                                   cooldown=AUTOSCALING_COOLDOWN_PERIOD)

    scaledown_policy = ScalingPolicy(name='scale_down',
                                     adjustment_type='ChangeInCapacity',
                                     as_name=AUTOSCALING_GROUP_NAME,
                                     scaling_adjustment=-1,
                                     cooldown=AUTOSCALING_COOLDOWN_PERIOD)

    con.create_scaling_policy(scaleup_policy)
    con.create_scaling_policy(scaledown_policy)

    # Get freshened policy objects
    scaleup_policy = con.get_all_policies(as_group=AUTOSCALING_GROUP_NAME, policy_names=['scale_up'])[0]
    scaledown_policy = con.get_all_policies(as_group=AUTOSCALING_GROUP_NAME, policy_names=['scale_down'])[0]

    print "Creating cloudwatch alarms"
    cloudwatch_con = CloudWatchConnection(aws_secret_access_key=AWS_SECRET_ACCESS_KEY,
                                      aws_access_key_id=AWS_ACCESS_KEY,
                                      region=RegionInfo(name=REGION,
                                                        endpoint='monitoring.%s.amazonaws.com' % REGION))


    alarm_dimensions = {"AutoScalingGroupName": AUTOSCALING_GROUP_NAME}
    scaleup_alarm = MetricAlarm(name='scale_up_on_cpu',
                                namespace='AWS/EC2',
                                metric='CPUUtilization',
                                statistic='Average',
                                comparison='>',
                                threshold=AUTOSCALING_CPU_MAX_THRESHOLD,
                                period='60',
                                evaluation_periods=1,
                                alarm_actions=[scaleup_policy.policy_arn, sns_arn],
                                dimensions=alarm_dimensions)

    # Don't send SNS on scaledown policy
    scaledown_alarm = MetricAlarm(name='scale_down_on_cpu',
                                 namespace='AWS/EC2',
                                 metric='CPUUtilization',
                                 statistic='Average',
                                 comparison='<',
                                 threshold=AUTOSCALING_CPU_MIN_THRESHOLD,
                                 period='60',
                                 evaluation_periods=1,
                                 alarm_actions=[scaledown_policy.policy_arn],
                                 dimensions=alarm_dimensions)
    cloudwatch_con.create_alarm(scaleup_alarm)
    cloudwatch_con.create_alarm(scaledown_alarm)

# 需要导入模块: from boto.ec2.autoscale import AutoScaleConnection [as 别名]
# 或者: from boto.ec2.autoscale.AutoScaleConnection import get_all_policies [as 别名]

#.........这里部分代码省略.........
        lc = lcs[0] if lcs else None
        if not lc:
            lc = LaunchConfiguration(
                name=name,
                image_id=image,
                key_name=key_name,
                security_groups=[security_groups],
                instance_type=instance_type,
            )
            self.auto_scale_conn.create_launch_configuration(lc)
        return lc

    def remove_launch_configuration(self, name):
        self.auto_scale_conn.delete_launch_configuration(name)

    def create_autoscaling_group(self, name, lb_name, zone, tags, instance_ids=None):
        lc = self.create_launch_configuration()
        as_groups = [a for a in self.auto_scale_conn.get_all_groups() if a.name == name]
        as_group = as_groups[0] if as_groups else None
        if not as_group:
            as_group = AutoScalingGroup(
                group_name=name,
                load_balancers=[lb_name],
                availability_zones=[zone],
                launch_config=lc,
                min_size=4,
                max_size=4,
                health_check_type="ELB",
                health_check_period=120,
                connection=self.auto_scale_conn,
                default_cooldown=self.default_cooldown,
                desired_capacity=4,
                tags=tags,
            )

            self.auto_scale_conn.create_auto_scaling_group(as_group)
            if instance_ids:
                self.auto_scale_conn.attach_instances(name, instance_ids)

            scale_up_policy = ScalingPolicy(
                name="scale_up",
                adjustment_type="ChangeInCapacity",
                as_name=name,
                scaling_adjustment=1,
                cooldown=self.default_cooldown,
            )
            scale_down_policy = ScalingPolicy(
                name="scale_down",
                adjustment_type="ChangeInCapacity",
                as_name=name,
                scaling_adjustment=-1,
                cooldown=self.default_cooldown,
            )

            self.auto_scale_conn.create_scaling_policy(scale_up_policy)
            self.auto_scale_conn.create_scaling_policy(scale_down_policy)

            scale_up_policy = self.auto_scale_conn.get_all_policies(as_group=name, policy_names=["scale_up"])[0]
            scale_down_policy = self.auto_scale_conn.get_all_policies(as_group=name, policy_names=["scale_down"])[0]

            alarm_dimensions = {"AutoScalingGroupName": name}
            scale_up_alarm = MetricAlarm(
                name="scale_up_on_cpu",
                namespace="AWS/EC2",
                metric="CPUUtilization",
                statistic="Average",
                comparison=">",
                threshold=85,
                period=60,
                evaluation_periods=1,
                alarm_actions=[scale_up_policy.policy_arn],
                dimensions=alarm_dimensions,
            )
            self.cloud_watch_conn.create_alarm(scale_up_alarm)
            scale_down_alarm = MetricAlarm(
                name="scale_down_on_cpu",
                namespace="AWS/EC2",
                metric="CPUUtilization",
                statistic="Average",
                comparison="<",
                threshold=60,
                period=60,
                evaluation_periods=1,
                alarm_actions=[scale_down_policy.policy_arn],
                dimensions=alarm_dimensions,
            )
            self.cloud_watch_conn.create_alarm(scale_down_alarm)

        return as_group

    def update_autoscaling_group_max_size(self, as_group, max_size):
        setattr(as_group, "max_size", max_size)
        as_group.update()

    def update_autoscaling_group_min_size(self, as_group, min_size):
        setattr(as_group, "min_size", min_size)
        as_group.update()

    def remove_autoscaling_group(self, name):
        self.auto_scale_conn.delete_auto_scaling_group(name)

# 需要导入模块: from boto.ec2.autoscale import AutoScaleConnection [as 别名]
# 或者: from boto.ec2.autoscale.AutoScaleConnection import get_all_policies [as 别名]
    def test_basic(self):
        # NB: as it says on the tin these are really basic tests that only
        # (lightly) exercise read-only behaviour - and that's only if you
        # have any autoscale groups to introspect. It's useful, however, to
        # catch simple errors

        print('--- running %s tests ---' % self.__class__.__name__)
        c = AutoScaleConnection()

        self.assertTrue(repr(c).startswith('AutoScaleConnection'))

        groups = c.get_all_groups()
        for group in groups:
            self.assertIsInstance(group, AutoScalingGroup)

            # get activities
            activities = group.get_activities()

            for activity in activities:
                self.assertIsInstance(activity, Activity)

        # get launch configs
        configs = c.get_all_launch_configurations()
        for config in configs:
            self.assertIsInstance(config, LaunchConfiguration)

        # get policies
        policies = c.get_all_policies()
        for policy in policies:
            self.assertIsInstance(policy, ScalingPolicy)

        # get scheduled actions
        actions = c.get_all_scheduled_actions()
        for action in actions:
            self.assertIsInstance(action, ScheduledUpdateGroupAction)

        # get instances
        instances = c.get_all_autoscaling_instances()
        for instance in instances:
            self.assertIsInstance(instance, Instance)

        # get all scaling process types
        ptypes = c.get_all_scaling_process_types()
        for ptype in ptypes:
            self.assertTrue(ptype, ProcessType)

        # get adjustment types
        adjustments = c.get_all_adjustment_types()
        for adjustment in adjustments:
            self.assertIsInstance(adjustment, AdjustmentType)

        # get metrics collection types
        types = c.get_all_metric_collection_types()
        self.assertIsInstance(types, MetricCollectionTypes)

        # create the simplest possible AutoScale group
        # first create the launch configuration
        time_string = '%d' % int(time.time())
        lc_name = 'lc-%s' % time_string
        lc = LaunchConfiguration(name=lc_name, image_id='ami-2272864b',
                                 instance_type='t1.micro')
        c.create_launch_configuration(lc)
        found = False
        lcs = c.get_all_launch_configurations()
        for lc in lcs:
            if lc.name == lc_name:
                found = True
                break
        assert found

        # now create autoscaling group
        group_name = 'group-%s' % time_string
        group = AutoScalingGroup(name=group_name, launch_config=lc,
                                 availability_zones=['us-east-1a'],
                                 min_size=1, max_size=1)
        c.create_auto_scaling_group(group)
        found = False
        groups = c.get_all_groups()
        for group in groups:
            if group.name == group_name:
                found = True
                break
        assert found

        # now create a tag
        tag = Tag(key='foo', value='bar', resource_id=group_name,
                  propagate_at_launch=True)
        c.create_or_update_tags([tag])

        found = False
        tags = c.get_all_tags()
        for tag in tags:
            if tag.resource_id == group_name and tag.key == 'foo':
                found = True
                break
        assert found

        c.delete_tags([tag])

        # shutdown instances and wait for them to disappear
#.........这里部分代码省略.........

# 需要导入模块: from boto.ec2.autoscale import AutoScaleConnection [as 别名]
# 或者: from boto.ec2.autoscale.AutoScaleConnection import get_all_policies [as 别名]
scaleOut = ScalingPolicy(name='ScaleOut',
                         adjustment_type='ChangeInCapacity',
                         as_name=asg.name,
                         scaling_adjustment=1,
                         cooldown=100)

scaleIn = ScalingPolicy(name='ScaleIn',
                        adjustment_type='ChangeInCapacity',
                        as_name=asg.name,
                        scaling_adjustment=-1,
                        cooldown=100)

con_as.create_scaling_policy(scaleOut)
con_as.create_scaling_policy(scaleIn)

scaleOut_policy = con_as.get_all_policies(
            as_group=asg.name, policy_names=['ScaleOut'])[0]
scaleIn_policy = con_as.get_all_policies(
            as_group=asg.name, policy_names=['ScaleIn'])[0]

# -------------------------Create CloudWatch Alarm------------------------------
con_cw = CloudWatchConnection()

alarm_dimensions = {"AutoScalingGroupName": asg.name}

scaleOut_alarm = MetricAlarm(name='scaleOut_on_cpu',
                             namespace='AWS/EC2',
                             metric='CPUUtilization',
                             statistic='Average',
                             comparison='>',
                             threshold='70',
                             period='120',

# 需要导入模块: from boto.ec2.autoscale import AutoScaleConnection [as 别名]
# 或者: from boto.ec2.autoscale.AutoScaleConnection import get_all_policies [as 别名]
print 'Creating ASG'
asg = AutoScalingGroup(group_name='Project22group', load_balancers=['Project22hongf'], health_check_type = 'ELB', health_check_period = '119', desired_capacity = 5, availability_zones=['us-east-1c'], launch_config = lc, min_size = 5, max_size = 5, tags = [boto.ec2.autoscale.tag.Tag(key='Project',value='2.2', resource_id = 'Project22group', propagate_at_launch=True)])
asg_conn.create_auto_scaling_group(asg)
print 'ASG created'

#Create Scaling Policy

print 'Creating Scaling Policy'
scale_out_policy = ScalingPolicy(name = 'scale_out', adjustment_type = 'ChangeInCapacity', as_name = 'Project22group', scaling_adjustment = 1, cooldown = 60)
asg_conn.create_scaling_policy(scale_out_policy)
scale_in_policy = ScalingPolicy(name = 'scale_in', adjustment_type = 'ChangeInCapacity', as_name = 'Project22group', scaling_adjustment = -1, cooldown = 60)
asg_conn.create_scaling_policy(scale_in_policy)

#Check Policys and get them for CloudWatch
ScaleOut = asg_conn.get_all_policies(as_group = 'Project22group', policy_names = ['scale_out'])[0]
ScaleIn = asg_conn.get_all_policies(as_group = 'Project22group', policy_names = ['scale_in'])[0]
print 'Scaling Policy created'

#Create CloudWatch

alarm_dimensions = {"AutoScalingGroupName": 'Project22group'}
scale_out_alarm = MetricAlarm(name = 'scale_out', namespace = 'AWS/EC2', metric = 'CPUUtilization', statistic='Average', comparison='>', threshold='80', period = '60', evaluation_periods=5, alarm_actions=[ScaleOut.policy_arn], dimensions=alarm_dimensions)
cw_conn.create_alarm(scale_out_alarm)
scale_in_alarm = MetricAlarm(name = 'scale_in', namespace = 'AWS/EC2', metric = 'CPUUtilization', statistic='Average', comparison='<', threshold='20', period = '60', evaluation_periods=5, alarm_actions=[ScaleIn.policy_arn], dimensions=alarm_dimensions)
cw_conn.create_alarm(scale_in_alarm)
print'CloudWatch Alarm created'

# 需要导入模块: from boto.ec2.autoscale import AutoScaleConnection [as 别名]
# 或者: from boto.ec2.autoscale.AutoScaleConnection import get_all_policies [as 别名]
class AutoScale:

    def __init__(self, args):
        """
        Initializing basic variables needed for auto scaling
        """
        self.configs                = ConfigParser.RawConfigParser()
        self.args                   = args
        self.test_props             = {}
        self.props                  = {}
        self.ec2_connection         = EC2Connection(self.args.access_key, self.args.secret_key)
        self.autoscale_connection   = AutoScaleConnection(self.args.access_key, self.args.secret_key)
        self.elb_connection         = ELBConnection(self.args.access_key, self.args.secret_key)
        self.cw_connection          = CloudWatchConnection(self.args.access_key, self.args.secret_key)
        self.firstInstance          = None
        self.launchConfiguration    = None
        self.healthCheck            = None

    def loadConfigs(self):
        """
        FIX ME: Currently doesnt do anything
        This method will load the configurations from boto config file if present else will 
        accept parameters passed by user.
        """
        if os.path.isfile("/etc/boto.cfg"):
            self.configs.read("/etc/boto.cfg")
            conf = self.configs.sections()
            self.populateConfigs(conf)
        if os.path.isfile("~/.boto"):
            self.configs.read("~/.boto")
            conf = self.configs.sections()
            self.populateConfigs(conf)
            
        print ">>> Loaded configs"
            
    def populateConfigs(self, sections):
        for section in sections:
            self.boto_props[section] = self.configs.items(section)
            for item in self.boto_props[section]:
                key, value = item
                if not self.props.has_key(key):
                    self.props[key] = value

    def createLaunchConfiguration(self, lc_name, ami_id, key_name):
        """
        Creates launch configuration for the auto scaling cluster
        """
        self.launchConfiguration = LaunchConfiguration(name     = lc_name, 
                                                       image_id = ami_id, 
                                                       key_name = key_name)
        self.autoscale_connection.create_launch_configuration(self.launchConfiguration)
        print ">>> Created launch configuration: " + lc_name

    def createAutoScaleGroup(self, asg_name):
        """
        Create a Auto scaling group for the auto scaling cluster
        """
        autoScalingGroup = AutoScalingGroup(group_name         = asg_name, 
                                            load_balancers     = [self.args.lb_name], 
                                            launch_config      = self.launchConfiguration, 
                                            min_size           = self.args.min_size, 
                                            max_size           = self.args.max_size, 
                                            availability_zones = ['us-east-1a'])
        self.autoscale_connection.create_auto_scaling_group(autoScalingGroup)
        print ">>> Created auto scaling group: " + asg_name

    def createTrigger(self, trigger_name, measure, asg_name):
        """
        Trigger to spawn new instances as per specific metrics
        """
        alarm_actions = []
        dimensions = {"AutoScalingGroupName" : asg_name}
        policies = self.autoscale_connection.get_all_policies(as_group=self.args.asg_name, policy_names=[self.args.asp_name])
        for policy in policies:
            alarm_actions.append(policy.policy_arn)
        alarm = MetricAlarm(name                = trigger_name, 
                            namespace           = "AWS/EC2", 
                            metric              = measure, 
                            statistic           = "Average", 
                            comparison          = ">=", 
                            threshold           = 50, 
                            period              = 60, 
                            unit                = "Percent",
                            evaluation_periods  = 2,  
                            alarm_actions       = alarm_actions, 
                            dimensions          = dimensions)
        
        self.cw_connection.create_alarm(alarm)
        print ">>> Created trigger: "+self.args.trigger

    def createAutoScalePolicy(self, asp_name):
        """
        Creates a Auto scaling policy to Add/Remove a instance from auto scaling cluster
        """
        self.autoScalingUpPolicy = ScalingPolicy(name                 = asp_name+'-up',
                                                 adjustment_type      = "ChangeInCapacity", 
                                                 as_name              = self.args.asg_name, 
                                                 scaling_adjustment   = 1, 
                                                 cooldown             = 180)
        self.autoScalingDownPolicy = ScalingPolicy(name                 = asp_name+'-down',
#.........这里部分代码省略.........

# 需要导入模块: from boto.ec2.autoscale import AutoScaleConnection [as 别名]
# 或者: from boto.ec2.autoscale.AutoScaleConnection import get_all_policies [as 别名]
scale_down_policy = ScalingPolicy(
        name='scale_down',
        adjustment_type='ChangeInCapacity',
        as_name=autoscaling_group['name'],
        scaling_adjustment=-1,
        cooldown=180
    )
conn_as.create_scaling_policy(scale_up_policy)
conn_as.create_scaling_policy(scale_down_policy)
print 'scaling policies created!'
sleep(10)

# refresh and get back the scaling policies
scale_up_policy = conn_as.get_all_policies(
        as_group=autoscaling_group['name'],
        policy_names=['scale_up'])[0]

scale_down_policy = conn_as.get_all_policies(
        as_group=autoscaling_group['name'],
        policy_names=['scale_down'])[0]

# ============================================== #



# ============================================== #
# create CloudWatch alarms for when to scale up and when to scale down
alarm_dimensions = {"AutoScalingGroupName": autoscaling_group['name']}
scale_up_alarm = MetricAlarm(
        name=metric_alarm['upAlarmName'],