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.assertTrue(type(group), AutoScalingGroup)
# get activities
activities = group.get_activities()
for activity in activities:
self.assertEqual(type(activity), Activity)
# get launch configs
configs = c.get_all_launch_configurations()
for config in configs:
self.assertTrue(type(config), LaunchConfiguration)
# get policies
policies = c.get_all_policies()
for policy in policies:
self.assertTrue(type(policy), ScalingPolicy)
# get scheduled actions
actions = c.get_all_scheduled_actions()
for action in actions:
self.assertTrue(type(action), ScheduledUpdateGroupAction)
# get instances
instances = c.get_all_autoscaling_instances()
for instance in instances:
self.assertTrue(type(instance), Instance)
# get all scaling process types
ptypes = c.get_all_scaling_process_types()
for ptype in ptypes:
self.assertTrue(type(ptype), ProcessType)
# get adjustment types
adjustments = c.get_all_adjustment_types()
for adjustment in adjustments:
self.assertTrue(type(adjustment), AdjustmentType)
# get metrics collection types
types = c.get_all_metric_collection_types()
self.assertTrue(type(types), MetricCollectionTypes)
print '--- tests completed ---'
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)
def get_all_adjustment_types(self):
return self.conn.get_all_adjustment_types()
# tag related
def delete_tags(self, tags):
return self.conn.delete_tags(tags)
def get_all_tags(self, filters=None, max_records=None, next_token=None):
obj = self.conn.get_all_tags(filters, max_records, next_token)
if self.saveclcdata:
self.__save_json__(obj, "mockdata/AS_Tags.json")
return obj
def create_or_update_tags(self, tags):
return self.conn.create_or_update_tags(tags)
def create_AutoScaling():
print "Creating AutoScaling..."
# establish connection
as_conn = AutoScaleConnection(AWSAccessKeyId, AWSSecretKey)
# create launch configuration
global lc
lc = LaunchConfiguration(name='lc',
image_id=DATA_CEN_AMI,
key_name=ACCESS_KEY,
instance_monitoring=True,
security_groups=[SECURITY_GRP],
instance_type=MACHINE_TYPE)
as_conn.create_launch_configuration(lc)
# create tag for autoscaling group
as_tag = Tag(key="Project",
value="2.2",
propagate_at_launch=True,
resource_id='my_group')
# create aotoscaling group
global ag
ag = AutoScalingGroup(group_name='my_group',
load_balancers=['myELB'],
availability_zones=['us-east-1a'],
launch_config=lc,
min_size=MIN_SIZE,
max_size=MAX_SIZE,
connection=as_conn,
tags=[as_tag])
# associate the autoscaling group with launch configuration
as_conn.create_auto_scaling_group(ag)
# build the scale policy
scale_up_policy = ScalingPolicy(name='scale_up',
adjustment_type='ChangeInCapacity',
as_name='my_group',
scaling_adjustment=1,
cooldown=60)
scale_down_policy = ScalingPolicy(name='scale_down',
adjustment_type='ChangeInCapacity',
as_name='my_group',
scaling_adjustment=-1,
cooldown=60)
# register the scale policy
as_conn.create_scaling_policy(scale_up_policy)
as_conn.create_scaling_policy(scale_down_policy)
# refresh the scale policy for extra information
scale_up_policy = as_conn.get_all_policies(as_group='my_group',
policy_names=['scale_up'])[0]
scale_down_policy = as_conn.get_all_policies(as_group='my_group',
policy_names=['scale_down'
])[0]
# create cloudwatch alarm
cloudwatch = CloudWatchConnection(aws_access_key_id=AWSAccessKeyId,
aws_secret_access_key=AWSSecretKey,
is_secure=True)
# region='us-east-1a')
# assocate cloudwatch with alarm
alarm_dimensions = {"AutoScalingGroupName": 'my_group'}
# create scale up alarm
scale_up_alarm = MetricAlarm(name='scale_up_on_cpu',
namespace='AWS/EC2',
metric='CPUUtilization',
statistic='Average',
comparison='>',
threshold='50',
period='60',
evaluation_periods=2,
alarm_actions=[scale_up_policy.policy_arn],
dimensions=alarm_dimensions)
cloudwatch.create_alarm(scale_up_alarm)
# create scale down alarm
scale_down_alarm = MetricAlarm(
name='scale_down_on_cpu',
namespace='AWS/EC2',
metric='CPUUtilization',
statistic='Average',
comparison='<',
threshold='20',
period='60',
evaluation_periods=1,
alarm_actions=[scale_down_policy.policy_arn],
dimensions=alarm_dimensions)
cloudwatch.create_alarm(scale_down_alarm)
print "AutoScaling created successfully"
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',
adjustment_type="ChangeInCapacity",
as_name=self.args.asg_name,
scaling_adjustment=-1,
cooldown=180)
self.autoscale_connection.create_scaling_policy(
self.autoScalingUpPolicy)
self.autoscale_connection.create_scaling_policy(
self.autoScalingDownPolicy)
print ">>> Created auto scaling policy: " + asp_name
def configureHealthCheck(self, target):
"""
Configures health check for the cluster
"""
self.healthCheck = HealthCheck(target=target, timeout=5)
print ">>> Configured health check for: " + target
def createLoadBalancer(self, lb_name, region, lb_port, instance_port,
protocol):
"""
Creates a load balancer for cluster
"""
listener = (int(lb_port), int(instance_port), protocol)
tuple_list = []
tuple_list.append(listener)
lbs = self.elb_connection.get_all_load_balancers()
for lb in lbs:
if lb.name != lb_name:
self.elb_connection.create_load_balancer(
lb_name, [region], tuple_list)
self.elb_connection.configure_health_check(
name=lb_name, health_check=self.healthCheck)
print ">>> Created load balancer: " + lb_name
else:
print "Load balancer with name '" + lb_name + "' already exists"
def startInstance(self, image_id, key_name, region, instance_type):
"""
Starts the first instance which will be serving requests irrespective of auto scaling
instances.
"""
reservation = self.ec2_connection.run_instances(
image_id=image_id,
min_count=1,
max_count=1,
placement=region,
key_name=key_name,
instance_type=instance_type)
# for instance in reservation.instances:
# instance.add_tag('node', '0')
# break
self.firstInstance = reservation.instances[0].id.split('\'')[0]
print ">>> Started instance: ", self.firstInstance
def registerInstanceToELB(self, lb_name):
"""
Register the first instance started to the Elastic Load Balancer.
"""
self.elb_connection.register_instances(load_balancer_name=lb_name,
instances=[self.firstInstance])
print ">>> Registered instance '", self.firstInstance, "' to load balancer '" + lb_name + "'"
def setUp(self):
"""
Set's up the auto scaling for the application
"""
# STEP 1: Load the configurations
self.loadConfigs()
# STEP 2: Configure the health check for the instances
self.configureHealthCheck(self.args.lb_target)
# STEP 3: Create a load balancer
self.createLoadBalancer(self.args.lb_name, self.args.region,
self.args.lb_port, self.args.instance_port,
self.args.protocol)
# STEP 4: Start the first instance
self.startInstance(self.args.ami_id, self.args.key_name,
self.args.region, self.args.instance_type)
# STEP 5: Register the instance to the load balancer created in STEP 4
self.registerInstanceToELB(self.args.lb_name)
# STEP 6: Create launch configuration to launch instances by auto scale
self.createLaunchConfiguration(self.args.lc_name, self.args.ami_id,
self.args.key_name)
# STEP 7: Create a auto scale group which will manage the instances started by auto scaling
self.createAutoScaleGroup(self.args.asg_name)
# STEP 8: Create a auto scaling policy to say add/remove a node
self.createAutoScalePolicy(self.args.asp_name)
# STEP 9: Create a trigger, so that auto scaling can trigger it to start
# or remove a instance from auto scaling group
self.createTrigger(self.args.trigger, self.args.measure,
self.args.asg_name)
class BotoScaleInterface(ScaleInterface):
conn = None
saveclcdata = False
def __init__(self, clc_host, access_id, secret_key, token):
#boto.set_stream_logger('foo')
path = '/services/AutoScaling'
reg = RegionInfo(name='eucalyptus', endpoint=clc_host)
port = 8773
if clc_host[len(clc_host) - 13:] == 'amazonaws.com':
clc_host = clc_host.replace('ec2', 'autoscaling', 1)
path = '/'
reg = None
port = 443
self.conn = AutoScaleConnection(access_id,
secret_key,
region=reg,
port=port,
path=path,
is_secure=True,
security_token=token,
debug=0)
self.conn.APIVersion = '2011-01-01'
if not (clc_host[len(clc_host) - 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):
return self.conn.get_all_policies(as_group, policy_names, max_records,
next_token)
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)
def get_all_adjustment_types(self):
return self.conn.get_all_adjustment_types()
# tag related
def delete_tags(self, tags):
return self.conn.delete_tags(tags)
def get_all_tags(self, filters=None, max_records=None, next_token=None):
return self.conn.get_all_tags(filters, max_records, next_token)
def create_or_update_tags(self, tags):
return self.conn.create_or_update_tags(tags)
class MSBManager:
def __init__(self, aws_access_key, aws_secret_key):
self.ec2_conn = EC2Connection(aws_access_key, aws_secret_key)
self.elb_conn = ELBConnection(aws_access_key, aws_secret_key)
self.auto_scale_conn = AutoScaleConnection(aws_access_key, aws_secret_key)
self.cloud_watch_conn = CloudWatchConnection(aws_access_key, aws_secret_key)
self.default_cooldown = 60
def get_security_group(self, name):
sgs = [g for g in self.ec2_conn.get_all_security_groups() if g.name == name]
return sgs[0] if sgs else None
def create_security_group(self, name, description):
sgs = [g for g in self.ec2_conn.get_all_security_groups() if g.name == name]
sg = sgs[0] if sgs else None
if not sgs:
sg = self.ec2_conn.create_security_group(name, description)
try:
sg.authorize(ip_protocol="-1", from_port=None, to_port=None, cidr_ip="0.0.0.0/0", dry_run=False)
except EC2ResponseError:
pass
return sg
def remove_security_group(self, name):
self.ec2_conn.delete_security_group(name=name)
def create_instance(self, image, instance_type, key_name, zone, security_groups, tags):
instance = None
reservations = self.ec2_conn.get_all_instances()
for reservation in reservations:
for i in reservation.instances:
if "Name" in i.tags and i.tags["Name"] == tags["Name"] and i.state == "running":
instance = i
break
if not instance:
reservation = self.ec2_conn.run_instances(
image,
instance_type=instance_type,
key_name=key_name,
placement=zone,
security_groups=security_groups,
monitoring_enabled=True,
)
instance = reservation.instances[0]
while not instance.update() == "running":
time.sleep(5)
time.sleep(10)
self.ec2_conn.create_tags([instance.id], tags)
return instance
def request_spot_instance(self, bid, image, instance_type, key_name, zone, security_groups, tags):
req = self.ec2_conn.request_spot_instances(
price=bid,
instance_type=instance_type,
image_id=image,
placement=zone,
key_name=key_name,
security_groups=security_groups,
)
instance_id = None
while not instance_id:
job_sir_id = req[0].id
requests = self.ec2_conn.get_all_spot_instance_requests()
for sir in requests:
if sir.id == job_sir_id:
instance_id = sir.instance_id
break
print "Job {} not ready".format(job_sir_id)
time.sleep(60)
self.ec2_conn.create_tags([instance_id], tags)
def remove_instance(self, instance_id):
self.remove_instances([instance_id])
def remove_instances(self, instance_ids):
self.ec2_conn.terminate_instances(instance_ids)
def remove_instance_by_tag_name(self, name):
reservations = self.ec2_conn.get_all_instances()
data_centers_intance_ids = []
for reservation in reservations:
for instance in reservation.instances:
if "Name" in instance.tags and instance.tags["Name"] == name and instance.state == "running":
data_centers_intance_ids.append(instance.id)
if data_centers_intance_ids:
self.remove_instances(data_centers_intance_ids)
def create_elb(self, name, zone, project_tag_value, security_group_id, instance_ids=None):
lbs = [l for l in self.elb_conn.get_all_load_balancers() if l.name == name]
lb = lbs[0] if lbs else None
if not lb:
hc = HealthCheck(
timeout=50, interval=60, healthy_threshold=2, unhealthy_threshold=8, target="HTTP:80/heartbeat"
)
ports = [(80, 80, "http")]
zones = [zone]
lb = self.elb_conn.create_load_balancer(name, zones, ports)
self.elb_conn.apply_security_groups_to_lb(name, [security_group_id])
lb.configure_health_check(hc)
if instance_ids:
lb.register_instances(instance_ids)
params = {
"LoadBalancerNames.member.1": lb.name,
"Tags.member.1.Key": "15619project",
"Tags.member.1.Value": project_tag_value,
}
lb.connection.get_status("AddTags", params, verb="POST")
return lb
def remove_elb(self, name):
self.elb_conn.delete_load_balancer(name)
def create_launch_configuration(self, name, image, key_name, security_groups, instance_type):
lcs = [l for l in self.auto_scale_conn.get_all_launch_configurations() if l.name == name]
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)
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)
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
group.shutdown_instances()
instances = True
while instances:
time.sleep(5)
groups = c.get_all_groups()
for group in groups:
if group.name == group_name:
if not group.instances:
instances = False
group.delete()
lc.delete()
found = True
while found:
found = False
time.sleep(5)
tags = c.get_all_tags()
for tag in tags:
if tag.resource_id == group_name and tag.key == 'foo':
found = True
assert not found
print('--- tests completed ---')
def setup(CONF):
global out
lookup_tbl = {
'name': CONF['NAME'],
}
conn = AutoScaleConnection()
out['conn'] = conn
# Launch Configurations
LC = CONF['LC']
LC['name'] = LC['name'] % lookup_tbl
lc = LaunchConfiguration(**LC)
conn.create_launch_configuration(lc)
out['lc'] = lc
# Auto Scaling Group
ASG = CONF['ASG']
ASG['group_name'] = ASG['group_name'] % lookup_tbl
ASG['launch_config'] = lc
groups = conn.get_all_groups(names=[ASG['group_name']])
if (len(groups) > 0):
# update
asg = groups[0]
for k in ASG :
# asg not iterable, try-except to make sure asg[k] exists
try: asg.__getattribute__(k)
except: continue
asg.__setattr__(k, ASG[k])
asg.launch_config_name = LC['name']
asg.update()
out['asg'] = asg
else:
#create
asg = AutoScalingGroup(**ASG)
conn.create_auto_scaling_group(asg)
# ASG Tags
ASG_TAGS = CONF['ASG_TAGS']
for i in ASG_TAGS:
if 'propagate_at_launch' not in i:
i['propagate_at_launch'] = True
i['key'] = i['key'] % lookup_tbl
i['value'] = i['value'] % lookup_tbl
tags = [
Tag(**dict(x.items() + [('resource_id', ASG['group_name'])])) for x in ASG_TAGS
]
conn.create_or_update_tags(tags)
# Triggers (Scaling Policy / Cloudwatch Alarm)
conn_cw = connect_to_region(CONF['REGION'])
TRIGGERS = CONF['TRIGGERS']
for T in TRIGGERS:
T['policy']['name'] = T['policy']['name'] % lookup_tbl
T['policy']['as_name'] = ASG['group_name']
T['alarm']['dimensions'] = {'AutoScalingGroupName': ASG['group_name']}
T['alarm']['alarm_actions'] = None
if 'name' in T['alarm']:
T['alarm']['name'] = T['alarm']['name'] % lookup_tbl
else:
T['alarm']['name'] = T['policy']['name']
# Policies are safely overwritten, so not checked for existence
conn.create_scaling_policy(ScalingPolicy(**T['policy']))
policy = conn.get_all_policies(as_group=ASG['group_name'], policy_names=[T['policy']['name']])[0]
T['alarm']['alarm_actions'] = [policy.policy_arn]
hits = conn_cw.describe_alarms(alarm_names=[T['alarm']['name']])
conn_cw.create_alarm(MetricAlarm(**T['alarm']))
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',
ag = AutoScalingGroup(connection=conn3, name='gp', load_balancers=['elb'], availability_zones=[ZONE],
health_check_type='ELB', health_check_period=60, launch_config=config,
min_size=2, max_size=5, desired_capacity=2,
tags=[Tag(key=TAGK, value=TAGV, propagate_at_launch=True,
resource_id='gp', resource_type='auto-scaling-group')])
conn3.create_auto_scaling_group(ag)
# define the scaling policies
scale_up_policy = ScalingPolicy(name='scale_up', adjustment_type='ChangeInCapacity',
as_name='gp', scaling_adjustment=1, cooldown=60)
scale_down_policy = ScalingPolicy(name='scale_down', adjustment_type='ChangeInCapacity',
as_name='gp', scaling_adjustment=-1, cooldown=60)
# create policies
conn3.create_scaling_policy(scale_up_policy)
conn3.create_scaling_policy(scale_down_policy)
# get ARN for policies
up_policy = conn3.get_all_policies(as_group='gp', policy_names=['scale_up'])[0]
down_policy = conn3.get_all_policies(as_group='gp', policy_names=['scale_down'])[0]
# set up cloudwatch
cloudwatch = boto.ec2.cloudwatch.connect_to_region('us-east-1',
aws_access_key_id=os.environ['AWS_ACCESS_KEY_ID'],
aws_secret_access_key=os.environ['AWS_SECRET_KEY'])
scale_up_alarm = MetricAlarm(name='scale_up_on_cpu', namespace='AWS/EC2', metric='CPUUtilization',
statistic='Average', comparison='>', threshold='80', period='60',
evaluation_periods=2, alarm_actions=[up_policy.policy_arn],
dimensions={"AutoScalingGroupName": 'gp'})
scale_down_alarm = MetricAlarm(name='scale_down_on_cpu', namespace='AWS/EC2', metric='CPUUtilization',
statistic='Average', comparison='<', threshold='30', period='60',
evaluation_periods=2, alarm_actions=[down_policy.policy_arn],
dimensions={"AutoScalingGroupName": 'gp'})
# create alarms
cloudwatch.create_alarm(scale_up_alarm)
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'
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',
adjustment_type = "ChangeInCapacity",
as_name = self.args.asg_name,
scaling_adjustment = -1,
cooldown = 180)
self.autoscale_connection.create_scaling_policy(self.autoScalingUpPolicy)
self.autoscale_connection.create_scaling_policy(self.autoScalingDownPolicy)
print ">>> Created auto scaling policy: " + asp_name
def configureHealthCheck(self, target):
"""
Configures health check for the cluster
"""
self.healthCheck = HealthCheck(target = target,
timeout = 5)
print ">>> Configured health check for: " + target
def createLoadBalancer(self, lb_name, region, lb_port, instance_port, protocol):
"""
Creates a load balancer for cluster
"""
listener = (int(lb_port), int(instance_port), protocol)
tuple_list =[]
tuple_list.append(listener)
lbs = self.elb_connection.get_all_load_balancers()
for lb in lbs:
if lb.name != lb_name:
self.elb_connection.create_load_balancer(lb_name, [region], tuple_list)
self.elb_connection.configure_health_check(name = lb_name,
health_check = self.healthCheck)
print ">>> Created load balancer: " + lb_name
else:
print "Load balancer with name '"+lb_name+"' already exists"
def startInstance(self, image_id, key_name, region, instance_type):
"""
Starts the first instance which will be serving requests irrespective of auto scaling
instances.
"""
reservation = self.ec2_connection.run_instances(image_id=image_id, min_count=1, max_count=1, placement=region, key_name=key_name, instance_type=instance_type)
# for instance in reservation.instances:
# instance.add_tag('node', '0')
# break
self.firstInstance = reservation.instances[0].id.split('\'')[0]
print ">>> Started instance: ", self.firstInstance
def registerInstanceToELB(self, lb_name):
"""
Register the first instance started to the Elastic Load Balancer.
"""
self.elb_connection.register_instances(load_balancer_name = lb_name,
instances = [self.firstInstance])
print ">>> Registered instance '",self.firstInstance,"' to load balancer '"+lb_name+"'"
def setUp(self):
"""
Set's up the auto scaling for the application
"""
# STEP 1: Load the configurations
self.loadConfigs()
# STEP 2: Configure the health check for the instances
self.configureHealthCheck(self.args.lb_target)
# STEP 3: Create a load balancer
self.createLoadBalancer(self.args.lb_name, self.args.region, self.args.lb_port, self.args.instance_port, self.args.protocol)
# STEP 4: Start the first instance
self.startInstance(self.args.ami_id, self.args.key_name, self.args.region, self.args.instance_type)
# STEP 5: Register the instance to the load balancer created in STEP 4
self.registerInstanceToELB(self.args.lb_name)
# STEP 6: Create launch configuration to launch instances by auto scale
self.createLaunchConfiguration(self.args.lc_name, self.args.ami_id, self.args.key_name)
# STEP 7: Create a auto scale group which will manage the instances started by auto scaling
self.createAutoScaleGroup(self.args.asg_name)
# STEP 8: Create a auto scaling policy to say add/remove a node
self.createAutoScalePolicy(self.args.asp_name)
# STEP 9: Create a trigger, so that auto scaling can trigger it to start
# or remove a instance from auto scaling group
self.createTrigger(self.args.trigger, self.args.measure, self.args.asg_name)
as_name=autoscaling_group['name'],
scaling_adjustment=1,
cooldown=180)
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'],
namespace=metric_alarm['nameSpace'],
metric=metric_alarm['metric'],
statistic=metric_alarm['statistic'],
comparison='>',
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'],
