def deploy_snappy(self, env, num, dryrun, accountid, newrelic, channelname,
devicestring, branch):
from wrapper.ec2 import Ec2
from wrapper.vpc import Vpc
ec2 = Ec2(session=self.session)
vpc = Vpc(session=self.session)
vpc_obj = vpc.get_vpc_from_env(env=env)
num = int(num)
snappyindex = self.get_snappy_index(num=num,
vpcid=vpc_obj.get('VpcId'))
lambda_function_args = {
'env': "infra",
'puppet_role': 'benchmarkslave',
'requester': "benchmark",
'xively_service': "benchmark_slave",
'customer': "",
'shutdown': "stop",
'dry_run': dryrun,
'base_ami': "benchmarkslave",
'instance_type': 'c3.xlarge',
'snappyindex': snappyindex,
'accountid': accountid,
'channelname': channelname,
'newrelic': newrelic,
'iam': 'infra-benchmarkslave',
'ebsoptimized': False,
'monitoring': False,
'devicestring': devicestring,
'branch': branch
}
lambda_function_args['userdata'] = Misc.get_userdata_for_os(
ostype="snappy")
baseami_object = self.get_ami_from_tag(
puppet_role=lambda_function_args['base_ami'])
lambda_function_args['baseamiid'] = baseami_object.get('ImageId')
availability = Misc.get_value_from_array_hash(
dictlist=baseami_object.get('Tags'), key='Availability')
lambda_function_args['ostype'] = Misc.get_value_from_array_hash(
dictlist=baseami_object.get('Tags'), key='Os')
lambda_function_args['keypair'] = Misc.get_value_from_array_hash(
dictlist=vpc_obj.get('Tags'), key='Keypair')
lambda_function_args['instance_name'] = ec2.generate_ec2_unique_name(
env=env, puppet_role="benchmarkslave", num=num)
lambda_function_args[
'securitygroup'] = ec2.get_security_group_ids_for_stack(
vpcid=vpc_obj.get('VpcId'),
puppet_role="benchmarkslave",
ostype=lambda_function_args['ostype'],
xively_service="benchmark_slave")
subnets = vpc.get_all_subnets(filters=[{
'Name': 'tag:Network',
'Values': [availability]
}, {
'Name': 'vpc-id',
'Values': [vpc_obj.get('VpcId')]
}])
lambda_function_args['subnet'] = ec2.get_subnet_with_algorithym(
puppet_role="benchmarkslave",
subnets=subnets,
num=num,
fillup=False,
xively_service="benchmark_slave")
## Get broker IP address
broker = ec2.get_ec2_instances(
filters=[{
'Name': 'vpc-id',
'Values': [vpc_obj.get('VpcId')]
}, {
'Name': 'tag:Xively_service',
'Values': ['benchmark_master']
}, {
'Name': 'tag:Puppet_role',
'Values': ['linuxbase']
}])
lambda_function_args['broker'] = broker[0].get(
'PrivateIpAddress') + ":8883"
instances = Misc.parallel_map_reduce(
lambda x: self.create_instance_lamdba(args=lambda_function_args),
lambda x, y: x + [y], xrange(0, num), [])
return instances
def create_ec2_instance(self,
puppet_role,
env,
requester,
customer,
xively_service,
base_ami,
iam,
instance_type,
dry_run,
shutdown,
monitoring,
fillup,
num,
keypair,
availability=None):
"""
This function creates an ec2 instance
:param puppet_role: the Puppet_role that should be used
:param env: the environment where we should provision to
:param requester: the user/team requesting the machine
:param customer: For future use only
:param xively_service: the Xively_service that should be used
:param base_ami: the base_ami that should be used. Can default to puppet_role
:param iam: The iam role that should be attached, defaults to ec2-base
:param instance_type: the type of instance requested
:param dry_run: No changes should be done
:param shutdown: The shutdown behavior to use
:param monitoring: Should monitoring be enabled
:param fillup: Should fillup algorithym be used or round robin
:param num: the number of instances
:return: a list of instance objects
"""
from wrapper.ec2 import Ec2
from wrapper.vpc import Vpc
from misc import Misc
from core.stackdata import stackdata
stackdata_object = stackdata(session=self.session)
ec2 = Ec2(session=self.session)
vpc = Vpc(session=self.session)
lambda_function_args = {
'env': env,
'puppet_role': puppet_role,
'requester': requester,
'xively_service': xively_service,
'customer': customer,
'shutdown': shutdown,
'dry_run': dry_run
}
stack_data = stackdata_object.get_stack_data(
puppet_role=puppet_role, xively_service=xively_service)
vpc_obj = vpc.get_vpc_from_env(env=env)
## Find the baseami object that needs to be used
if base_ami:
base_ami = base_ami
elif 'ami' in stack_data:
base_ami = stack_data['ami']
else:
logger.info("Falling back to puppet_role as AMI name")
base_ami = puppet_role
logger.info("The baseami that is going to be used: %s" % (base_ami, ))
baseami_object = self.get_ami_from_tag(puppet_role=base_ami)
## Get values for lambda function
lambda_function_args['baseamiid'] = baseami_object.get('ImageId')
if (availability == None):
availability = Misc.get_value_from_array_hash(
dictlist=baseami_object.get('Tags'), key='Availability')
lambda_function_args['ostype'] = Misc.get_value_from_array_hash(
dictlist=baseami_object.get('Tags'), key='Os')
if keypair is not None:
lambda_function_args['keypair'] = keypair
else:
lambda_function_args['keypair'] = Misc.get_value_from_array_hash(
dictlist=vpc_obj.get('Tags'), key='Keypair')
## Find the instance_type that needs to be used
if instance_type:
inst_type_final = instance_type
elif 'instance_type' in stack_data and env in stack_data[
'instance_type']:
inst_type_final = stack_data['instance_type'][env]
else:
inst_type_final = Misc.get_value_from_array_hash(
dictlist=baseami_object.get('Tags'), key='Instancetype')
logger.info("Instance type that will be used: %s" %
(inst_type_final, ))
lambda_function_args['instance_type'] = inst_type_final
## Find the instance profile that needs to be used
if iam:
iam_name = iam
elif 'iam' in stack_data:
iam_name = "%s-%s" % (env, stack_data['iam']['name_postfix'])
else:
iam_name = "ec2-base"
logger.info("Base iam instance profile name: %s" % (iam_name, ))
lambda_function_args['iam'] = iam_name
## Find value for ebsoptimized
if 'ebsoptimized' in stack_data and env in stack_data['ebsoptimized']:
lambda_function_args['ebsoptimized'] = Misc.str2bool(
stack_data['ebsoptimized'][env])
else:
lambda_function_args['ebsoptimized'] = False
## Find value for monitoring enablement
if monitoring:
lambda_function_args['monitoring'] = monitoring
elif 'monitoring' in stack_data and env in stack_data['monitoring']:
lambda_function_args['monitoring'] = Misc.str2bool(
stack_data['monitoring'][env])
else:
lambda_function_args['monitoring'] = False
## Generate instance names for all required instances
lambda_function_args['instance_name'] = ec2.generate_ec2_unique_name(
env=env, puppet_role=puppet_role, num=num)
## Gather all security groups needed for creating an instance stack
lambda_function_args[
'securitygroup'] = ec2.get_security_group_ids_for_stack(
vpcid=vpc_obj.get('VpcId'),
puppet_role=puppet_role,
ostype=lambda_function_args['ostype'],
xively_service=xively_service)
# We need to retrieve the subnets from Vpc object, and pass it to Ec2 object
subnets = vpc.get_all_subnets(filters=[{
'Name': 'tag:Network',
'Values': [availability]
}, {
'Name': 'vpc-id',
'Values': [vpc_obj.get('VpcId')]
}])
lambda_function_args['subnet'] = ec2.get_subnet_with_algorithym(
puppet_role=puppet_role,
subnets=subnets,
num=num,
fillup=fillup,
xively_service=xively_service)
instances = Misc.parallel_map_reduce(
lambda x: self.create_instance_lamdba(args=lambda_function_args),
lambda x, y: x + [y], xrange(0, num), [])
return instances
