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