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app.py
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app.py
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# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: MIT-0
from aws_cdk import (
aws_ec2 as ec2,
aws_s3 as s3,
aws_ecs as ecs,
aws_rds as rds,
aws_iam as iam,
aws_secretsmanager as sm,
aws_ecs_patterns as ecs_patterns,
App, Stack, CfnParameter, CfnOutput, Aws, RemovalPolicy, Duration
)
from constructs import Construct
class DeploymentStack(Stack):
def __init__(self, scope: Construct, id: str, **kwargs) -> None:
super().__init__(scope, id, **kwargs)
# ==============================
# ======= CFN PARAMETERS =======
# ==============================
project_name_param = CfnParameter(scope=self, id='ProjectName', type='String')
db_name = 'mlflowdb'
port = 3306
username = 'master'
bucket_name = f'{project_name_param.value_as_string}-artifacts-{Aws.ACCOUNT_ID}'
container_repo_name = 'mlflow-containers'
cluster_name = 'mlflow'
service_name = 'mlflow'
# ==================================================
# ================= IAM ROLE =======================
# ==================================================
role = iam.Role(scope=self, id='TASKROLE', assumed_by=iam.ServicePrincipal(service='ecs-tasks.amazonaws.com'))
role.add_managed_policy(iam.ManagedPolicy.from_aws_managed_policy_name('AmazonS3FullAccess'))
role.add_managed_policy(iam.ManagedPolicy.from_aws_managed_policy_name('AmazonECS_FullAccess'))
# ==================================================
# ================== SECRET ========================
# ==================================================
db_password_secret = sm.Secret(
scope=self,
id='DBSECRET',
secret_name='dbPassword',
generate_secret_string=sm.SecretStringGenerator(password_length=20, exclude_punctuation=True)
)
# ==================================================
# ==================== VPC =========================
# ==================================================
public_subnet = ec2.SubnetConfiguration(name='Public', subnet_type=ec2.SubnetType.PUBLIC, cidr_mask=28)
private_subnet = ec2.SubnetConfiguration(name='Private', subnet_type=ec2.SubnetType.PRIVATE_WITH_NAT, cidr_mask=28)
isolated_subnet = ec2.SubnetConfiguration(name='DB', subnet_type=ec2.SubnetType.PRIVATE_ISOLATED, cidr_mask=28)
vpc = ec2.Vpc(
scope=self,
id='VPC',
cidr='10.0.0.0/24',
max_azs=2,
nat_gateway_provider=ec2.NatProvider.gateway(),
nat_gateways=1,
subnet_configuration=[public_subnet, private_subnet, isolated_subnet]
)
vpc.add_gateway_endpoint('S3Endpoint', service=ec2.GatewayVpcEndpointAwsService.S3)
# ==================================================
# ================= S3 BUCKET ======================
# ==================================================
artifact_bucket = s3.Bucket(
scope=self,
id='ARTIFACTBUCKET',
bucket_name=bucket_name,
public_read_access=False
)
# # ==================================================
# # ================== DATABASE =====================
# # ==================================================
# Creates a security group for AWS RDS
sg_rds = ec2.SecurityGroup(scope=self, id='SGRDS', vpc=vpc, security_group_name='sg_rds')
# Adds an ingress rule which allows resources in the VPC's CIDR to access the database.
sg_rds.add_ingress_rule(peer=ec2.Peer.ipv4('10.0.0.0/24'), connection=ec2.Port.tcp(port))
database = rds.DatabaseInstance(
scope=self,
id='MYSQL',
database_name=db_name,
port=port,
credentials=rds.Credentials.from_username(username=username, password=db_password_secret.secret_value),
engine=rds.DatabaseInstanceEngine.mysql(version=rds.MysqlEngineVersion.VER_8_0_26),
instance_type=ec2.InstanceType.of(ec2.InstanceClass.BURSTABLE2, ec2.InstanceSize.SMALL),
vpc=vpc,
security_groups=[sg_rds],
vpc_subnets=ec2.SubnetSelection(subnet_type=ec2.SubnetType.PRIVATE_ISOLATED),
# multi_az=True,
removal_policy=RemovalPolicy.DESTROY,
deletion_protection=False
)
# ==================================================
# =============== FARGATE SERVICE ==================
# ==================================================
cluster = ecs.Cluster(scope=self, id='CLUSTER', cluster_name=cluster_name, vpc=vpc)
task_definition = ecs.FargateTaskDefinition(
scope=self,
id='MLflow',
task_role=role,
)
container = task_definition.add_container(
id='Container',
image=ecs.ContainerImage.from_asset(directory='container'),
environment={
'BUCKET': f's3://{artifact_bucket.bucket_name}',
'HOST': database.db_instance_endpoint_address,
'PORT': str(port),
'DATABASE': db_name,
'USERNAME': username
},
secrets={
'PASSWORD': ecs.Secret.from_secrets_manager(db_password_secret)
},
logging=ecs.LogDriver.aws_logs(stream_prefix='mlflow')
)
port_mapping = ecs.PortMapping(container_port=5000, host_port=5000, protocol=ecs.Protocol.TCP)
container.add_port_mappings(port_mapping)
fargate_service = ecs_patterns.NetworkLoadBalancedFargateService(
scope=self,
id='MLFLOW',
service_name=service_name,
cluster=cluster,
task_definition=task_definition
)
# Setup security group
fargate_service.service.connections.security_groups[0].add_ingress_rule(
peer=ec2.Peer.ipv4(vpc.vpc_cidr_block),
connection=ec2.Port.tcp(5000),
description='Allow inbound from VPC for mlflow'
)
# Setup autoscaling policy
scaling = fargate_service.service.auto_scale_task_count(max_capacity=2)
scaling.scale_on_cpu_utilization(
id='AUTOSCALING',
target_utilization_percent=70,
scale_in_cooldown=Duration.seconds(60),
scale_out_cooldown=Duration.seconds(60)
)
# ==================================================
# =================== OUTPUTS ======================
# ==================================================
CfnOutput(scope=self, id='LoadBalancerDNS', value=fargate_service.load_balancer.load_balancer_dns_name)
app = App()
DeploymentStack(app, "DeploymentStack")
app.synth()