When working with AWS CDK in Python, you may come across the need to create an IAM role for a Glue crawler with a daily trigger. In this article, we will explore three different ways to solve this problem using Python.
Solution 1: Using AWS CDK Constructs
The first solution involves using AWS CDK constructs to define the IAM role and the Glue crawler with a daily trigger. Here’s how you can achieve this:
from aws_cdk import (
aws_iam as iam,
aws_glue as glue,
aws_events as events,
aws_events_targets as targets,
core
)
class MyStack(core.Stack):
def __init__(self, scope: core.Construct, id: str, **kwargs) -> None:
super().__init__(scope, id, **kwargs)
# Create IAM role
role = iam.Role(self, "GlueCrawlerRole",
assumed_by=iam.ServicePrincipal("glue.amazonaws.com"),
managed_policies=[
iam.ManagedPolicy.from_aws_managed_policy_name("service-role/AWSGlueServiceRole")
]
)
# Create Glue crawler
crawler = glue.CfnCrawler(self, "GlueCrawler",
role=role.role_arn,
targets=glue.CfnCrawler.TargetsProperty(
s3_targets=[glue.CfnCrawler.S3TargetProperty(path="s3://your-bucket")]
)
)
# Create CloudWatch event rule for daily trigger
rule = events.Rule(self, "GlueCrawlerTrigger",
schedule=events.Schedule.cron(day="*", hour="0"),
targets=[targets.LambdaFunction(handler="index.handler")]
)
# Add the Glue crawler as a target to the CloudWatch event rule
rule.add_target(targets.LambdaFunction(handler="index.handler"))
This solution uses the AWS CDK constructs to define the IAM role, Glue crawler, and CloudWatch event rule with a daily trigger. It provides a clean and declarative way to create the required resources.
Solution 2: Using Boto3
The second solution involves using the Boto3 library, which is the AWS SDK for Python, to create the IAM role, Glue crawler, and CloudWatch event rule. Here’s an example:
import boto3
# Create IAM role
iam_client = boto3.client('iam')
role_response = iam_client.create_role(
RoleName='GlueCrawlerRole',
AssumeRolePolicyDocument='{"Version": "2012-10-17", "Statement": [{"Effect": "Allow", "Principal": {"Service": "glue.amazonaws.com"}, "Action": "sts:AssumeRole"}]}'
)
# Attach managed policy to the IAM role
iam_client.attach_role_policy(
RoleName='GlueCrawlerRole',
PolicyArn='arn:aws:iam::aws:policy/service-role/AWSGlueServiceRole'
)
# Create Glue crawler
glue_client = boto3.client('glue')
crawler_response = glue_client.create_crawler(
Name='GlueCrawler',
Role=role_response['Role']['Arn'],
Targets={'S3Targets': [{'Path': 's3://your-bucket'}]}
)
# Create CloudWatch event rule for daily trigger
events_client = boto3.client('events')
rule_response = events_client.put_rule(
Name='GlueCrawlerTrigger',
ScheduleExpression='cron(0 * * * ? *)'
)
# Add the Glue crawler as a target to the CloudWatch event rule
events_client.put_targets(
Rule='GlueCrawlerTrigger',
Targets=[{'Id': '1', 'Arn': crawler_response['Crawler']['Arn']}]
)
This solution uses the Boto3 library to interact with the AWS services directly. It provides more control and flexibility but requires more manual configuration compared to the AWS CDK solution.
Solution 3: Using AWS CloudFormation
The third solution involves using AWS CloudFormation to define the IAM role, Glue crawler, and CloudWatch event rule. Here’s an example:
import boto3
cloudformation_client = boto3.client('cloudformation')
template = {
"Resources": {
"GlueCrawlerRole": {
"Type": "AWS::IAM::Role",
"Properties": {
"AssumeRolePolicyDocument": {
"Version": "2012-10-17",
"Statement": [{
"Effect": "Allow",
"Principal": {"Service": "glue.amazonaws.com"},
"Action": "sts:AssumeRole"
}]
},
"ManagedPolicyArns": ["arn:aws:iam::aws:policy/service-role/AWSGlueServiceRole"]
}
},
"GlueCrawler": {
"Type": "AWS::Glue::Crawler",
"Properties": {
"Role": {"Fn::GetAtt": ["GlueCrawlerRole", "Arn"]},
"Targets": {"S3Targets": [{"Path": "s3://your-bucket"}]}
}
},
"GlueCrawlerTrigger": {
"Type": "AWS::Events::Rule",
"Properties": {
"ScheduleExpression": "cron(0 * * * ? *)",
"Targets": [{
"Id": "1",
"Arn": {"Fn::GetAtt": ["GlueCrawler", "Arn"]}
}]
}
}
}
}
response = cloudformation_client.create_stack(
StackName='GlueCrawlerStack',
TemplateBody=json.dumps(template)
)
This solution uses AWS CloudFormation to define the resources in a JSON or YAML template. It provides a scalable and repeatable way to create and manage the infrastructure but requires more upfront configuration.
After evaluating the three solutions, the best option depends on your specific requirements and preferences. If you are already using AWS CDK in your project, Solution 1 provides a seamless integration and a more streamlined development experience. However, if you prefer more control and flexibility, Solution 2 using Boto3 is a good choice. Solution 3 using AWS CloudFormation is ideal if you want to manage the infrastructure as code and leverage the benefits of AWS CloudFormation.
9 Responses
I personally think Solution 2 using Boto3 seems more practical and straightforward. 🤔
Solution 1: Using AWS CDK Constructs seems easier for developers, but what about the cost implications?
Solution 2 seems like a no-brainer, Boto3 is the way to go! Who needs all that CDK complexity?
I personally think Solution 2 using Boto3 is the way to go! It feels more old school and reliable.
Ive been using Boto3 for a while and its been rock solid. Cant complain!
Solution 1 seems convenient, but Solution 3 sounds like a CloudFormation headache. Thoughts?
Solution 1 seems cool, but Solution 3 is old school and Solution 2 sounds like a hassle. #TeamCDK
I couldnt disagree more! Solution 2 is a game-changer, while Solution 3 brings a tried-and-true approach. Solution 1 lacks innovation. #TeamInnovation #ThinkOutsideTheBox
Solution 2 is the way to go! Boto3 is a Python powerhouse, making life easier. Plus, who doesnt love a good Python script? 🐍