IAM Automation Pipeline
Production-grade automated IAM provisioning workflow designed for the AWS Student Data Infrastructure. The automation ensures users are created securely, assigned correct permissions, enforced with MFA, and tagged for audit visibility — all with zero manual intervention.
Provisioning Workflow
Security Controls
Automation Benefits
import boto3
from datetime import datetime
def provision_user(username, groups, tags):
"""
Provision IAM user with groups and tags.
Enforces MFA and least-privilege policies.
"""
iam = boto3.client('iam')
# Create user with required tags
iam.create_user(
UserName=username,
Tags=[
{'Key': 'Environment', 'Value': 'Production'},
{'Key': 'MFARequired', 'Value': 'true'},
{'Key': 'CreatedBy', 'Value': 'Automation'},
*tags
]
)
# Add to security groups
for group in groups:
iam.add_user_to_group(
UserName=username,
GroupName=group
)
return {'status': 'success', 'user': username}
Try the Live Demo
$ python iam_provisioner.py
[INIT] Starting IAM provisioning...
[✓] User created: student_analyst
[✓] Added to group: StudentDataReadOnly
[✓] MFA policy attached
[✓] Tags applied: Department=Registrar
[✓] Logged to CloudTrail
Execution time: 0.52 seconds
Watch the automation script execute in real-time in your browser. This safe simulation demonstrates the complete provisioning workflow including group creation, policy attachment, and audit logging.
No AWS credentials required — the demo runs entirely in your browser without making any actual AWS API calls.
▶ Launch Live Demo