AWS Machine Learning Associate Exam Walkthrough 97 AWS Config

Video Description

AWS Machine Learning Associate Exam Walkthrough 97 AWS Config - October 08 VIEW RECORDING: https://fathom.video/share/_TumXr1a9D-y7m36rkk7g74UkAayF6n1 Meeting Purpose To discuss AWS Config for machine learning compliance and its application in AWS environments. Key Takeaways - AWS Config is crucial for ML compliance, auditing resource configurations against FedRAMP, HIPAA, and internal policies - Config integrates with CloudTrail, EventBridge, SNS, and SSM for comprehensive monitoring, alerting, and automated remediation - Pricing is based on configuration items (~$0.0003/item/region) and rule evaluations (~$0.0001/evaluation/region) - Config is essential for maintaining secure, compliant ML infrastructures in regulated environments Topics AWS Config Overview - Configuration auditing and compliance monitoring service for AWS resources - Tracks current state and changes over time - Evaluates resources against user-defined or managed rules - Key for ML infrastructure compliance (FedRAMP, HIPAA, internal policies) - Ensures proper IAM role scoping, S3 security, EC2 constraints for ML workloads - Audits compliance for reproducibility in ML workflows Core Capabilities - Resource recording: Tracks configurations for EC2, IAM, S3, VPC, and others - Rules evaluation: 75+ AWS managed rules, custom Lambda rules available - Historical views: Compliance history and change timelines for resources - CloudTrail integration: Traces API calls leading to non-compliance - EventBridge/SNS integration: Triggers alerts or automation workflows - Remediation actions: Automates fixes using SSM automation documents Pricing Structure - Configuration items: ~$0.0003 per item recorded per region - Config rule evaluations: ~$0.0001 per evaluation per region - Additional costs: Cross-region aggregation, S3 storage - Optional costs: SNS notifications, EventBridge rules, custom Lambda evaluations Setup Process - Console walkthrough: "Get Started" button initiates setup - Options: Record all/specific resources, continuous/daily recording - Resource exclusion overrides available - AWS Config service role creation or selection - S3 bucket configuration for data delivery - Rule selection from 63+ pages of managed rules Service Integrations - CloudTrail: API-level insight into configuration changes - EventBridge: Detects compliance failures, triggers Lambda/Step Functions - SNS: Pushes compliance notifications (email, Slack) - SSM: Executes remediation playbooks (manual/automatic) - Athena: SQL-like querying of configuration history from S3 - Organizations: Cross-account/region config data aggregation Monitoring in ML Environments - CloudWatch: Monitors performance metrics, logs, alarms (e.g., ML training CPU/GPU usage) - CloudTrail: Audits API calls/events (e.g., IAM role modifications in SageMaker) - Config: Tracks configuration compliance (e.g., S3 encryption, approved instance types) ML-Specific Use Case - SageMaker workload example: - CloudWatch monitors CPU/GPU utilization during training - CloudTrail logs IAM users triggering SageMaker jobs - Config ensures approved instance types (e.g., ML.P instances), encryption on S3/EBS, IAM role MFA - Compliance violation scenario: - Developer opens port 22 on training EC2 - Config detects via restricted SSH rule - SSM triggers remediation to remove the rule - CloudTrail logs the user responsible - SNS notifies security team Next Steps - Implement AWS Config for ML workflows to ensure compliance with regulations - Set up integrations with CloudTrail, EventBridge, and SSM for comprehensive monitoring and automated remediation - Review and select appropriate managed rules for ML-specific compliance needs - Consider custom Lambda rules for organization-specific compliance requirements - Evaluate cost implications and optimize Config usage across regions and accounts