# Pre-Execution Gates: How to Block Before You Execute (Part 2/3)

1. 1Design a pre-execution gate framework using tools like AWS IAM or Azure Policy
2. 2Implement input validation and data quality checks to prevent malicious data
3. 3Configure model metadata and versioning to track changes and updates
4. 4Test and deploy pre-execution gates using CI/CD pipelines
5. 5Monitor and audit pre-execution gate performance using logging and analytics tools

AI engineers and DevOps teams can benefit from pre-execution gates to ensure compliance and security in AI model deployment

💡 Pre-execution gates can prevent AI model execution if input data is invalid or malicious, ensuring compliance and security

🚫 Block before you execute! Implement pre-execution gates for safe and controlled AI model deployment 💻