MLSEC-08: Secure governed ML environment - Machine Learning Lens
Implementation planDocumentsBlogs

MLSEC-08: Secure governed ML environment

Protect ML operations environments using managed services with best practices including: detective and preventive guardrails, monitoring, security, and incident management. Explore data in a managed and secure development environment. Centrally manage the configuration of development environments and enable self-service provisioning for the users.

Implementation plan

  • Break out ML workloads by organizational unit access patterns. This will enable delegating required access to each group, such as administrators or data analysts.

  • Use guardrails and service control policies (SCPs) to enforce best practices for each environment type. Limit infrastructure management access to administrators.

  • Verify all sensitive data has access through restricted, isolated environments. Ensure network isolation, dedicated resources, and check service dependencies.

  • Secure ML algorithm implementation using a restricted development environment. Secure model training and hosting containers by following the security processes required for your organization.

Documents

Blogs