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MLSecOps Automation & Monitoring
MLSecOps Automation & Monitoring
Overview
Deploy turnkey monitoring and alerting for your ML models and pipelines. Detect drift, adversarial attacks, and unauthorized changes in real time—integrated seamlessly into your existing
Integration Services
- Model Behavior Monitoring (e.g., AWS SageMaker Model Monitor)
- Data Drift & Schema Anomaly Detectors
- Adversarial Input & Prompt-Injection Alerts
- Custom Dashboards in Datadog, Grafana, or CloudWatch
Integration Services
- Monthly tuning of thresholds and rules
- Alert triage and incident-response assistance
- Quarterly health reports with metrics on incidents, drift events, and system uptime
Key Benefits
- Continuous MLSecOps visibility without manual effort
- Early detection of data poisoning and model theft
- Reduced false positives through adaptive rule refinement
- Compliance reporting with automated log collection
Deliverables
- Integration of monitoring agents and rule configurations
- Custom dashboards and alert workflows
- User guide and admin training
