May 21
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In this final video of our enterprise AI security series, we cover ClearML's monitoring and audit trail capabilities — the visibility layer that ties everything together. We walk through the platform's operational dashboards, task-level audit surfaces, cost attribution, and external integration points, showing how ClearML delivers live operations and compliance-ready audit out of the box. What we cover: - The Orchestration Dashboard — fleet-wide visibility across resource groups, autoscalers, workers, and queues, with drill-down from whole-fleet view to per-worker GPU utilization. - Task-level audit surface — downloadable timestamped event logs capturing every change, the user who made it, and whether it came from an Agent, the SDK, or the UI. - Model lineage and dataviews — the full chain answering "what data fed this model" and "what task produced this artefact." - Model Endpoints monitoring — unified view of every served model with live request counts, latency, and per-endpoint infrastructure metrics, regardless of whether it was trained in-house or deployed via the GenAI App Engine. - The application pattern — every ClearML application runs as a task underneath, inheriting the same monitoring and audit surface across vLLM, Jupyter Lab, NVIDIA NIMs, and dozens more. - Cost Analytics and the Platform Management Centre — showback and chargeback per team, plus cross-tenant visibility for service providers that preserves tenant isolation. - External integration — REST API access to everything in the GUI, ready to feed your SIEM, Grafana, Slack, and chargeback systems. - The full picture — how all six layers of the series converge into a complete enterprise security posture. Previous videos in this series: - Part 1 — Introduction to the Six Layers of Enterprise Security: https://www.youtube.com/watch?v=RXz8FuzzwI4 - Part 2 — Identity Provider Setup, Group Sync & Access Rules: https://www.youtube.com/watch?v=wnVbOxWbzWM - Part 3 — Configuration Governance with Administrator Vaults: https://www.youtube.com/watch?v=vse_015TaWM - Part 4 — Service Accounts & Automation Security: https://www.youtube.com/watch?v=aPyVLSOp_4I - Part 5 — Compute Governance Layer — resource pools, resource profiles, and resource policies: https://www.youtube.com/watch?v=Wa0ULIyychs - Part 6 — Model Serving Security with the AI Application Gateway: https://www.youtube.com/watch?v=gum-wQ_W27A This is the final video in our series on enterprise AI infrastructure security. Everything we've configured across the previous six layers gets recorded, monitored, and made auditable here. Whether you're an IT director answering compliance questions, a platform engineer wiring ClearML into your SIEM and observability stack, or a security architect mapping platform behavior to your control framework — this walkthrough ties the whole posture together.