Track AIDP MLOps Models, Workflows, and Notebooks in One Inventory View
Data science assets change faster than infrastructure - new model versions, notebook experiments, and workflow definitions appear weekly. OCI Vision AIDP inventory gives platform and ML ops teams a live catalog of what is deployed, not just what is in Git.
MLOps without a shadow registry
Registered models and model versions in AIDP are production artifacts. They need the same visibility as database systems or load balancers. OCI Vision lists MLOps registered models and versions with platform and workspace context so you can trace which lakehouse hosts which model family.
When auditors ask which ML models were active in a period, you start from inventory rather than reconstructing from experiment logs.
Workflows and notebook sessions
Workflow jobs and job runs appear in dedicated categories with lifecycle state - spot failed runs before customers notice stale dashboards. Notebook sessions show active exploration workloads; workspace objects and connected Git repositories document where code and notebooks live relative to each workspace.
This is especially useful when multiple teams share one AIDP platform and naming conventions drift.
Connecting analytics to the wider estate
AIDP does not run in isolation. Spark clusters consume compute-shaped resources; lakehouse data lands in Object Storage; credentials may reference Autonomous Database wallets. OCI Vision keeps AIDP in the same portal as core CMDB domains so you can switch from a workflow job to the underlying tenancy cost view or security posture without changing tools.
OCI Vision intelligence scores and change tracking apply to the broader inventory, helping teams prioritise remediation across analytics and infrastructure together.
Who benefits
ML platform owners get a single pane for models, jobs, and notebooks. Security teams review Delta Shares and credentials alongside NSGs and public IPs. MSPs deliver customer analytics governance reports from the same product they use for IaaS CMDB.