az ml online-endpoint create --file endpoint.yml --workspace-name <workspace> --resource-group <group>Create, update, or operate ml online-endpoint with the Azure CLI.
Search an az command, command group, or Azure task. AzureGlossary shows what the command touches, how risky it is, which concepts explain it, and what safer checks and generated safe-first paths to run first.
Microsoft Learn remains the official Azure CLI reference. This page is the plain-English command map for safety, context, operator review, and safe-first command paths.
az ml online-endpoint commands for AI and Machine Learning; browse safety labels, operation lanes, mapped Azure concepts, and safe-first examples.
az ml online-endpoint create --file endpoint.yml --workspace-name <workspace> --resource-group <group>Create, update, or operate ml online-endpoint with the Azure CLI.
az ml online-endpoint create --workspace-name <workspace-name> --resource-group <resource-group> --file endpoint.ymlCreate, update, or operate ml online-endpoint with the Azure CLI.
az ml online-endpoint delete --workspace-name <workspace-name> --resource-group <resource-group> --name <endpoint-name>Delete or remove ml online-endpoint with the Azure CLI; verify scope and backup/rollback before running.
az ml online-endpoint invoke --name <endpoint-name> --resource-group <resource-group> --workspace-name <workspace-name> --request-file request.jsonCreate, update, or operate ml online-endpoint with the Azure CLI.
az ml online-endpoint invoke --name <endpoint> --request-file request.json --workspace-name <workspace> --resource-group <group>Create, update, or operate ml online-endpoint with the Azure CLI.
az ml online-endpoint invoke --name <endpoint> --request-file sample.json --workspace-name <workspace> --resource-group <group>Create, update, or operate ml online-endpoint with the Azure CLI.
az ml online-endpoint invoke --workspace-name <workspace-name> --resource-group <resource-group> --name <endpoint-name> --request-file sample-request.jsonCreate, update, or operate ml online-endpoint with the Azure CLI.
az ml online-endpoint list --workspace-name <workspace-name> --resource-group <resource-group>List managed online endpoints.
az ml online-endpoint list --workspace-name <workspace-name> --resource-group <resource-group> --output tableInspect or list ml online-endpoint with the Azure CLI before making changes.
az ml online-endpoint list --workspace-name <workspace> --resource-group <group>Inspect or list ml online-endpoint with the Azure CLI before making changes.
az ml online-endpoint list --workspace-name <workspace> --resource-group <resource-group>List managed online endpoints.
az ml online-endpoint show --name <endpoint-name> --resource-group <resource-group> --workspace-name <workspace-name>Inspect or list ml online-endpoint with the Azure CLI before making changes.
Start with a command, group, or messy task. The Command Center gives you a briefing before you copy anything: risk, touched services, safe-first paths, related concepts, and the official Microsoft Learn reference.
Try a real command such as az role assignment list, a group such as az aks, or a task such as private endpoint. Results open as command briefing cards.
Each card explains the command, what it touches, whether it is safe for discovery, and the safe-first path to run before risky changes.
Try a command group such as az group, az storage, az webapp, az aks, az sql, or az role assignment.
Inspect AKS state, credentials, node pools, upgrades, monitoring, and destructive operations from one lane.
Navigate database, analytics, messaging, and AI commands from discovery to controlled mutation.
Inspect identities and assignments before making privileged RBAC, managed identity, or credential changes.
Start with read-only discovery, create only after context checks, then clean up deliberately.
Discover storage accounts, then check network, identity, lifecycle, container, and destructive cleanup commands.
Move from App Service discovery through deployment, slot checks, diagnostics, and guarded rollback.