Cloudera Docs

Limitations and Restrictions

Consider the listed limitations and restrictions when using Cloudera AI Inference service.

  • API Stability: Both the Cloudera AI Control Plane and Cloudera AI Inference service workload APIs and CLIs are under active development and are subject to change in a backward-incompatible way.
  • Cloud Platforms: Cloudera AI Inference service is available only on Cloudera Embedded Container Service platform.
  • One Instance: Only one Cloudera AI Inference service instance per cluster is supported.
  • No upgrade: Cloudera AI Inference service upgrade is not supported on the Technical Preview release.
  • Configuration: The Cloudera control plane must be configured with the LDAP authentication which Knox leverages to authenticate users accessing Cloudera AI Inference service.
  • No Non-Transparent Proxy Support: Cloudera AI Inference service has not been tested with a non-transparent proxy (NTP) setup. However, it works in an Air-gapped setup.
  • Logging: All Kubernetes pod logs, including pods that are running model servers, are scraped by the platform log aggregator service (fluentd). Model endpoint logs can be viewed from the Cloudera AI Inference service GUI. To view logs of other pods, you must first obtain the kubeconfig of the cluster and use the kubectl command. It is not possible to retrieve historical pod logs, and therefore there is no Diagnostic bundle feature at this time.
  • Namespace: Model endpoints can only be deployed in the serving-default namespace.