Troubleshoot common setup issues
Explore common troubleshooting issues.
Could not find executable named 'groff'
When using the AWS CLI, you might encounter the following error: Could not find
executable named 'groff'.
If using a Mac, you can resolve this issue with the following command:
brew install groff
On a Linux machine, use the following commands:
sudo apt-get update -y sudo apt-get install groff -y
Command not found: jq
When creating your AuthZ permission policy JSON file, you might encounter the following
error: jq: command not found.
If using a Mac, you can resolve this issue with the following command:
brew install jq
On a Linux machine, use the following commands:
sudo apt-get update -y sudo apt-get install jq -y
AWS MLflow plugin installation speeds
Installing the AWS MLflow plugin can take several minutes when using a Mac Python environment.
UnsupportedModelRegistryStoreURIException
If you see the UnsupportedModelRegistryStoreURIException, do the
following:
Restart your Jupyter notebook Kernel.
-
Reinstall the AWS MLflow plugin:
!pip install --force-reinstall sagemaker-mlflow
Unsupported MLflow features
Some features available in open source MLflow are not supported in Amazon SageMaker AI managed MLflow.
The following features are currently not supported:
-
MLflow AI Gateway
– The MLflow AI Gateway for managing connections to LLM providers is not available. -
LLM Judges and Scorers
– Built-in judges and custom judges are not supported. Code-based scorers continue to work as expected. -
Prompt Optimization
– Automatic prompt optimization is not available. -
OpenTelemetry Integration
– The OTEL-compatible traces ingestion endpoint is not available.
If you attempt to use these features, you may encounter missing UI elements or unexpected errors. This is expected behavior in the Amazon SageMaker AI managed environment.
