Integrations

HPE Machine Learning Development Environment is designed to easily integrate with other popular ML ecosystem tools for tasks that are related to model training, such as ETL, ML pipelines, and model serving. It is recommended to use the Python SDK Client Module Reference to interact with HPE Machine Learning Development Environment.

• Data Transformers: Dive into how HPE Machine Learning Development Environment integrates with data transformation tools such as Pachyderm.

• IDEs: HPE Machine Learning Development Environment shells can be used in the popular IDEs similarly to a common remote SSH host.

• Notifications: Make use of webhooks to integrate HPE Machine Learning Development Environment into your existing workflows.

• Prometheus & Grafana: Discover how to enable a Grafana dashboard to monitor HPE Machine Learning Development Environment hardware and system metrics on a cloud cluster, such as AWS or Kubernetes.

Learn more:

Visit the Works with HPE Machine Learning Development Environment repository to find examples of how to use HPE Machine Learning Development Environment with a variety of ML ecosystem tools, including HPE Machine Learning Data Management, DVC, Delta Lake, Seldon, Spark, Argo, Airflow, and Kubeflow.