This site contains documentation for HPE Ezmeral Runtime Enterprise, including installation, configuration, administration, and reference content, and information about related solutions. Examples of related solutions include HPE Ezmeral ML Ops and HPE Ezmeral Runtime Analytics for Apache Spark.
Kubernetes Bundles are software packages that can contain software to support newer Kubernetes versions, updated add-ons, and software fixes. Kubernetes Bundles enable you to update your deployment without requiring you to upgrade to a newer version of HPE Ezmeral Runtime Enterprise.
This topic summarizes the new features and important changes in HPE Ezmeral Runtime Enterprise 5.6.x compared to HPE Ezmeral Runtime Enterprise 5.5.x.
Describes the screen layout of the HPE Ezmeral Runtime Enterprise graphical user interface (GUI).
The topics in this section provide information about machine learning operations (ML Ops/MLOps) using HPE Ezmeral ML Ops in HPE Ezmeral Runtime Enterprise. (Not available with HPE Ezmeral Runtime Enterprise Essentials.)
This topic describes getting started with the AI and ML workflows in HPE Ezmeral Runtime Enterprise deployments that implement HPE Ezmeral ML Ops.
This topic describes how to install HPE Ezmeral ML Ops on Kubernetes clusters in HPE Ezmeral Runtime Enterprise.
Describes the toolbar and navigation sidebar available to users with Tenant Member access rights to an ML Ops project in HPE Ezmeral Runtime Enterprise.
This topic describes Project Administrator and Project Member Tasks in HPE Ezmeral Runtime Enterprise deployments that implement HPE Ezmeral ML Ops.
The topics in this section describe using data sources. Data sources are available for use in both HPE Ezmeral ML Ops projects and non-HPE Ezmeral ML Ops projects.
The topics in this section describe using source control configurations. Source control is available for use in both HPE Ezmeral ML Ops projects and non-HPE Ezmeral ML Ops projects.
The topics in this section describe using Notebook Servers in HPE Ezmeral ML Ops.
The topics in this section describe using Experiments in HPE Ezmeral ML Ops.
This topic describes how to view experiment results in HPE Ezmeral Runtime Enterprise deployments that implement HPE Ezmeral ML Ops.
This topic describes deleting experiments in HPE Ezmeral Runtime Enterprise deployments that implement HPE Ezmeral ML Ops.
This topic describes deleting experiment runs in HPE Ezmeral Runtime Enterprise deployments that implement HPE Ezmeral ML Ops.
The topics in this section describe using Models in HPE Ezmeral ML Ops.
This topic describes Model Management APIs in HPE Ezmeral ML Ops.
ezmllib
HPE Ezmeral ML Ops on Kubernetes in HPE Ezmeral Runtime Enterprise provides a specialized function library to streamline various Machine Learning (ML) and Spark pipeline operations in Jupyter notebooks. This library, ezmllib, has several modules.
Jupyter notebook magic functions, also known as magics, are special commands that provide notebook functions that might not be easy for you to program using Python. HPE Ezmeral ML Ops on Kubernetes in HPE Ezmeral Runtime Enterprise supports line magics and cell magics.
The topics in this section provide information about Apache Spark on Kubernetes in HPE Ezmeral Runtime Enterprise. (Not available with HPE Ezmeral Runtime Enterprise Essentials.)
Tasks and reference information for Platform Adminstrators (Site Administrators) managing the HPE Ezmeral Runtime Enterprise deployment.
HPE Ezmeral Data Fabric is a platform for data-driven analytics, ML, and AI workloads. The patented file-system architecture was designed and built for performance, reliability, and scalability. HPE Ezmeral Runtime Enterprise supports multiple implementations of HPE Ezmeral Data Fabric.
You administer HPE Ezmeral Data Fabric on Kubernetes and Embedded Data Fabric as part of your HPE Ezmeral Runtime Enterprise environment. The external "bare metal" implementation of HPE Ezmeral Data Fabric is administered through its own tools and has its own documentation. (Not available in HPE Ezmeral Runtime Enterprise Essentials.)
This topic provides information about support for NVIDIA GPU and MIG devices on HPE Ezmeral Runtime Enterprise.
A high-level overview of the items to consider when planning an HPE Ezmeral Runtime Enterprise deployment.
The topics in this section describe deploying HPE Ezmeral Runtime Enterprise. Deployment is divided into phases.
This article describes the process to upgrade to the latest 5.6.x version of HPE Ezmeral Runtime Enterprise.
Upgrade from HPE Ezmeral Runtime Enterprise Essentials to the full-featured HPE Ezmeral Runtime Enterprise or to HPE Ezmeral ML Ops by uploading a license. No additional steps are required.
This topic describes restarting HPE Ezmeral Runtime Enterprise services in non-Kubernetes hosts.
