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2.4.2 Release
2.4.2 Release
  • Hydrosphere
  • 🌊About Hydrosphere
    • Overview
    • Concepts
    • Platform Architecture
      • Serving
      • Monitoring
      • Interpretability
    • Key Features
      • Model Registry
      • Inference Pipelines
      • A/B Model Deployments
      • Traffic Shadowing
      • Language-Agnostic
      • Automatic Outlier Detection
      • Data Drift Report
      • Monitoring Dashboard
      • Alerts
      • Prediction Explanation
      • Data Projection
      • Kubeflow Components
      • AWS Sagemaker
  • 🏄Quickstart
    • Installation
      • CLI
      • Python SDK
    • Getting Started
    • Tutorials
      • A/B Analysis for a Recommendation Model
      • Using Deployment Configurations
      • Train & Deploy Census Income Classification Model
      • Monitoring Anomalies with a Custom Metric
      • Monitoring External Models
    • How-To
      • Invoke applications
      • Write definitions
      • Develop runtimes
      • Use private pip repositories
  • 💧Resources
    • Troubleshooting
    • Reference
      • Runtimes
    • Contribution
      • Contributing Pull Requests
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  • Release

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  1. About Hydrosphere
  2. Key Features

Kubeflow Components

PreviousData ProjectionNextAWS Sagemaker

Last updated 4 years ago

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Hydrosphere Serving Components for Kubeflow Pipelines provide integration between Hydrosphere model serving benefits and orchestration capabilities. This allows launching training jobs as well as serving the same models in Kubernetes in a single pipeline.

You can find examples of sample pipelines .

Serving components

Deploy

The Deploy component allows you to upload a model, trained in a Kubeflow pipelines workflow to a Hydrosphere platform.

Release

The Release component allows you to create an Application from a model previously uploaded to Hydrosphere platform. This application will be capable of serving prediction requests by HTTP or gRPC.

For more information, check

For more information, check

🌊
Hydrosphere Deploy Kubeflow Component
Hydrosphere Release Kubeflow Component
Kubeflow
here