Hydrosphere.io
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2.4.3 Release
2.4.3 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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  1. About Hydrosphere

Platform Architecture

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Last updated 4 years ago

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Hydrosphere is composed of several microservices, united to efficiently serve and monitor machine learning models in production. Hydrosphere features are divided between multiple services. You can learn more about each of them in this section.

UI / nginx

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