Canso - ML Platform
  • 👋Introduction
  • 🏛️Canso Architecture
  • 💻Getting Started
    • 🏁Overview
    • 🌌Provison K8s Clusters
    • 🚢Install Canso Helm Charts
    • 🐍🔗 Canso Python Client & Web App
    • 📊Health Metrics for Features in the Data Plane
  • 💡Feature Store
    • Data Sources
      • Data Spans
    • Data Sinks
    • ML Features
      • Raw ML Batch Feature
      • Derived ML Batch Feature
      • Raw ML Streaming Feature
      • Custom User Defined Function
  • 💡AI Agents
    • Introduction
    • Getting Started
    • Quickstart
    • Use Cases
      • Fraud Analyst Agent
      • Agent with Memory
      • Memory command examples
    • Concepts
      • Task Server
      • Broker
      • Checkpoint DB
      • Conversation History
      • Memory
    • How Tos
      • Update the AI Agent
      • Delete the AI Agent
    • Toolkit
      • SQL Runner
      • Kubernetes Job
      • Text-to-SQL
    • API Documentation
      • Agent
      • Memory
  • 💡Risk
    • Overview
    • Workflows and Rules
    • Real Time Transaction Monitoring
    • API Documentation
  • 📝Guides
    • Registry
    • Dry Runs for Batch ML Features
    • Deployment
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  • Steps for Feature Registration
  • Create Feature Objects
  • Generate the access token
  • Register the Features
  • Tool Tips

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  1. Guides

Registry

PreviousAPI DocumentationNextDry Runs for Batch ML Features

Last updated 9 months ago

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In the Canso platform, we begin by registering the data sources and sinks, followed by the registration of features. We support S3 and Kafka as data sources, and S3 and Redis as data sinks. Our platform accommodates raw, derived batch, and streaming features. Once a feature is defined, it must be registered to ensure its metadata, logic, and scheduling details are stored for future reference and reuse.

Steps for Feature Registration

Create Feature Objects

  • Define the raw, derived, and streaming features by creating their respective objects with their configurations.

Generate the access token

  • To register the feature, generate an access token and store it as an environment variable on your data plane machine.

  • Only active tokens can be used. When a token expires, generate a new one and update the environment variable.

  • Take a reference from below to generate the access token.

Register the Features

  • Register each feature object within the platform to persist their details.

  • Here the feature names are primary key. You cannot register the feature again with the same name.

  • Take a reference from to register the features,data sources and sinks.

Tool Tips

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README.md
data-sources.md
data-sinks.md
raw-feature.md
derived-feature.md
streaming-feature.md
deploy-feature.md
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