Key features

Configurable automation

  • Well documented API and CLI
  • Versioned artifacts for each pipeline
  • Trigger-based pipeline runs to automate machine learning workflows

Managed orchestration

  • Transition of pipelines from training to serving to avoid skew
  • Configure type of compute instances per pipeline runs
  • Blue/Green deployment of models

Collaborate on experiments and models

  • Centralized pipeline configurations and runs
  • Compare experiments across your organization
  • Consolidated ownership of code, configuration and models
  • Full transparency over model development lifecycle

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