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Concepts#

This section explains what Hopsworks is and why it is built the way it is. It is reference and explanation, not step-by-step instructions. For the how-to, see the Guides.

Start here#

Read the FTI Pipeline Architecture first. It is the one idea the rest of this section builds on: every AI system decomposes into feature, training, and inference pipelines, connected through a feature store and a model registry. Once you have that model, the other pages are the parts of it.

Reading path#

  • Hopsworks Platform: the components of the platform and how they fit together.
  • FTI Pipeline Architecture: the architecture all AI systems share, and the four classes of AI system.
  • Feature Store: how feature pipelines write feature data (feature groups) and how training and inference pipelines read it (feature views).
  • Projects: the multi-tenant unit that owns your data and ML assets, with governance, sharing, and lineage.
  • MLOps: training, the model registry, serving, and monitoring, the inference side of an AI system.
  • Development: building and running pipelines inside and outside Hopsworks.

How the section is organised#

The Feature Store pages follow the write path then the read path: you write features to feature groups, and you read them through feature views. The MLOps pages follow a model from training through registration, serving, and monitoring. Projects and Development cut across both.