Local Artifact Store

Storing artifacts on your local filesystem.

The local Artifact Store is a built-in ZenML Artifact Store flavor that uses a folder on your local filesystem to store artifacts.

When would you want to use it?

The local Artifact Store is a great way to get started with ZenML, as it doesn't require you to provision additional local resources or to interact with managed object-store services like Amazon S3 and Google Cloud Storage. All you need is the local filesystem. You should use the local Artifact Store if you're just evaluating or getting started with ZenML, or if you are still in the experimental phase and don't need to share your pipeline artifacts (dataset, models, etc.) with others.

The local Artifact Store is not meant to be utilized in production. The local filesystem cannot be shared across your team and the artifacts stored in it cannot be accessed from other machines. This also means that artifact visualizations will not be available when using a local Artifact Store through a ZenML instance deployed in the cloud.

Furthermore, the local Artifact Store doesn't cover services like high-availability, scalability, backup and restore and other features that are expected from a production grade MLOps system.

The fact that it stores artifacts on your local filesystem also means that not all stack components can be used in the same stack as a local Artifact Store:

only Orchestrators running on the local machine, such as the local Orchestrator, a local Kubeflow Orchestrator, or a local Kubernetes Orchestrator can be combined with a local Artifact Store

only Model Deployers that are running locally, such as the MLflow Model Deployer, can be used in combination with a local Artifact Store

Step Operators: none of the Step Operators can be used in the same stack as a local Artifact Store, given that their very purpose is to run ZenML steps in remote specialized environments