Google Cloud Storage (GCS)
Storing artifacts using GCP Cloud Storage.
Google Cloud Storage (GCS)
When would you want to use it?
if you want to share your pipeline run results with other team members or stakeholders inside or outside your organization
if you have other components in your stack that are running remotely (e.g. a Kubeflow or Kubernetes Orchestrator running in a public cloud).
if you outgrow what your local machine can offer in terms of storage space and need to use some form of private or public storage service that is shared with others
if you are running pipelines at scale and need an Artifact Store that can handle the demands of production-grade MLOps
In all these cases, you need an Artifact Store that is backed by a form of public cloud or self-hosted shared object storage service.
How do you deploy it?
The GCS Artifact Store flavor is provided by the GCP ZenML integration, you need to install it on your local machine to be able to register a GCS Artifact Store and add it to your stack:
With the URI to your GCS bucket known, registering a GCS Artifact Store can be done as follows:
Infrastructure Deployment
A GCS Artifact Store can be deployed directly from the ZenML CLI:
Authentication Methods
Certain dashboard functionality, such as visualizing or deleting artifacts, is not available when using an implicitly authenticated artifact store together with a deployed ZenML server because the ZenML server will not have permission to access the filesystem.
The implicit authentication method also needs to be coordinated with other stack components that are highly dependent on the Artifact Store and need to interact with it directly to the function. If these components are not running on your machine, they do not have access to the local Google Cloud CLI configuration and will encounter authentication failures while trying to access the GCS Artifact Store:
How do you use it?
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