my-data.csvthen an example artifact key might be:
gretel_89bdba626464477aaeeef96fc8b2b613_my-data.csv. This key can be used as a data source for training or running models.
api.gretel.cloud. If you are running your own Gretel Workers, they will need this communications path open.
created- A request for a worker has been made. This is the default state for a worker and will stay in this state until a worker is launched. By default, a user may have up to 10 created workers. This essentially serves as your “queue” for creating or running models.
pending- When using Gretel Cloud Workers, this state indicates that our scheduling service has obtained the request and is provisioning a worker for your model or model server.
active- A worker is creating a model, generating, or processing records. Once a worker is in this state it will begin periodically sending control plane and logging information back to Gretel Cloud.
completed- A worker successfully completed its job. If it was a Gretel Cloud Worker, all model or server artifacts have been uploaded and stored in Gretel Cloud. If using a local worker, then all artifacts should have been written out the location specified when starting the job.
error- A worker countered an error. Basic error and troubleshooting information should have been sent to Gretel Cloud.
cancelled- A user has cancelled the worker. When a worker is cancelled, the worker will promptly shut down operation and cease all processing.
lost- A worker will be marked as lost if Gretel Cloud has been unable to communicate with the worker after some period of time.
loststatus, a worker cannot recover from this state. A new model or server will have to be created once the underlying issue is fixed.
createdstate. If you are using Gretel Cloud workers, these jobs are automatically queued to start. While a worker is in this state, you may delete it or cancel it at any time. When this number is exceeded, API calls will return a
4xxerror when attempting to create new models or model servers.
activestate. When using Gretel Cloud workers, if this limit is exceeded, Gretel will wait for work to complete and then automatically start a new job from the queue of
createdjobs. When running local workers, if the worker starts and the limit is exceeded, the job will be put into an
activestate either creating or serving a model. If the job exceeds this limit, the job will be put into an