DeploymentParams

DeploymentParams defines the deployment configuration for a model, including the artifact type, deployment environment, resource allocation, and container specifications. These parameters control how the model is packaged, deployed, and scaled within the Fiddler infrastructure. This class is used when deploying models to specify the runtime environment, resource requirements, and deployment strategy that best fits your model’s needs and performance requirements.

Examples

Creating basic deployment parameters:

basic_params = DeploymentParams()

Creating deployment with custom resources:

custom_params = DeploymentParams(
    artifact_type=ArtifactType.PYTHON_PACKAGE,
    deployment_type=DeploymentType.BASE_CONTAINER,
    replicas=3,
    cpu=1000,  # millicpus (1 vCPU)
    memory=4096  # MiB (4 GiB)
)

Creating deployment with custom container:

container_params = DeploymentParams(
    artifact_type=ArtifactType.DOCKER_IMAGE,
    deployment_type=DeploymentType.CUSTOM_CONTAINER,
    image_uri="my-registry.com/my-model:v1.0",
    replicas=2,
    cpu=2000,  # millicpus (2 vCPU)
    memory=8192  # MiB (8 GiB)
)

Attributes

Model artifact type; an ArtifactType value (default PYTHON_PACKAGE).

Deployment type; a DeploymentType value (default BASE_CONTAINER).

URI of the container image used to run the model (optional).

Number of replicas to run for the model deployment (optional).

CPU allocation per replica, in millicpus (e.g. 250 = 0.25 vCPU).

Memory allocation per replica, in mebibytes (MiB).

Fiddler Python Client SDK

Fiddler Evals SDK

Fiddler OTel SDK

Fiddler LangGraph SDK

Fiddler LangChain SDK

Fiddler Google ADK SDK

Fiddler Strands Agent SDK

Fiddler OTel JS SDK

Fiddler LangGraph JS SDK

Fiddler LangChain JS SDK

Examples

Attributes

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Examples

Attributes