Choose an execution rule
A deployment is a way to run a Machine Learning pipeline in a repeatable and automated way.
For each deployment, you can configure an execution rule:
- by endpoint (web API) : the pipeline will be executed by a call to a web API. In addition, this API will allow, if necessary, to retrieve data as input and deliver the result of the pipeline as output. Access to the API can be securely communicated to external users.
- by periodic trigger (CRON) : rules can be configured to trigger the pipeline periodically.
Summary
Function name | Method | Return type | Description |
---|---|---|---|
create_deployment | create_deployment(deployment_name, pipeline_name, execution_rule, deployment_mode, outputs_mapping=[], inputs_mapping=[], description) | Dict | Function that deploys a pipeline by creating a deployment which allows a user to trigger the pipeline execution |
Deploy with execution rule: Endpoint
Definition function
To create an auto-mapping deployment where all inputs and outputs are
based on API calls, you can use the create_deployment
function. To
create a deployment with manual mapping, you can use the
create_deployment
function with the additional parameters
inputs_mapping
to specify the precise mapping between input and
source.
CraftAiSdk.create_deployment(
pipeline_name,
deployment_name,
execution_rule="endpoint",
deployment_mode=DEPLOYMENT_MODES.ELASTIC,
inputs_mapping=None,
outputs_mapping=None,
description=None
)
Parameters
deployment_name
(str) -- Name of endpoint chosen by the user to refer to the endpointpipeline_name
(str) -- Name of pipeline that will be run by the deployment / endpointexecution_rule
(str) - Execution rule of the deployment. Must beendpoint
orperiodic
. For convenience, members of the enumerationDEPLOYMENT_EXECUTION_RULES
could be used too.deployment_mode
(str) – Mode of the deployment. Must be “elastic”.description
(str, optional) -- Text description of usage of pipeline for user onlyoutputs_mapping
(List) - List of all OutputDestination objects with information for each output mapping.inputs_mapping
(List, optional) - List of input mappings, to map pipeline inputs to different sources (such as constant values, endpoint inputs, data store or environment variables). SeeInputSource
for more details. For endpoint rules, if an input of the step in the pipeline is not explicitly mapped, it will be automatically mapped to an endpoint input with the same name.description
(str, optional) – Description of the deployment.
Returns
Information about the deployment just create in a dict Python format. In this data, you will have :
- name - Name of the deployment.
- endpoint_token - Token of the endpoint used to trigger the deployment. Note that this token is only returned if execution_rule is “endpoint”.
Example
Example auto mapping
sdk.create_deployment(
deployment_name="my_deployment",
pipeline_name="my_pipeline",
execution_rule="endpoint",
outputs_mapping=[],
inputs_mapping=[],
)
> {
> 'name': 'name-endpoint',
> 'endpoint_token': 'S_xZOKU ... KHs'
> }
Example manual mapping
sdk.create_deployment(
deployment_name="my_deployment",
pipeline_name="my_pipeline",
execution_rule="endpoint",
inputs_mapping=[
seagull_endpoint_input,
big_whale_input,
salt_constant_input,
],
outputs_mapping=[prediction_endpoint_ouput],
)
> {
> 'name': 'name-endpoint',
> 'endpoint_token': 'S_xZOkCI ... FIg'
> }
Deploy with execution rule: Periodic
Definition function
To create an auto-mapping deployment where all inputs and outputs are
based on periodicity, you can use the create_deployment
function. To
create a deployment with manual mapping, you can use the
create_deployment
function with the additional parameters
inputs_mapping
to specify the precise mapping between input and
source.
CraftAiSdk.create_deployment(
pipeline_name,
deployment_name,
execution_rule="periodic",
deployment_mode=DEPLOYMENT_MODES.ELASTIC,
schedule=None,
inputs_mapping=None,
outputs_mapping=None,
description=None
)
Warning
Input and output mapping must always be precise. Auto mapping isn't available for periodic deployment.
Parameters
-
deployment_name
(str) -- Name of the deployment chosen -
pipeline_name
(str) -- Name of pipeline that will be run by the deployment -
description
(str, optional) -- Text description of usage of pipeline for user only. -
execution_rule
(str) - Execution rule of the deployment. Must beendpoint
orperiodic
. For convenience, members of the enumerationDEPLOYMENT_EXECUTION_RULES
could be used too. -
schedule
(str, optional) - Schedule of the deployment. Only required ifexecution_rule
is "periodic". Must be a valid: cron expression. The deployment will be executed periodically according to this schedule. The schedule must follow this format:<minute> <hour> <day of month> <month> <day of week>
. Note that the schedule is in UTC time zone. "*" means all possible values. Here are some examples:"0 0 * * *"
will execute the deployment every day at midnight."0 0 5 * *"
will execute the deployment every 5th day of the month at midnight.
-
inputs_mapping
(List of instances of [InputSource], optional) - List of input mappings, to map pipeline inputs to different : sources (such as constant values, endpoint inputs, or environment variables). SeeInputSource
for more details. For endpoint rules, if an input of the step in the pipeline is not explicitly mapped, it will be automatically mapped to an endpoint input with the same name. For periodic rules, all inputs of the step in the pipeline must be explicitly mapped. -
outputs_mapping
(List of instances of [OutputDestination], optional) - List of output mappings, to map pipeline outputs to different :
destinations. SeeOutputDestination
for more details. For endpoint execution rules, if an output of the step in the pipeline is not explicitly mapped, it will be automatically mapped to an endpoint input with the same name. For other rules, all outputs of the step in the pipeline must be explicitly mapped. -
description
(str, optional) – Description of the deployment.
Returns
Information about the deployment just create in a dict Python format.
- name - Name of the deployment.
- schedule - Schedule of the deployment. Note that this schedule is only returned if execution_rule is “periodic”.
- human_readable_schedule - Human readable schedule of the deployment. Note that this schedule is only returned if execution_rule is “periodic”.
Example
Set up deployment to be triggered automatically every 14 days.