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create_agent_goal

create_agent_goal(
    profile_arn: AgentProfileArn,
    pillars: Pillars,
    title: SensitiveString,
    *,
    config_overrides: Optional[WellArchitectedClientConfig] = None,
    client_token: Optional[str] = None,
    description: Optional[SensitiveString] = None,
) -> CreateAgentGoalResponse

Creates an optimization goal associated with a profile. Goals define specific targets and objectives for the optimization process.

Parameters:

  • client_token (Optional[str], default: None ) –

    A unique, case-sensitive identifier that you provide to ensure the idempotency of the request.

  • profile_arn (AgentProfileArn) –

    The Amazon Resource Name (ARN) of the profile to associate the goal with.

  • pillars (Pillars) –

    The Well-Architected Tool Framework pillars to associate with this goal.

  • title (SensitiveString) –

    The title of the goal.

  • description (Optional[SensitiveString], default: None ) –

    A description of the goal.

Raises:

Source code in docs_src/capo_wellarchitected/_services/well_architected.py
def create_agent_goal(
    self,
    profile_arn: "capo_wellarchitected.types.agent_profile_arn.AgentProfileArn",
    pillars: "capo_wellarchitected.types.pillars.Pillars",
    title: "capo_wellarchitected.types.sensitive_string.SensitiveString",
    *,
    config_overrides: Optional[WellArchitectedClientConfig] = None,
    client_token: Optional[str] = None,
    description: Optional[
        "capo_wellarchitected.types.sensitive_string.SensitiveString"
    ] = None,
) -> (
    "capo_wellarchitected.types.create_agent_goal_response.CreateAgentGoalResponse"
):
    """<p>Creates an optimization goal associated with a profile. Goals define specific targets and objectives for the optimization process.</p>

    Args:
        client_token: <p>A unique, case-sensitive identifier that you provide to ensure the idempotency of the request.</p>
        profile_arn: <p>The Amazon Resource Name (ARN) of the profile to associate the goal with.</p>
        pillars: <p>The Well-Architected Tool Framework pillars to associate with this goal.</p>
        title: <p>The title of the goal.</p>
        description: <p>A description of the goal.</p>

    Raises:
        capo_wellarchitected.errors.access_denied_exception.AccessDeniedException: <p>User does not have sufficient access to perform this action.</p>
        capo_wellarchitected.errors.conflict_exception.ConflictException: <p>The resource has already been processed, was deleted, or is too large.</p>
        capo_wellarchitected.errors.internal_server_exception.InternalServerException: <p>There is a problem with the Well-Architected Tool API service.</p>
        capo_wellarchitected.errors.resource_not_found_exception.ResourceNotFoundException: <p>The requested resource was not found.</p>
        capo_wellarchitected.errors.service_quota_exceeded_exception.ServiceQuotaExceededException: <p>The user has reached their resource quota.</p>
        capo_wellarchitected.errors.throttling_exception.ThrottlingException: <p>Request was denied due to request throttling.</p>
        capo_wellarchitected.errors.validation_exception.ValidationException: <p>The user input is not valid.</p>
        capo_wellarchitected.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_wellarchitected.types.create_agent_goal_request.CreateAgentGoalRequest]",
    ) -> OperationResponse[
        "capo_wellarchitected.types.create_agent_goal_response.CreateAgentGoalResponse"
    ]:
        import capo_wellarchitected._operations.well_architected_api_service_lambda.create_agent_goal

        output, http_response = (
            capo_wellarchitected._operations.well_architected_api_service_lambda.create_agent_goal.create_agent_goal(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    def _redact_input(
        input_: "capo_wellarchitected.types.create_agent_goal_request.CreateAgentGoalRequest",
    ) -> dict[str, Any]:
        import capo_wellarchitected.types.create_agent_goal_request

        return (
            capo_wellarchitected.types.create_agent_goal_request.redact_sensitive(
                input_
            )
        )

    def _redact_output(
        output: "capo_wellarchitected.types.create_agent_goal_response.CreateAgentGoalResponse",
    ) -> dict[str, Any]:
        import capo_wellarchitected.types.create_agent_goal_response

        return (
            capo_wellarchitected.types.create_agent_goal_response.redact_sensitive(
                output
            )
        )

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging(
            "CreateAgentGoal",
            redact_input=_redact_input,
            redact_output=_redact_output,
        ),
    )
    input_: capo_wellarchitected.types.create_agent_goal_request.CreateAgentGoalRequest = {
        "profile_arn": profile_arn,
        "pillars": pillars,
        "title": title,
    }
    if client_token is None:
        client_token = str(uuid.uuid4())
    input_["client_token"] = client_token
    if description is not None:
        input_["description"] = description

    response = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output