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get_service_graph

get_service_graph(
    start_time: Timestamp,
    end_time: Timestamp,
    *,
    config_overrides: Optional[XRayClientConfig] = None,
    group_name: Optional[GroupName] = None,
    group_arn: Optional[GroupARN] = None,
    next_token: Optional[String] = None,
) -> GetServiceGraphResult

Retrieves a document that describes services that process incoming requests, and downstream services that they call as a result. Root services process incoming requests and make calls to downstream services. Root services are applications that use the Amazon Web Services X-Ray SDK. Downstream services can be other applications, Amazon Web Services resources, HTTP web APIs, or SQL databases.

Parameters:

  • start_time (Timestamp) –

    The start of the time frame for which to generate a graph.

  • end_time (Timestamp) –

    The end of the timeframe for which to generate a graph.

  • group_name (Optional[GroupName], default: None ) –

    The name of a group based on which you want to generate a graph.

  • group_arn (Optional[GroupARN], default: None ) –

    The Amazon Resource Name (ARN) of a group based on which you want to generate a graph.

  • next_token (Optional[String], default: None ) –

    Pagination token.

Raises:

Source code in docs_src/capo_xray/_services/x_ray.py
def get_service_graph(
    self,
    start_time: "capo_xray.types.timestamp.Timestamp",
    end_time: "capo_xray.types.timestamp.Timestamp",
    *,
    config_overrides: Optional[XRayClientConfig] = None,
    group_name: Optional["capo_xray.types.group_name.GroupName"] = None,
    group_arn: Optional["capo_xray.types.group_arn.GroupARN"] = None,
    next_token: Optional["capo_xray.types.string.String"] = None,
) -> "capo_xray.types.get_service_graph_result.GetServiceGraphResult":
    """<p>Retrieves a document that describes services that process incoming requests, and downstream services that they call as a result. Root services process incoming requests and make calls to downstream services. Root services are applications that use the <a href="https://docs.aws.amazon.com/xray/index.html">Amazon Web Services X-Ray SDK</a>. Downstream services can be other applications, Amazon Web Services resources, HTTP web APIs, or SQL databases.</p>

    Args:
        start_time: <p>The start of the time frame for which to generate a graph.</p>
        end_time: <p>The end of the timeframe for which to generate a graph.</p>
        group_name: <p>The name of a group based on which you want to generate a graph.</p>
        group_arn: <p>The Amazon Resource Name (ARN) of a group based on which you want to generate a graph.</p>
        next_token: <p>Pagination token.</p>

    Raises:
        capo_xray.errors.invalid_request_exception.InvalidRequestException: <p>The request is missing required parameters or has invalid parameters.</p>
        capo_xray.errors.throttled_exception.ThrottledException: <p>The request exceeds the maximum number of requests per second.</p>
        capo_xray.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_xray.types.get_service_graph_request.GetServiceGraphRequest]",
    ) -> OperationResponse[
        "capo_xray.types.get_service_graph_result.GetServiceGraphResult"
    ]:
        import capo_xray._operations.awsx_ray.get_service_graph

        output, http_response = (
            capo_xray._operations.awsx_ray.get_service_graph.get_service_graph(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("GetServiceGraph")
    )
    input_: capo_xray.types.get_service_graph_request.GetServiceGraphRequest = {
        "start_time": start_time,
        "end_time": end_time,
    }
    if group_name is not None:
        input_["group_name"] = group_name
    if group_arn is not None:
        input_["group_arn"] = group_arn
    if next_token is not None:
        input_["next_token"] = next_token

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