CfnAnomalyDetector
- class aws_cdk.aws_lookoutmetrics.CfnAnomalyDetector(scope, id, *, anomaly_detector_config, metric_set_list, anomaly_detector_description=None, anomaly_detector_name=None, kms_key_arn=None)
Bases:
CfnResourceA CloudFormation
AWS::LookoutMetrics::AnomalyDetector.The
AWS::LookoutMetrics::AnomalyDetectortype creates an anomaly detector.- CloudformationResource:
AWS::LookoutMetrics::AnomalyDetector
- Link:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_lookoutmetrics as lookoutmetrics cfn_anomaly_detector = lookoutmetrics.CfnAnomalyDetector(self, "MyCfnAnomalyDetector", anomaly_detector_config=lookoutmetrics.CfnAnomalyDetector.AnomalyDetectorConfigProperty( anomaly_detector_frequency="anomalyDetectorFrequency" ), metric_set_list=[lookoutmetrics.CfnAnomalyDetector.MetricSetProperty( metric_list=[lookoutmetrics.CfnAnomalyDetector.MetricProperty( aggregation_function="aggregationFunction", metric_name="metricName", # the properties below are optional namespace="namespace" )], metric_set_name="metricSetName", metric_source=lookoutmetrics.CfnAnomalyDetector.MetricSourceProperty( app_flow_config=lookoutmetrics.CfnAnomalyDetector.AppFlowConfigProperty( flow_name="flowName", role_arn="roleArn" ), cloudwatch_config=lookoutmetrics.CfnAnomalyDetector.CloudwatchConfigProperty( role_arn="roleArn" ), rds_source_config=lookoutmetrics.CfnAnomalyDetector.RDSSourceConfigProperty( database_host="databaseHost", database_name="databaseName", database_port=123, db_instance_identifier="dbInstanceIdentifier", role_arn="roleArn", secret_manager_arn="secretManagerArn", table_name="tableName", vpc_configuration=lookoutmetrics.CfnAnomalyDetector.VpcConfigurationProperty( security_group_id_list=["securityGroupIdList"], subnet_id_list=["subnetIdList"] ) ), redshift_source_config=lookoutmetrics.CfnAnomalyDetector.RedshiftSourceConfigProperty( cluster_identifier="clusterIdentifier", database_host="databaseHost", database_name="databaseName", database_port=123, role_arn="roleArn", secret_manager_arn="secretManagerArn", table_name="tableName", vpc_configuration=lookoutmetrics.CfnAnomalyDetector.VpcConfigurationProperty( security_group_id_list=["securityGroupIdList"], subnet_id_list=["subnetIdList"] ) ), s3_source_config=lookoutmetrics.CfnAnomalyDetector.S3SourceConfigProperty( file_format_descriptor=lookoutmetrics.CfnAnomalyDetector.FileFormatDescriptorProperty( csv_format_descriptor=lookoutmetrics.CfnAnomalyDetector.CsvFormatDescriptorProperty( charset="charset", contains_header=False, delimiter="delimiter", file_compression="fileCompression", header_list=["headerList"], quote_symbol="quoteSymbol" ), json_format_descriptor=lookoutmetrics.CfnAnomalyDetector.JsonFormatDescriptorProperty( charset="charset", file_compression="fileCompression" ) ), role_arn="roleArn", # the properties below are optional historical_data_path_list=["historicalDataPathList"], templated_path_list=["templatedPathList"] ) ), # the properties below are optional dimension_list=["dimensionList"], metric_set_description="metricSetDescription", metric_set_frequency="metricSetFrequency", offset=123, timestamp_column=lookoutmetrics.CfnAnomalyDetector.TimestampColumnProperty( column_format="columnFormat", column_name="columnName" ), timezone="timezone" )], # the properties below are optional anomaly_detector_description="anomalyDetectorDescription", anomaly_detector_name="anomalyDetectorName", kms_key_arn="kmsKeyArn" )
Create a new
AWS::LookoutMetrics::AnomalyDetector.- Parameters:
scope (
Construct) –scope in which this resource is defined.
id (
str) –scoped id of the resource.
anomaly_detector_config (
Union[IResolvable,AnomalyDetectorConfigProperty,Dict[str,Any]]) – Contains information about the configuration of the anomaly detector.metric_set_list (
Union[IResolvable,Sequence[Union[IResolvable,MetricSetProperty,Dict[str,Any]]]]) – The detector’s dataset.anomaly_detector_description (
Optional[str]) – A description of the detector.anomaly_detector_name (
Optional[str]) – The name of the detector.kms_key_arn (
Optional[str]) – The ARN of the KMS key to use to encrypt your data.
Methods
- add_deletion_override(path)
Syntactic sugar for
addOverride(path, undefined).- Parameters:
path (
str) – The path of the value to delete.- Return type:
None
- add_depends_on(target)
Indicates that this resource depends on another resource and cannot be provisioned unless the other resource has been successfully provisioned.
This can be used for resources across stacks (or nested stack) boundaries and the dependency will automatically be transferred to the relevant scope.
- Parameters:
target (
CfnResource) –- Return type:
None
- add_metadata(key, value)
Add a value to the CloudFormation Resource Metadata.
- Parameters:
key (
str) –value (
Any) –
- See:
- Return type:
None
https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/metadata-section-structure.html
Note that this is a different set of metadata from CDK node metadata; this metadata ends up in the stack template under the resource, whereas CDK node metadata ends up in the Cloud Assembly.
- add_override(path, value)
Adds an override to the synthesized CloudFormation resource.
To add a property override, either use
addPropertyOverrideor prefixpathwith “Properties.” (i.e.Properties.TopicName).If the override is nested, separate each nested level using a dot (.) in the path parameter. If there is an array as part of the nesting, specify the index in the path.
To include a literal
.in the property name, prefix with a\. In most programming languages you will need to write this as"\\."because the\itself will need to be escaped.For example:
cfn_resource.add_override("Properties.GlobalSecondaryIndexes.0.Projection.NonKeyAttributes", ["myattribute"]) cfn_resource.add_override("Properties.GlobalSecondaryIndexes.1.ProjectionType", "INCLUDE")
would add the overrides Example:
"Properties": { "GlobalSecondaryIndexes": [ { "Projection": { "NonKeyAttributes": [ "myattribute" ] ... } ... }, { "ProjectionType": "INCLUDE" ... }, ] ... }
The
valueargument toaddOverridewill not be processed or translated in any way. Pass raw JSON values in here with the correct capitalization for CloudFormation. If you pass CDK classes or structs, they will be rendered with lowercased key names, and CloudFormation will reject the template.- Parameters:
path (
str) –The path of the property, you can use dot notation to override values in complex types. Any intermdediate keys will be created as needed.
value (
Any) –The value. Could be primitive or complex.
- Return type:
None
- add_property_deletion_override(property_path)
Adds an override that deletes the value of a property from the resource definition.
- Parameters:
property_path (
str) – The path to the property.- Return type:
None
- add_property_override(property_path, value)
Adds an override to a resource property.
Syntactic sugar for
addOverride("Properties.<...>", value).- Parameters:
property_path (
str) – The path of the property.value (
Any) – The value.
- Return type:
None
- apply_removal_policy(policy=None, *, apply_to_update_replace_policy=None, default=None)
Sets the deletion policy of the resource based on the removal policy specified.
The Removal Policy controls what happens to this resource when it stops being managed by CloudFormation, either because you’ve removed it from the CDK application or because you’ve made a change that requires the resource to be replaced.
The resource can be deleted (
RemovalPolicy.DESTROY), or left in your AWS account for data recovery and cleanup later (RemovalPolicy.RETAIN).- Parameters:
policy (
Optional[RemovalPolicy]) –apply_to_update_replace_policy (
Optional[bool]) – Apply the same deletion policy to the resource’s “UpdateReplacePolicy”. Default: truedefault (
Optional[RemovalPolicy]) – The default policy to apply in case the removal policy is not defined. Default: - Default value is resource specific. To determine the default value for a resoure, please consult that specific resource’s documentation.
- Return type:
None
- get_att(attribute_name)
Returns a token for an runtime attribute of this resource.
Ideally, use generated attribute accessors (e.g.
resource.arn), but this can be used for future compatibility in case there is no generated attribute.- Parameters:
attribute_name (
str) – The name of the attribute.- Return type:
- get_metadata(key)
Retrieve a value value from the CloudFormation Resource Metadata.
- Parameters:
key (
str) –- See:
- Return type:
Any
https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/metadata-section-structure.html
Note that this is a different set of metadata from CDK node metadata; this metadata ends up in the stack template under the resource, whereas CDK node metadata ends up in the Cloud Assembly.
- inspect(inspector)
Examines the CloudFormation resource and discloses attributes.
- Parameters:
inspector (
TreeInspector) –tree inspector to collect and process attributes.
- Return type:
None
- override_logical_id(new_logical_id)
Overrides the auto-generated logical ID with a specific ID.
- Parameters:
new_logical_id (
str) – The new logical ID to use for this stack element.- Return type:
None
- to_string()
Returns a string representation of this construct.
- Return type:
str- Returns:
a string representation of this resource
Attributes
- CFN_RESOURCE_TYPE_NAME = 'AWS::LookoutMetrics::AnomalyDetector'
- anomaly_detector_config
Contains information about the configuration of the anomaly detector.
- anomaly_detector_description
A description of the detector.
- anomaly_detector_name
The name of the detector.
- attr_arn
The Amazon Resource Name (ARN) of the detector.
For example,
arn:aws:lookoutmetrics:us-east-2:123456789012:AnomalyDetector:my-detector- CloudformationAttribute:
Arn
- cfn_options
Options for this resource, such as condition, update policy etc.
- cfn_resource_type
AWS resource type.
- creation_stack
return:
the stack trace of the point where this Resource was created from, sourced from the +metadata+ entry typed +aws:cdk:logicalId+, and with the bottom-most node +internal+ entries filtered.
- kms_key_arn
The ARN of the KMS key to use to encrypt your data.
- logical_id
The logical ID for this CloudFormation stack element.
The logical ID of the element is calculated from the path of the resource node in the construct tree.
To override this value, use
overrideLogicalId(newLogicalId).- Returns:
the logical ID as a stringified token. This value will only get resolved during synthesis.
- metric_set_list
The detector’s dataset.
- node
The construct tree node associated with this construct.
- ref
Return a string that will be resolved to a CloudFormation
{ Ref }for this element.If, by any chance, the intrinsic reference of a resource is not a string, you could coerce it to an IResolvable through
Lazy.any({ produce: resource.ref }).
- stack
The stack in which this element is defined.
CfnElements must be defined within a stack scope (directly or indirectly).
Static Methods
- classmethod is_cfn_element(x)
Returns
trueif a construct is a stack element (i.e. part of the synthesized cloudformation template).Uses duck-typing instead of
instanceofto allow stack elements from different versions of this library to be included in the same stack.- Parameters:
x (
Any) –- Return type:
bool- Returns:
The construct as a stack element or undefined if it is not a stack element.
- classmethod is_cfn_resource(construct)
Check whether the given construct is a CfnResource.
- Parameters:
construct (
IConstruct) –- Return type:
bool
- classmethod is_construct(x)
Return whether the given object is a Construct.
- Parameters:
x (
Any) –- Return type:
bool
AnomalyDetectorConfigProperty
- class CfnAnomalyDetector.AnomalyDetectorConfigProperty(*, anomaly_detector_frequency)
Bases:
objectContains information about a detector’s configuration.
- Parameters:
anomaly_detector_frequency (
str) – The frequency at which the detector analyzes its source data.- Link:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_lookoutmetrics as lookoutmetrics anomaly_detector_config_property = lookoutmetrics.CfnAnomalyDetector.AnomalyDetectorConfigProperty( anomaly_detector_frequency="anomalyDetectorFrequency" )
Attributes
- anomaly_detector_frequency
The frequency at which the detector analyzes its source data.
AppFlowConfigProperty
- class CfnAnomalyDetector.AppFlowConfigProperty(*, flow_name, role_arn)
Bases:
objectDetails about an Amazon AppFlow flow datasource.
- Parameters:
flow_name (
str) – name of the flow.role_arn (
str) – An IAM role that gives Amazon Lookout for Metrics permission to access the flow.
- Link:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_lookoutmetrics as lookoutmetrics app_flow_config_property = lookoutmetrics.CfnAnomalyDetector.AppFlowConfigProperty( flow_name="flowName", role_arn="roleArn" )
Attributes
- flow_name
name of the flow.
- role_arn
An IAM role that gives Amazon Lookout for Metrics permission to access the flow.
CloudwatchConfigProperty
- class CfnAnomalyDetector.CloudwatchConfigProperty(*, role_arn)
Bases:
objectDetails about an Amazon CloudWatch datasource.
- Parameters:
role_arn (
str) – An IAM role that gives Amazon Lookout for Metrics permission to access data in Amazon CloudWatch.- Link:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_lookoutmetrics as lookoutmetrics cloudwatch_config_property = lookoutmetrics.CfnAnomalyDetector.CloudwatchConfigProperty( role_arn="roleArn" )
Attributes
- role_arn
An IAM role that gives Amazon Lookout for Metrics permission to access data in Amazon CloudWatch.
CsvFormatDescriptorProperty
- class CfnAnomalyDetector.CsvFormatDescriptorProperty(*, charset=None, contains_header=None, delimiter=None, file_compression=None, header_list=None, quote_symbol=None)
Bases:
objectContains information about how a source CSV data file should be analyzed.
- Parameters:
charset (
Optional[str]) – The character set in which the source CSV file is written.contains_header (
Union[bool,IResolvable,None]) – Whether or not the source CSV file contains a header.delimiter (
Optional[str]) – The character used to delimit the source CSV file.file_compression (
Optional[str]) – The level of compression of the source CSV file.header_list (
Optional[Sequence[str]]) – A list of the source CSV file’s headers, if any.quote_symbol (
Optional[str]) – The character used as a quote character.
- Link:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_lookoutmetrics as lookoutmetrics csv_format_descriptor_property = lookoutmetrics.CfnAnomalyDetector.CsvFormatDescriptorProperty( charset="charset", contains_header=False, delimiter="delimiter", file_compression="fileCompression", header_list=["headerList"], quote_symbol="quoteSymbol" )
Attributes
- charset
The character set in which the source CSV file is written.
- contains_header
Whether or not the source CSV file contains a header.
- delimiter
The character used to delimit the source CSV file.
- file_compression
The level of compression of the source CSV file.
- header_list
A list of the source CSV file’s headers, if any.
- quote_symbol
The character used as a quote character.
FileFormatDescriptorProperty
- class CfnAnomalyDetector.FileFormatDescriptorProperty(*, csv_format_descriptor=None, json_format_descriptor=None)
Bases:
objectContains information about a source file’s formatting.
- Parameters:
csv_format_descriptor (
Union[IResolvable,CsvFormatDescriptorProperty,Dict[str,Any],None]) – Contains information about how a source CSV data file should be analyzed.json_format_descriptor (
Union[IResolvable,JsonFormatDescriptorProperty,Dict[str,Any],None]) – Contains information about how a source JSON data file should be analyzed.
- Link:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_lookoutmetrics as lookoutmetrics file_format_descriptor_property = lookoutmetrics.CfnAnomalyDetector.FileFormatDescriptorProperty( csv_format_descriptor=lookoutmetrics.CfnAnomalyDetector.CsvFormatDescriptorProperty( charset="charset", contains_header=False, delimiter="delimiter", file_compression="fileCompression", header_list=["headerList"], quote_symbol="quoteSymbol" ), json_format_descriptor=lookoutmetrics.CfnAnomalyDetector.JsonFormatDescriptorProperty( charset="charset", file_compression="fileCompression" ) )
Attributes
- csv_format_descriptor
Contains information about how a source CSV data file should be analyzed.
- json_format_descriptor
Contains information about how a source JSON data file should be analyzed.
JsonFormatDescriptorProperty
- class CfnAnomalyDetector.JsonFormatDescriptorProperty(*, charset=None, file_compression=None)
Bases:
objectContains information about how a source JSON data file should be analyzed.
- Parameters:
charset (
Optional[str]) – The character set in which the source JSON file is written.file_compression (
Optional[str]) – The level of compression of the source CSV file.
- Link:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_lookoutmetrics as lookoutmetrics json_format_descriptor_property = lookoutmetrics.CfnAnomalyDetector.JsonFormatDescriptorProperty( charset="charset", file_compression="fileCompression" )
Attributes
- charset
The character set in which the source JSON file is written.
- file_compression
The level of compression of the source CSV file.
MetricProperty
- class CfnAnomalyDetector.MetricProperty(*, aggregation_function, metric_name, namespace=None)
Bases:
objectA calculation made by contrasting a measure and a dimension from your source data.
- Parameters:
aggregation_function (
str) – The function with which the metric is calculated.metric_name (
str) – The name of the metric.namespace (
Optional[str]) – The namespace for the metric.
- Link:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_lookoutmetrics as lookoutmetrics metric_property = lookoutmetrics.CfnAnomalyDetector.MetricProperty( aggregation_function="aggregationFunction", metric_name="metricName", # the properties below are optional namespace="namespace" )
Attributes
- aggregation_function
The function with which the metric is calculated.
- metric_name
The name of the metric.
- namespace
The namespace for the metric.
MetricSetProperty
- class CfnAnomalyDetector.MetricSetProperty(*, metric_list, metric_set_name, metric_source, dimension_list=None, metric_set_description=None, metric_set_frequency=None, offset=None, timestamp_column=None, timezone=None)
Bases:
objectContains information about a dataset.
- Parameters:
metric_list (
Union[IResolvable,Sequence[Union[IResolvable,MetricProperty,Dict[str,Any]]]]) – A list of metrics that the dataset will contain.metric_set_name (
str) – The name of the dataset.metric_source (
Union[IResolvable,MetricSourceProperty,Dict[str,Any]]) – Contains information about how the source data should be interpreted.dimension_list (
Optional[Sequence[str]]) – A list of the fields you want to treat as dimensions.metric_set_description (
Optional[str]) – A description of the dataset you are creating.metric_set_frequency (
Optional[str]) – The frequency with which the source data will be analyzed for anomalies.offset (
Union[int,float,None]) – After an interval ends, the amount of seconds that the detector waits before importing data. Offset is only supported for S3, Redshift, Athena and datasources.timestamp_column (
Union[IResolvable,TimestampColumnProperty,Dict[str,Any],None]) – Contains information about the column used for tracking time in your source data.timezone (
Optional[str]) – The time zone in which your source data was recorded.
- Link:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_lookoutmetrics as lookoutmetrics metric_set_property = lookoutmetrics.CfnAnomalyDetector.MetricSetProperty( metric_list=[lookoutmetrics.CfnAnomalyDetector.MetricProperty( aggregation_function="aggregationFunction", metric_name="metricName", # the properties below are optional namespace="namespace" )], metric_set_name="metricSetName", metric_source=lookoutmetrics.CfnAnomalyDetector.MetricSourceProperty( app_flow_config=lookoutmetrics.CfnAnomalyDetector.AppFlowConfigProperty( flow_name="flowName", role_arn="roleArn" ), cloudwatch_config=lookoutmetrics.CfnAnomalyDetector.CloudwatchConfigProperty( role_arn="roleArn" ), rds_source_config=lookoutmetrics.CfnAnomalyDetector.RDSSourceConfigProperty( database_host="databaseHost", database_name="databaseName", database_port=123, db_instance_identifier="dbInstanceIdentifier", role_arn="roleArn", secret_manager_arn="secretManagerArn", table_name="tableName", vpc_configuration=lookoutmetrics.CfnAnomalyDetector.VpcConfigurationProperty( security_group_id_list=["securityGroupIdList"], subnet_id_list=["subnetIdList"] ) ), redshift_source_config=lookoutmetrics.CfnAnomalyDetector.RedshiftSourceConfigProperty( cluster_identifier="clusterIdentifier", database_host="databaseHost", database_name="databaseName", database_port=123, role_arn="roleArn", secret_manager_arn="secretManagerArn", table_name="tableName", vpc_configuration=lookoutmetrics.CfnAnomalyDetector.VpcConfigurationProperty( security_group_id_list=["securityGroupIdList"], subnet_id_list=["subnetIdList"] ) ), s3_source_config=lookoutmetrics.CfnAnomalyDetector.S3SourceConfigProperty( file_format_descriptor=lookoutmetrics.CfnAnomalyDetector.FileFormatDescriptorProperty( csv_format_descriptor=lookoutmetrics.CfnAnomalyDetector.CsvFormatDescriptorProperty( charset="charset", contains_header=False, delimiter="delimiter", file_compression="fileCompression", header_list=["headerList"], quote_symbol="quoteSymbol" ), json_format_descriptor=lookoutmetrics.CfnAnomalyDetector.JsonFormatDescriptorProperty( charset="charset", file_compression="fileCompression" ) ), role_arn="roleArn", # the properties below are optional historical_data_path_list=["historicalDataPathList"], templated_path_list=["templatedPathList"] ) ), # the properties below are optional dimension_list=["dimensionList"], metric_set_description="metricSetDescription", metric_set_frequency="metricSetFrequency", offset=123, timestamp_column=lookoutmetrics.CfnAnomalyDetector.TimestampColumnProperty( column_format="columnFormat", column_name="columnName" ), timezone="timezone" )
Attributes
- dimension_list
A list of the fields you want to treat as dimensions.
- metric_list
A list of metrics that the dataset will contain.
- metric_set_description
A description of the dataset you are creating.
- metric_set_frequency
The frequency with which the source data will be analyzed for anomalies.
- metric_set_name
The name of the dataset.
- metric_source
Contains information about how the source data should be interpreted.
- offset
After an interval ends, the amount of seconds that the detector waits before importing data.
Offset is only supported for S3, Redshift, Athena and datasources.
- timestamp_column
Contains information about the column used for tracking time in your source data.
- timezone
The time zone in which your source data was recorded.
MetricSourceProperty
- class CfnAnomalyDetector.MetricSourceProperty(*, app_flow_config=None, cloudwatch_config=None, rds_source_config=None, redshift_source_config=None, s3_source_config=None)
Bases:
objectContains information about how the source data should be interpreted.
- Parameters:
app_flow_config (
Union[IResolvable,AppFlowConfigProperty,Dict[str,Any],None]) – Details about an AppFlow datasource.cloudwatch_config (
Union[IResolvable,CloudwatchConfigProperty,Dict[str,Any],None]) – Details about an Amazon CloudWatch monitoring datasource.rds_source_config (
Union[IResolvable,RDSSourceConfigProperty,Dict[str,Any],None]) – Details about an Amazon Relational Database Service (RDS) datasource.redshift_source_config (
Union[IResolvable,RedshiftSourceConfigProperty,Dict[str,Any],None]) – Details about an Amazon Redshift database datasource.s3_source_config (
Union[IResolvable,S3SourceConfigProperty,Dict[str,Any],None]) – Contains information about the configuration of the S3 bucket that contains source files.
- Link:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_lookoutmetrics as lookoutmetrics metric_source_property = lookoutmetrics.CfnAnomalyDetector.MetricSourceProperty( app_flow_config=lookoutmetrics.CfnAnomalyDetector.AppFlowConfigProperty( flow_name="flowName", role_arn="roleArn" ), cloudwatch_config=lookoutmetrics.CfnAnomalyDetector.CloudwatchConfigProperty( role_arn="roleArn" ), rds_source_config=lookoutmetrics.CfnAnomalyDetector.RDSSourceConfigProperty( database_host="databaseHost", database_name="databaseName", database_port=123, db_instance_identifier="dbInstanceIdentifier", role_arn="roleArn", secret_manager_arn="secretManagerArn", table_name="tableName", vpc_configuration=lookoutmetrics.CfnAnomalyDetector.VpcConfigurationProperty( security_group_id_list=["securityGroupIdList"], subnet_id_list=["subnetIdList"] ) ), redshift_source_config=lookoutmetrics.CfnAnomalyDetector.RedshiftSourceConfigProperty( cluster_identifier="clusterIdentifier", database_host="databaseHost", database_name="databaseName", database_port=123, role_arn="roleArn", secret_manager_arn="secretManagerArn", table_name="tableName", vpc_configuration=lookoutmetrics.CfnAnomalyDetector.VpcConfigurationProperty( security_group_id_list=["securityGroupIdList"], subnet_id_list=["subnetIdList"] ) ), s3_source_config=lookoutmetrics.CfnAnomalyDetector.S3SourceConfigProperty( file_format_descriptor=lookoutmetrics.CfnAnomalyDetector.FileFormatDescriptorProperty( csv_format_descriptor=lookoutmetrics.CfnAnomalyDetector.CsvFormatDescriptorProperty( charset="charset", contains_header=False, delimiter="delimiter", file_compression="fileCompression", header_list=["headerList"], quote_symbol="quoteSymbol" ), json_format_descriptor=lookoutmetrics.CfnAnomalyDetector.JsonFormatDescriptorProperty( charset="charset", file_compression="fileCompression" ) ), role_arn="roleArn", # the properties below are optional historical_data_path_list=["historicalDataPathList"], templated_path_list=["templatedPathList"] ) )
Attributes
- app_flow_config
Details about an AppFlow datasource.
- cloudwatch_config
Details about an Amazon CloudWatch monitoring datasource.
- rds_source_config
Details about an Amazon Relational Database Service (RDS) datasource.
- redshift_source_config
Details about an Amazon Redshift database datasource.
- s3_source_config
Contains information about the configuration of the S3 bucket that contains source files.
RDSSourceConfigProperty
- class CfnAnomalyDetector.RDSSourceConfigProperty(*, database_host, database_name, database_port, db_instance_identifier, role_arn, secret_manager_arn, table_name, vpc_configuration)
Bases:
objectContains information about the Amazon Relational Database Service (RDS) configuration.
- Parameters:
database_host (
str) – The host name of the database.database_name (
str) – The name of the RDS database.database_port (
Union[int,float]) – The port number where the database can be accessed.db_instance_identifier (
str) – A string identifying the database instance.role_arn (
str) – The Amazon Resource Name (ARN) of the role.secret_manager_arn (
str) – The Amazon Resource Name (ARN) of the AWS Secrets Manager role.table_name (
str) – The name of the table in the database.vpc_configuration (
Union[IResolvable,VpcConfigurationProperty,Dict[str,Any]]) – An object containing information about the Amazon Virtual Private Cloud (VPC) configuration.
- Link:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_lookoutmetrics as lookoutmetrics r_dSSource_config_property = lookoutmetrics.CfnAnomalyDetector.RDSSourceConfigProperty( database_host="databaseHost", database_name="databaseName", database_port=123, db_instance_identifier="dbInstanceIdentifier", role_arn="roleArn", secret_manager_arn="secretManagerArn", table_name="tableName", vpc_configuration=lookoutmetrics.CfnAnomalyDetector.VpcConfigurationProperty( security_group_id_list=["securityGroupIdList"], subnet_id_list=["subnetIdList"] ) )
Attributes
- database_host
The host name of the database.
- database_name
The name of the RDS database.
- database_port
The port number where the database can be accessed.
- db_instance_identifier
A string identifying the database instance.
- role_arn
The Amazon Resource Name (ARN) of the role.
- secret_manager_arn
The Amazon Resource Name (ARN) of the AWS Secrets Manager role.
- table_name
The name of the table in the database.
- vpc_configuration
An object containing information about the Amazon Virtual Private Cloud (VPC) configuration.
RedshiftSourceConfigProperty
- class CfnAnomalyDetector.RedshiftSourceConfigProperty(*, cluster_identifier, database_host, database_name, database_port, role_arn, secret_manager_arn, table_name, vpc_configuration)
Bases:
objectProvides information about the Amazon Redshift database configuration.
- Parameters:
cluster_identifier (
str) – A string identifying the Redshift cluster.database_host (
str) – The name of the database host.database_name (
str) – The Redshift database name.database_port (
Union[int,float]) – The port number where the database can be accessed.role_arn (
str) – The Amazon Resource Name (ARN) of the role providing access to the database.secret_manager_arn (
str) – The Amazon Resource Name (ARN) of the AWS Secrets Manager role.table_name (
str) – The table name of the Redshift database.vpc_configuration (
Union[IResolvable,VpcConfigurationProperty,Dict[str,Any]]) – Contains information about the Amazon Virtual Private Cloud (VPC) configuration.
- Link:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_lookoutmetrics as lookoutmetrics redshift_source_config_property = lookoutmetrics.CfnAnomalyDetector.RedshiftSourceConfigProperty( cluster_identifier="clusterIdentifier", database_host="databaseHost", database_name="databaseName", database_port=123, role_arn="roleArn", secret_manager_arn="secretManagerArn", table_name="tableName", vpc_configuration=lookoutmetrics.CfnAnomalyDetector.VpcConfigurationProperty( security_group_id_list=["securityGroupIdList"], subnet_id_list=["subnetIdList"] ) )
Attributes
- cluster_identifier
A string identifying the Redshift cluster.
- database_host
The name of the database host.
- database_name
The Redshift database name.
- database_port
The port number where the database can be accessed.
- role_arn
The Amazon Resource Name (ARN) of the role providing access to the database.
- secret_manager_arn
The Amazon Resource Name (ARN) of the AWS Secrets Manager role.
- table_name
The table name of the Redshift database.
- vpc_configuration
Contains information about the Amazon Virtual Private Cloud (VPC) configuration.
S3SourceConfigProperty
- class CfnAnomalyDetector.S3SourceConfigProperty(*, file_format_descriptor, role_arn, historical_data_path_list=None, templated_path_list=None)
Bases:
objectContains information about the configuration of the S3 bucket that contains source files.
- Parameters:
file_format_descriptor (
Union[IResolvable,FileFormatDescriptorProperty,Dict[str,Any]]) – Contains information about a source file’s formatting.role_arn (
str) – The ARN of an IAM role that has read and write access permissions to the source S3 bucket.historical_data_path_list (
Optional[Sequence[str]]) – A list of paths to the historical data files.templated_path_list (
Optional[Sequence[str]]) – A list of templated paths to the source files.
- Link:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_lookoutmetrics as lookoutmetrics s3_source_config_property = lookoutmetrics.CfnAnomalyDetector.S3SourceConfigProperty( file_format_descriptor=lookoutmetrics.CfnAnomalyDetector.FileFormatDescriptorProperty( csv_format_descriptor=lookoutmetrics.CfnAnomalyDetector.CsvFormatDescriptorProperty( charset="charset", contains_header=False, delimiter="delimiter", file_compression="fileCompression", header_list=["headerList"], quote_symbol="quoteSymbol" ), json_format_descriptor=lookoutmetrics.CfnAnomalyDetector.JsonFormatDescriptorProperty( charset="charset", file_compression="fileCompression" ) ), role_arn="roleArn", # the properties below are optional historical_data_path_list=["historicalDataPathList"], templated_path_list=["templatedPathList"] )
Attributes
- file_format_descriptor
Contains information about a source file’s formatting.
- historical_data_path_list
A list of paths to the historical data files.
- role_arn
The ARN of an IAM role that has read and write access permissions to the source S3 bucket.
- templated_path_list
A list of templated paths to the source files.
TimestampColumnProperty
- class CfnAnomalyDetector.TimestampColumnProperty(*, column_format=None, column_name=None)
Bases:
objectContains information about the column used to track time in a source data file.
- Parameters:
column_format (
Optional[str]) – The format of the timestamp column.column_name (
Optional[str]) – The name of the timestamp column.
- Link:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_lookoutmetrics as lookoutmetrics timestamp_column_property = lookoutmetrics.CfnAnomalyDetector.TimestampColumnProperty( column_format="columnFormat", column_name="columnName" )
Attributes
- column_format
The format of the timestamp column.
- column_name
The name of the timestamp column.
VpcConfigurationProperty
- class CfnAnomalyDetector.VpcConfigurationProperty(*, security_group_id_list, subnet_id_list)
Bases:
objectContains configuration information about the Amazon Virtual Private Cloud (VPC).
- Parameters:
security_group_id_list (
Sequence[str]) – An array of strings containing the list of security groups.subnet_id_list (
Sequence[str]) – An array of strings containing the Amazon VPC subnet IDs (e.g.,subnet-0bb1c79de3EXAMPLE.
- Link:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_lookoutmetrics as lookoutmetrics vpc_configuration_property = lookoutmetrics.CfnAnomalyDetector.VpcConfigurationProperty( security_group_id_list=["securityGroupIdList"], subnet_id_list=["subnetIdList"] )
Attributes
- security_group_id_list
An array of strings containing the list of security groups.
- subnet_id_list
An array of strings containing the Amazon VPC subnet IDs (e.g.,
subnet-0bb1c79de3EXAMPLE.