CfnAnomalyDetector

class aws_cdk.aws_cloudwatch.CfnAnomalyDetector(scope, id, *, configuration=None, dimensions=None, metric_characteristics=None, metric_math_anomaly_detector=None, metric_name=None, namespace=None, single_metric_anomaly_detector=None, stat=None)

Bases: CfnResource

The AWS::CloudWatch::AnomalyDetector type specifies an anomaly detection band for a certain metric and statistic.

The band represents the expected “normal” range for the metric values. Anomaly detection bands can be used for visualization of a metric’s expected values, and for alarms.

For more information see Using CloudWatch anomaly detection. .

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-cloudwatch-anomalydetector.html
CloudformationResource:: AWS::CloudWatch::AnomalyDetector
ExampleMetadata:: fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk import aws_cloudwatch as cloudwatch

cfn_anomaly_detector = cloudwatch.CfnAnomalyDetector(self, "MyCfnAnomalyDetector",
    configuration=cloudwatch.CfnAnomalyDetector.ConfigurationProperty(
        excluded_time_ranges=[cloudwatch.CfnAnomalyDetector.RangeProperty(
            end_time="endTime",
            start_time="startTime"
        )],
        metric_time_zone="metricTimeZone"
    ),
    dimensions=[cloudwatch.CfnAnomalyDetector.DimensionProperty(
        name="name",
        value="value"
    )],
    metric_characteristics=cloudwatch.CfnAnomalyDetector.MetricCharacteristicsProperty(
        periodic_spikes=False
    ),
    metric_math_anomaly_detector=cloudwatch.CfnAnomalyDetector.MetricMathAnomalyDetectorProperty(
        metric_data_queries=[cloudwatch.CfnAnomalyDetector.MetricDataQueryProperty(
            id="id",

            # the properties below are optional
            account_id="accountId",
            expression="expression",
            label="label",
            metric_stat=cloudwatch.CfnAnomalyDetector.MetricStatProperty(
                metric=cloudwatch.CfnAnomalyDetector.MetricProperty(
                    metric_name="metricName",
                    namespace="namespace",

                    # the properties below are optional
                    dimensions=[cloudwatch.CfnAnomalyDetector.DimensionProperty(
                        name="name",
                        value="value"
                    )]
                ),
                period=123,
                stat="stat",

                # the properties below are optional
                unit="unit"
            ),
            period=123,
            return_data=False
        )]
    ),
    metric_name="metricName",
    namespace="namespace",
    single_metric_anomaly_detector=cloudwatch.CfnAnomalyDetector.SingleMetricAnomalyDetectorProperty(
        account_id="accountId",
        dimensions=[cloudwatch.CfnAnomalyDetector.DimensionProperty(
            name="name",
            value="value"
        )],
        metric_name="metricName",
        namespace="namespace",
        stat="stat"
    ),
    stat="stat"
)

Parameters:

scope (Construct) – Scope in which this resource is defined.
id (str) – Construct identifier for this resource (unique in its scope).
configuration (Union[IResolvable, ConfigurationProperty, Dict[str, Any], None]) – Specifies details about how the anomaly detection model is to be trained, including time ranges to exclude when training and updating the model. The configuration can also include the time zone to use for the metric.
dimensions (Union[IResolvable, Sequence[Union[IResolvable, DimensionProperty, Dict[str, Any]]], None]) – The dimensions of the metric associated with the anomaly detection band.
metric_characteristics (Union[IResolvable, MetricCharacteristicsProperty, Dict[str, Any], None]) – Use this object to include parameters to provide information about your metric to CloudWatch to help it build more accurate anomaly detection models. Currently, it includes the PeriodicSpikes parameter.
metric_math_anomaly_detector (Union[IResolvable, MetricMathAnomalyDetectorProperty, Dict[str, Any], None]) – The CloudWatch metric math expression for this anomaly detector.
metric_name (Optional[str]) – The name of the metric associated with the anomaly detection band.
namespace (Optional[str]) – The namespace of the metric associated with the anomaly detection band.
single_metric_anomaly_detector (Union[IResolvable, SingleMetricAnomalyDetectorProperty, Dict[str, Any], None]) – The CloudWatch metric and statistic for this anomaly detector.
stat (Optional[str]) – The statistic of the metric associated with the anomaly detection band.

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_dependency(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_depends_on(target)

(deprecated) Indicates that this resource depends on another resource and cannot be provisioned unless the other resource has been successfully provisioned.

Parameters:

target (CfnResource) –

Deprecated:

use addDependency

Stability:

deprecated

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 addPropertyOverride or prefix path with “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 value argument to addOverride will 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 intermediate 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). In some cases, a snapshot can be taken of the resource prior to deletion (RemovalPolicy.SNAPSHOT). A list of resources that support this policy can be found in the following link:

Parameters:

policy (Optional[RemovalPolicy]) –
apply_to_update_replace_policy (Optional[bool]) – Apply the same deletion policy to the resource’s “UpdateReplacePolicy”. Default: true
default (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 resource, please consult that specific resource’s documentation.

See:

https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-attribute-deletionpolicy.html#aws-attribute-deletionpolicy-options

Return type:

None

get_att(attribute_name, type_hint=None)

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.
type_hint (Optional[ResolutionTypeHint]) –

Return type:

Reference

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

obtain_dependencies()

Retrieves an array of resources this resource depends on.

This assembles dependencies on resources across stacks (including nested stacks) automatically.

Return type:: List[Union[Stack, CfnResource]]

obtain_resource_dependencies()

Get a shallow copy of dependencies between this resource and other resources in the same stack.

Return type:: List[CfnResource]

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

remove_dependency(target)

Indicates that this resource no longer depends on another resource.

This can be used for resources across stacks (including nested stacks) and the dependency will automatically be removed from the relevant scope.

Parameters:

target (CfnResource) –

Return type:

None

replace_dependency(target, new_target)

Replaces one dependency with another.

Parameters:

target (CfnResource) – The dependency to replace.
new_target (CfnResource) – The new dependency to add.

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::CloudWatch::AnomalyDetector'

attr_id

Id

Type:: cloudformationAttribute

cfn_options: Options for this resource, such as condition, update policy etc.

cfn_resource_type: AWS resource type.

configuration: Specifies details about how the anomaly detection model is to be trained, including time ranges to exclude when training and updating the model.

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.

dimensions: The dimensions of the metric associated with the anomaly detection band.

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_characteristics: Use this object to include parameters to provide information about your metric to CloudWatch to help it build more accurate anomaly detection models.

metric_math_anomaly_detector: The CloudWatch metric math expression for this anomaly detector.

metric_name: The name of the metric associated with the anomaly detection band.

namespace: The namespace of the metric associated with the anomaly detection band.

node: The tree node.

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 }).

single_metric_anomaly_detector: The CloudWatch metric and statistic for this anomaly detector.

stack

The stack in which this element is defined.

CfnElements must be defined within a stack scope (directly or indirectly).

stat: The statistic of the metric associated with the anomaly detection band.

Static Methods

classmethod is_cfn_element(x)

Returns true if a construct is a stack element (i.e. part of the synthesized cloudformation template).

Uses duck-typing instead of instanceof to 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(x)

Check whether the given object is a CfnResource.

Parameters:

x (Any) –

Return type:

bool

classmethod is_construct(x)

Checks if x is a construct.

Use this method instead of instanceof to properly detect Construct instances, even when the construct library is symlinked.

Explanation: in JavaScript, multiple copies of the constructs library on disk are seen as independent, completely different libraries. As a consequence, the class Construct in each copy of the constructs library is seen as a different class, and an instance of one class will not test as instanceof the other class. npm install will not create installations like this, but users may manually symlink construct libraries together or use a monorepo tool: in those cases, multiple copies of the constructs library can be accidentally installed, and instanceof will behave unpredictably. It is safest to avoid using instanceof, and using this type-testing method instead.

Parameters:: x (Any) – Any object.
Return type:: bool
Returns:: true if x is an object created from a class which extends Construct.

ConfigurationProperty

class CfnAnomalyDetector.ConfigurationProperty(*, excluded_time_ranges=None, metric_time_zone=None)

Bases: object

Specifies details about how the anomaly detection model is to be trained, including time ranges to exclude when training and updating the model.

The configuration can also include the time zone to use for the metric.

Parameters:

excluded_time_ranges (Union[IResolvable, Sequence[Union[IResolvable, RangeProperty, Dict[str, Any]]], None]) – Specifies an array of time ranges to exclude from use when the anomaly detection model is trained and updated. Use this to make sure that events that could cause unusual values for the metric, such as deployments, aren’t used when CloudWatch creates or updates the model.
metric_time_zone (Optional[str]) – The time zone to use for the metric. This is useful to enable the model to automatically account for daylight savings time changes if the metric is sensitive to such time changes. To specify a time zone, use the name of the time zone as specified in the standard tz database. For more information, see tz database .

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-configuration.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk import aws_cloudwatch as cloudwatch

configuration_property = cloudwatch.CfnAnomalyDetector.ConfigurationProperty(
    excluded_time_ranges=[cloudwatch.CfnAnomalyDetector.RangeProperty(
        end_time="endTime",
        start_time="startTime"
    )],
    metric_time_zone="metricTimeZone"
)

Attributes

excluded_time_ranges

Specifies an array of time ranges to exclude from use when the anomaly detection model is trained and updated.

Use this to make sure that events that could cause unusual values for the metric, such as deployments, aren’t used when CloudWatch creates or updates the model.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-configuration.html#cfn-cloudwatch-anomalydetector-configuration-excludedtimeranges

metric_time_zone

The time zone to use for the metric.

This is useful to enable the model to automatically account for daylight savings time changes if the metric is sensitive to such time changes.

To specify a time zone, use the name of the time zone as specified in the standard tz database. For more information, see tz database .

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-configuration.html#cfn-cloudwatch-anomalydetector-configuration-metrictimezone

DimensionProperty

class CfnAnomalyDetector.DimensionProperty(*, name, value)

Bases: object

A dimension is a name/value pair that is part of the identity of a metric.

Because dimensions are part of the unique identifier for a metric, whenever you add a unique name/value pair to one of your metrics, you are creating a new variation of that metric. For example, many Amazon EC2 metrics publish InstanceId as a dimension name, and the actual instance ID as the value for that dimension.

You can assign up to 30 dimensions to a metric.

Parameters:

name (str) – The name of the dimension.
value (str) – The value of the dimension. Dimension values must contain only ASCII characters and must include at least one non-whitespace character. ASCII control characters are not supported as part of dimension values.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-dimension.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk import aws_cloudwatch as cloudwatch

dimension_property = cloudwatch.CfnAnomalyDetector.DimensionProperty(
    name="name",
    value="value"
)

Attributes

name

The name of the dimension.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-dimension.html#cfn-cloudwatch-anomalydetector-dimension-name

value

The value of the dimension.

Dimension values must contain only ASCII characters and must include at least one non-whitespace character. ASCII control characters are not supported as part of dimension values.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-dimension.html#cfn-cloudwatch-anomalydetector-dimension-value

MetricCharacteristicsProperty

class CfnAnomalyDetector.MetricCharacteristicsProperty(*, periodic_spikes=None)

Bases: object

This object includes parameters that you can use to provide information to CloudWatch to help it build more accurate anomaly detection models.

Parameters:: periodic_spikes (Union[bool, IResolvable, None]) – Set this parameter to true if values for this metric consistently include spikes that should not be considered to be anomalies. With this set to true, CloudWatch will expect to see spikes that occurred consistently during the model training period, and won’t flag future similar spikes as anomalies.
See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-metriccharacteristics.html
ExampleMetadata:: fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk import aws_cloudwatch as cloudwatch

metric_characteristics_property = cloudwatch.CfnAnomalyDetector.MetricCharacteristicsProperty(
    periodic_spikes=False
)

Attributes

periodic_spikes

Set this parameter to true if values for this metric consistently include spikes that should not be considered to be anomalies.

With this set to true, CloudWatch will expect to see spikes that occurred consistently during the model training period, and won’t flag future similar spikes as anomalies.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-metriccharacteristics.html#cfn-cloudwatch-anomalydetector-metriccharacteristics-periodicspikes

MetricDataQueryProperty

class CfnAnomalyDetector.MetricDataQueryProperty(*, id, account_id=None, expression=None, label=None, metric_stat=None, period=None, return_data=None)

Bases: object

This structure is used in both GetMetricData and PutMetricAlarm .

The supported use of this structure is different for those two operations.

When used in GetMetricData , it indicates the metric data to return, and whether this call is just retrieving a batch set of data for one metric, or is performing a Metrics Insights query or a math expression. A single GetMetricData call can include up to 500 MetricDataQuery structures.

When used in PutMetricAlarm , it enables you to create an alarm based on a metric math expression. Each MetricDataQuery in the array specifies either a metric to retrieve, or a math expression to be performed on retrieved metrics. A single PutMetricAlarm call can include up to 20 MetricDataQuery structures in the array. The 20 structures can include as many as 10 structures that contain a MetricStat parameter to retrieve a metric, and as many as 10 structures that contain the Expression parameter to perform a math expression. Of those Expression structures, one must have true as the value for ReturnData . The result of this expression is the value the alarm watches.

Any expression used in a PutMetricAlarm operation must return a single time series. For more information, see Metric Math Syntax and Functions in the Amazon CloudWatch User Guide .

Some of the parameters of this structure also have different uses whether you are using this structure in a GetMetricData operation or a PutMetricAlarm operation. These differences are explained in the following parameter list.

Parameters:

id (str) – A short name used to tie this object to the results in the response. This name must be unique within a single call to GetMetricData . If you are performing math expressions on this set of data, this name represents that data and can serve as a variable in the mathematical expression. The valid characters are letters, numbers, and underscore. The first character must be a lowercase letter.
account_id (Optional[str]) – The ID of the account where the metrics are located. If you are performing a GetMetricData operation in a monitoring account, use this to specify which account to retrieve this metric from. If you are performing a PutMetricAlarm operation, use this to specify which account contains the metric that the alarm is watching.
expression (Optional[str]) –
This field can contain either a Metrics Insights query, or a metric math expression to be performed on the returned data. For more information about Metrics Insights queries, see Metrics Insights query components and syntax in the Amazon CloudWatch User Guide . A math expression can use the Id of the other metrics or queries to refer to those metrics, and can also use the Id of other expressions to use the result of those expressions. For more information about metric math expressions, see Metric Math Syntax and Functions in the Amazon CloudWatch User Guide . Within each MetricDataQuery object, you must specify either Expression or MetricStat but not both.
label (Optional[str]) – A human-readable label for this metric or expression. This is especially useful if this is an expression, so that you know what the value represents. If the metric or expression is shown in a CloudWatch dashboard widget, the label is shown. If Label is omitted, CloudWatch generates a default. You can put dynamic expressions into a label, so that it is more descriptive. For more information, see Using Dynamic Labels .
metric_stat (Union[IResolvable, MetricStatProperty, Dict[str, Any], None]) – The metric to be returned, along with statistics, period, and units. Use this parameter only if this object is retrieving a metric and not performing a math expression on returned data. Within one MetricDataQuery object, you must specify either Expression or MetricStat but not both.
period (Union[int, float, None]) – The granularity, in seconds, of the returned data points. For metrics with regular resolution, a period can be as short as one minute (60 seconds) and must be a multiple of 60. For high-resolution metrics that are collected at intervals of less than one minute, the period can be 1, 5, 10, 30, 60, or any multiple of 60. High-resolution metrics are those metrics stored by a PutMetricData operation that includes a StorageResolution of 1 second .
return_data (Union[bool, IResolvable, None]) – When used in GetMetricData , this option indicates whether to return the timestamps and raw data values of this metric. If you are performing this call just to do math expressions and do not also need the raw data returned, you can specify false . If you omit this, the default of true is used. When used in PutMetricAlarm , specify true for the one expression result to use as the alarm. For all other metrics and expressions in the same PutMetricAlarm operation, specify ReturnData as False.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-metricdataquery.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk import aws_cloudwatch as cloudwatch

metric_data_query_property = cloudwatch.CfnAnomalyDetector.MetricDataQueryProperty(
    id="id",

    # the properties below are optional
    account_id="accountId",
    expression="expression",
    label="label",
    metric_stat=cloudwatch.CfnAnomalyDetector.MetricStatProperty(
        metric=cloudwatch.CfnAnomalyDetector.MetricProperty(
            metric_name="metricName",
            namespace="namespace",

            # the properties below are optional
            dimensions=[cloudwatch.CfnAnomalyDetector.DimensionProperty(
                name="name",
                value="value"
            )]
        ),
        period=123,
        stat="stat",

        # the properties below are optional
        unit="unit"
    ),
    period=123,
    return_data=False
)

Attributes

account_id

The ID of the account where the metrics are located.

If you are performing a GetMetricData operation in a monitoring account, use this to specify which account to retrieve this metric from.

If you are performing a PutMetricAlarm operation, use this to specify which account contains the metric that the alarm is watching.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-metricdataquery.html#cfn-cloudwatch-anomalydetector-metricdataquery-accountid

expression

This field can contain either a Metrics Insights query, or a metric math expression to be performed on the returned data.

For more information about Metrics Insights queries, see Metrics Insights query components and syntax in the Amazon CloudWatch User Guide .

A math expression can use the Id of the other metrics or queries to refer to those metrics, and can also use the Id of other expressions to use the result of those expressions. For more information about metric math expressions, see Metric Math Syntax and Functions in the Amazon CloudWatch User Guide .

Within each MetricDataQuery object, you must specify either Expression or MetricStat but not both.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-metricdataquery.html#cfn-cloudwatch-anomalydetector-metricdataquery-expression

id

A short name used to tie this object to the results in the response.

This name must be unique within a single call to GetMetricData . If you are performing math expressions on this set of data, this name represents that data and can serve as a variable in the mathematical expression. The valid characters are letters, numbers, and underscore. The first character must be a lowercase letter.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-metricdataquery.html#cfn-cloudwatch-anomalydetector-metricdataquery-id

label

A human-readable label for this metric or expression.

This is especially useful if this is an expression, so that you know what the value represents. If the metric or expression is shown in a CloudWatch dashboard widget, the label is shown. If Label is omitted, CloudWatch generates a default.

You can put dynamic expressions into a label, so that it is more descriptive. For more information, see Using Dynamic Labels .

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-metricdataquery.html#cfn-cloudwatch-anomalydetector-metricdataquery-label

metric_stat

The metric to be returned, along with statistics, period, and units.

Use this parameter only if this object is retrieving a metric and not performing a math expression on returned data.

Within one MetricDataQuery object, you must specify either Expression or MetricStat but not both.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-metricdataquery.html#cfn-cloudwatch-anomalydetector-metricdataquery-metricstat

period

The granularity, in seconds, of the returned data points.

For metrics with regular resolution, a period can be as short as one minute (60 seconds) and must be a multiple of 60. For high-resolution metrics that are collected at intervals of less than one minute, the period can be 1, 5, 10, 30, 60, or any multiple of 60. High-resolution metrics are those metrics stored by a PutMetricData operation that includes a StorageResolution of 1 second .

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-metricdataquery.html#cfn-cloudwatch-anomalydetector-metricdataquery-period

return_data

When used in GetMetricData , this option indicates whether to return the timestamps and raw data values of this metric.

If you are performing this call just to do math expressions and do not also need the raw data returned, you can specify false . If you omit this, the default of true is used.

When used in PutMetricAlarm , specify true for the one expression result to use as the alarm. For all other metrics and expressions in the same PutMetricAlarm operation, specify ReturnData as False.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-metricdataquery.html#cfn-cloudwatch-anomalydetector-metricdataquery-returndata

MetricMathAnomalyDetectorProperty

class CfnAnomalyDetector.MetricMathAnomalyDetectorProperty(*, metric_data_queries=None)

Bases: object

Indicates the CloudWatch math expression that provides the time series the anomaly detector uses as input.

The designated math expression must return a single time series.

Parameters:: metric_data_queries (Union[IResolvable, Sequence[Union[IResolvable, MetricDataQueryProperty, Dict[str, Any]]], None]) – An array of metric data query structures that enables you to create an anomaly detector based on the result of a metric math expression. Each item in MetricDataQueries gets a metric or performs a math expression. One item in MetricDataQueries is the expression that provides the time series that the anomaly detector uses as input. Designate the expression by setting ReturnData to true for this object in the array. For all other expressions and metrics, set ReturnData to false . The designated expression must return a single time series.
See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-metricmathanomalydetector.html
ExampleMetadata:: fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk import aws_cloudwatch as cloudwatch

metric_math_anomaly_detector_property = cloudwatch.CfnAnomalyDetector.MetricMathAnomalyDetectorProperty(
    metric_data_queries=[cloudwatch.CfnAnomalyDetector.MetricDataQueryProperty(
        id="id",

        # the properties below are optional
        account_id="accountId",
        expression="expression",
        label="label",
        metric_stat=cloudwatch.CfnAnomalyDetector.MetricStatProperty(
            metric=cloudwatch.CfnAnomalyDetector.MetricProperty(
                metric_name="metricName",
                namespace="namespace",

                # the properties below are optional
                dimensions=[cloudwatch.CfnAnomalyDetector.DimensionProperty(
                    name="name",
                    value="value"
                )]
            ),
            period=123,
            stat="stat",

            # the properties below are optional
            unit="unit"
        ),
        period=123,
        return_data=False
    )]
)

Attributes

metric_data_queries

An array of metric data query structures that enables you to create an anomaly detector based on the result of a metric math expression.

Each item in MetricDataQueries gets a metric or performs a math expression. One item in MetricDataQueries is the expression that provides the time series that the anomaly detector uses as input. Designate the expression by setting ReturnData to true for this object in the array. For all other expressions and metrics, set ReturnData to false . The designated expression must return a single time series.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-metricmathanomalydetector.html#cfn-cloudwatch-anomalydetector-metricmathanomalydetector-metricdataqueries

MetricProperty

class CfnAnomalyDetector.MetricProperty(*, metric_name, namespace, dimensions=None)

Bases: object

Represents a specific metric.

Parameters:

metric_name (str) – The name of the metric. This is a required field.
namespace (str) – The namespace of the metric.
dimensions (Union[IResolvable, Sequence[Union[IResolvable, DimensionProperty, Dict[str, Any]]], None]) – The dimensions for the metric.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-metric.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk import aws_cloudwatch as cloudwatch

metric_property = cloudwatch.CfnAnomalyDetector.MetricProperty(
    metric_name="metricName",
    namespace="namespace",

    # the properties below are optional
    dimensions=[cloudwatch.CfnAnomalyDetector.DimensionProperty(
        name="name",
        value="value"
    )]
)

Attributes

dimensions

The dimensions for the metric.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-metric.html#cfn-cloudwatch-anomalydetector-metric-dimensions

metric_name

The name of the metric.

This is a required field.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-metric.html#cfn-cloudwatch-anomalydetector-metric-metricname

namespace

The namespace of the metric.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-metric.html#cfn-cloudwatch-anomalydetector-metric-namespace

MetricStatProperty

class CfnAnomalyDetector.MetricStatProperty(*, metric, period, stat, unit=None)

Bases: object

This structure defines the metric to be returned, along with the statistics, period, and units.

Parameters:

metric (Union[IResolvable, MetricProperty, Dict[str, Any]]) – The metric to return, including the metric name, namespace, and dimensions.
period (Union[int, float]) – The granularity, in seconds, of the returned data points. For metrics with regular resolution, a period can be as short as one minute (60 seconds) and must be a multiple of 60. For high-resolution metrics that are collected at intervals of less than one minute, the period can be 1, 5, 10, 30, 60, or any multiple of 60. High-resolution metrics are those metrics stored by a PutMetricData call that includes a StorageResolution of 1 second. If the StartTime parameter specifies a time stamp that is greater than 3 hours ago, you must specify the period as follows or no data points in that time range is returned: - Start time between 3 hours and 15 days ago - Use a multiple of 60 seconds (1 minute). - Start time between 15 and 63 days ago - Use a multiple of 300 seconds (5 minutes). - Start time greater than 63 days ago - Use a multiple of 3600 seconds (1 hour).
stat (str) – The statistic to return. It can include any CloudWatch statistic or extended statistic.
unit (Optional[str]) – When you are using a Put operation, this defines what unit you want to use when storing the metric. In a Get operation, if you omit Unit then all data that was collected with any unit is returned, along with the corresponding units that were specified when the data was reported to CloudWatch. If you specify a unit, the operation returns only data that was collected with that unit specified. If you specify a unit that does not match the data collected, the results of the operation are null. CloudWatch does not perform unit conversions.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-metricstat.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk import aws_cloudwatch as cloudwatch

metric_stat_property = cloudwatch.CfnAnomalyDetector.MetricStatProperty(
    metric=cloudwatch.CfnAnomalyDetector.MetricProperty(
        metric_name="metricName",
        namespace="namespace",

        # the properties below are optional
        dimensions=[cloudwatch.CfnAnomalyDetector.DimensionProperty(
            name="name",
            value="value"
        )]
    ),
    period=123,
    stat="stat",

    # the properties below are optional
    unit="unit"
)

Attributes

metric

The metric to return, including the metric name, namespace, and dimensions.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-metricstat.html#cfn-cloudwatch-anomalydetector-metricstat-metric

period

The granularity, in seconds, of the returned data points.

For metrics with regular resolution, a period can be as short as one minute (60 seconds) and must be a multiple of 60. For high-resolution metrics that are collected at intervals of less than one minute, the period can be 1, 5, 10, 30, 60, or any multiple of 60. High-resolution metrics are those metrics stored by a PutMetricData call that includes a StorageResolution of 1 second.

If the StartTime parameter specifies a time stamp that is greater than 3 hours ago, you must specify the period as follows or no data points in that time range is returned:

Start time between 3 hours and 15 days ago - Use a multiple of 60 seconds (1 minute).
Start time between 15 and 63 days ago - Use a multiple of 300 seconds (5 minutes).
Start time greater than 63 days ago - Use a multiple of 3600 seconds (1 hour).

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-metricstat.html#cfn-cloudwatch-anomalydetector-metricstat-period

stat

The statistic to return.

It can include any CloudWatch statistic or extended statistic.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-metricstat.html#cfn-cloudwatch-anomalydetector-metricstat-stat

unit

When you are using a Put operation, this defines what unit you want to use when storing the metric.

In a Get operation, if you omit Unit then all data that was collected with any unit is returned, along with the corresponding units that were specified when the data was reported to CloudWatch. If you specify a unit, the operation returns only data that was collected with that unit specified. If you specify a unit that does not match the data collected, the results of the operation are null. CloudWatch does not perform unit conversions.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-metricstat.html#cfn-cloudwatch-anomalydetector-metricstat-unit

RangeProperty

class CfnAnomalyDetector.RangeProperty(*, end_time, start_time)

Bases: object

Each Range specifies one range of days or times to exclude from use for training or updating an anomaly detection model.

Parameters:

end_time (str) – The end time of the range to exclude. The format is yyyy-MM-dd'T'HH:mm:ss . For example, 2019-07-01T23:59:59 .
start_time (str) – The start time of the range to exclude. The format is yyyy-MM-dd'T'HH:mm:ss . For example, 2019-07-01T23:59:59 .

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-range.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk import aws_cloudwatch as cloudwatch

range_property = cloudwatch.CfnAnomalyDetector.RangeProperty(
    end_time="endTime",
    start_time="startTime"
)

Attributes

end_time

The end time of the range to exclude.

The format is yyyy-MM-dd'T'HH:mm:ss . For example, 2019-07-01T23:59:59 .

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-range.html#cfn-cloudwatch-anomalydetector-range-endtime

start_time

The start time of the range to exclude.

The format is yyyy-MM-dd'T'HH:mm:ss . For example, 2019-07-01T23:59:59 .

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-range.html#cfn-cloudwatch-anomalydetector-range-starttime

SingleMetricAnomalyDetectorProperty

class CfnAnomalyDetector.SingleMetricAnomalyDetectorProperty(*, account_id=None, dimensions=None, metric_name=None, namespace=None, stat=None)

Bases: object

Designates the CloudWatch metric and statistic that provides the time series the anomaly detector uses as input.

If you have enabled unified cross-account observability, and this account is a monitoring account, the metric can be in the same account or a source account.

Parameters:

account_id (Optional[str]) – If the CloudWatch metric that provides the time series that the anomaly detector uses as input is in another account, specify that account ID here. If you omit this parameter, the current account is used.
dimensions (Union[IResolvable, Sequence[Union[IResolvable, DimensionProperty, Dict[str, Any]]], None]) – The metric dimensions to create the anomaly detection model for.
metric_name (Optional[str]) – The name of the metric to create the anomaly detection model for.
namespace (Optional[str]) – The namespace of the metric to create the anomaly detection model for.
stat (Optional[str]) – The statistic to use for the metric and anomaly detection model.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cloudwatch-anomalydetector-singlemetricanomalydetector.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk import aws_cloudwatch as cloudwatch

single_metric_anomaly_detector_property = cloudwatch.CfnAnomalyDetector.SingleMetricAnomalyDetectorProperty(
    account_id="accountId",
    dimensions=[cloudwatch.CfnAnomalyDetector.DimensionProperty(
        name="name",
        value="value"
    )],
    metric_name="metricName",
    namespace="namespace",
    stat="stat"
)