Enumerations

Aligner

static

number

The Aligner describes how to bring the data points in a single time series into temporal alignment.

Value

ALIGN_NONE

No alignment. Raw data is returned. Not valid if cross-time series reduction is requested. The value type of the result is the same as the value type of the input.

ALIGN_DELTA

Align and convert to delta metric type. This alignment is valid for cumulative metrics and delta metrics. Aligning an existing delta metric to a delta metric requires that the alignment period be increased. The value type of the result is the same as the value type of the input.

ALIGN_RATE

Align and convert to a rate. This alignment is valid for cumulative metrics and delta metrics with numeric values. The output is a gauge metric with value type DOUBLE.

ALIGN_INTERPOLATE

Align by interpolating between adjacent points around the period boundary. This alignment is valid for gauge metrics with numeric values. The value type of the result is the same as the value type of the input.

ALIGN_NEXT_OLDER

Align by shifting the oldest data point before the period boundary to the boundary. This alignment is valid for gauge metrics. The value type of the result is the same as the value type of the input.

ALIGN_MIN

Align time series via aggregation. The resulting data point in the alignment period is the minimum of all data points in the period. This alignment is valid for gauge and delta metrics with numeric values. The value type of the result is the same as the value type of the input.

ALIGN_MAX

Align time series via aggregation. The resulting data point in the alignment period is the maximum of all data points in the period. This alignment is valid for gauge and delta metrics with numeric values. The value type of the result is the same as the value type of the input.

ALIGN_MEAN

Align time series via aggregation. The resulting data point in the alignment period is the average or arithmetic mean of all data points in the period. This alignment is valid for gauge and delta metrics with numeric values. The value type of the output is DOUBLE.

ALIGN_COUNT

Align time series via aggregation. The resulting data point in the alignment period is the count of all data points in the period. This alignment is valid for gauge and delta metrics with numeric or Boolean values. The value type of the output is INT64.

ALIGN_SUM

Align time series via aggregation. The resulting data point in the alignment period is the sum of all data points in the period. This alignment is valid for gauge and delta metrics with numeric and distribution values. The value type of the output is the same as the value type of the input.

ALIGN_STDDEV

Align time series via aggregation. The resulting data point in the alignment period is the standard deviation of all data points in the period. This alignment is valid for gauge and delta metrics with numeric values. The value type of the output is DOUBLE.

ALIGN_COUNT_TRUE

Align time series via aggregation. The resulting data point in the alignment period is the count of True-valued data points in the period. This alignment is valid for gauge metrics with Boolean values. The value type of the output is INT64.

ALIGN_FRACTION_TRUE

Align time series via aggregation. The resulting data point in the alignment period is the fraction of True-valued data points in the period. This alignment is valid for gauge metrics with Boolean values. The output value is in the range [0, 1] and has value type DOUBLE.

ALIGN_PERCENTILE_99

Align time series via aggregation. The resulting data point in the alignment period is the 99th percentile of all data points in the period. This alignment is valid for gauge and delta metrics with distribution values. The output is a gauge metric with value type DOUBLE.

ALIGN_PERCENTILE_95

Align time series via aggregation. The resulting data point in the alignment period is the 95th percentile of all data points in the period. This alignment is valid for gauge and delta metrics with distribution values. The output is a gauge metric with value type DOUBLE.

ALIGN_PERCENTILE_50

Align time series via aggregation. The resulting data point in the alignment period is the 50th percentile of all data points in the period. This alignment is valid for gauge and delta metrics with distribution values. The output is a gauge metric with value type DOUBLE.

ALIGN_PERCENTILE_05

Align time series via aggregation. The resulting data point in the alignment period is the 5th percentile of all data points in the period. This alignment is valid for gauge and delta metrics with distribution values. The output is a gauge metric with value type DOUBLE.

GroupResourceType

static

number

The supported resource types that can be used as values of group_resource.resource_type. gae_app and uptime_url are not allowed because group checks on App Engine modules and URLs are not allowed.

Value

RESOURCE_TYPE_UNSPECIFIED

Default value (not valid).

INSTANCE

A group of instances (could be either GCE or AWS_EC2).

AWS_ELB_LOAD_BALANCER

A group of AWS load balancers.

Reducer

static

number

A Reducer describes how to aggregate data points from multiple time series into a single time series.

Value

REDUCE_NONE

No cross-time series reduction. The output of the aligner is returned.

REDUCE_MEAN

Reduce by computing the mean across time series for each alignment period. This reducer is valid for delta and gauge metrics with numeric or distribution values. The value type of the output is DOUBLE.

REDUCE_MIN

Reduce by computing the minimum across time series for each alignment period. This reducer is valid for delta and gauge metrics with numeric values. The value type of the output is the same as the value type of the input.

REDUCE_MAX

Reduce by computing the maximum across time series for each alignment period. This reducer is valid for delta and gauge metrics with numeric values. The value type of the output is the same as the value type of the input.

REDUCE_SUM

Reduce by computing the sum across time series for each alignment period. This reducer is valid for delta and gauge metrics with numeric and distribution values. The value type of the output is the same as the value type of the input.

REDUCE_STDDEV

Reduce by computing the standard deviation across time series for each alignment period. This reducer is valid for delta and gauge metrics with numeric or distribution values. The value type of the output is DOUBLE.

REDUCE_COUNT

Reduce by computing the count of data points across time series for each alignment period. This reducer is valid for delta and gauge metrics of numeric, Boolean, distribution, and string value type. The value type of the output is INT64.

REDUCE_COUNT_TRUE

Reduce by computing the count of True-valued data points across time series for each alignment period. This reducer is valid for delta and gauge metrics of Boolean value type. The value type of the output is INT64.

REDUCE_FRACTION_TRUE

Reduce by computing the fraction of True-valued data points across time series for each alignment period. This reducer is valid for delta and gauge metrics of Boolean value type. The output value is in the range [0, 1] and has value type DOUBLE.

REDUCE_PERCENTILE_99

Reduce by computing 99th percentile of data points across time series for each alignment period. This reducer is valid for gauge and delta metrics of numeric and distribution type. The value of the output is DOUBLE

REDUCE_PERCENTILE_95

Reduce by computing 95th percentile of data points across time series for each alignment period. This reducer is valid for gauge and delta metrics of numeric and distribution type. The value of the output is DOUBLE

REDUCE_PERCENTILE_50

Reduce by computing 50th percentile of data points across time series for each alignment period. This reducer is valid for gauge and delta metrics of numeric and distribution type. The value of the output is DOUBLE

REDUCE_PERCENTILE_05

Reduce by computing 5th percentile of data points across time series for each alignment period. This reducer is valid for gauge and delta metrics of numeric and distribution type. The value of the output is DOUBLE

UptimeCheckRegion

static

number

The regions from which an uptime check can be run.

Value

REGION_UNSPECIFIED

Default value if no region is specified. Will result in uptime checks running from all regions.

USA

Allows checks to run from locations within the United States of America.

EUROPE

Allows checks to run from locations within the continent of Europe.

SOUTH_AMERICA

Allows checks to run from locations within the continent of South America.

ASIA_PACIFIC

Allows checks to run from locations within the Asia Pacific area (ex: Singapore).

Properties

Aligner

static

number

The Aligner describes how to bring the data points in a single time series into temporal alignment.

Value

ALIGN_NONE

No alignment. Raw data is returned. Not valid if cross-time series reduction is requested. The value type of the result is the same as the value type of the input.

ALIGN_DELTA

Align and convert to delta metric type. This alignment is valid for cumulative metrics and delta metrics. Aligning an existing delta metric to a delta metric requires that the alignment period be increased. The value type of the result is the same as the value type of the input.

ALIGN_RATE

Align and convert to a rate. This alignment is valid for cumulative metrics and delta metrics with numeric values. The output is a gauge metric with value type DOUBLE.

ALIGN_INTERPOLATE

Align by interpolating between adjacent points around the period boundary. This alignment is valid for gauge metrics with numeric values. The value type of the result is the same as the value type of the input.

ALIGN_NEXT_OLDER

Align by shifting the oldest data point before the period boundary to the boundary. This alignment is valid for gauge metrics. The value type of the result is the same as the value type of the input.

ALIGN_MIN

Align time series via aggregation. The resulting data point in the alignment period is the minimum of all data points in the period. This alignment is valid for gauge and delta metrics with numeric values. The value type of the result is the same as the value type of the input.

ALIGN_MAX

Align time series via aggregation. The resulting data point in the alignment period is the maximum of all data points in the period. This alignment is valid for gauge and delta metrics with numeric values. The value type of the result is the same as the value type of the input.

ALIGN_MEAN

Align time series via aggregation. The resulting data point in the alignment period is the average or arithmetic mean of all data points in the period. This alignment is valid for gauge and delta metrics with numeric values. The value type of the output is DOUBLE.

ALIGN_COUNT

Align time series via aggregation. The resulting data point in the alignment period is the count of all data points in the period. This alignment is valid for gauge and delta metrics with numeric or Boolean values. The value type of the output is INT64.

ALIGN_SUM

Align time series via aggregation. The resulting data point in the alignment period is the sum of all data points in the period. This alignment is valid for gauge and delta metrics with numeric and distribution values. The value type of the output is the same as the value type of the input.

ALIGN_STDDEV

Align time series via aggregation. The resulting data point in the alignment period is the standard deviation of all data points in the period. This alignment is valid for gauge and delta metrics with numeric values. The value type of the output is DOUBLE.

ALIGN_COUNT_TRUE

Align time series via aggregation. The resulting data point in the alignment period is the count of True-valued data points in the period. This alignment is valid for gauge metrics with Boolean values. The value type of the output is INT64.

ALIGN_FRACTION_TRUE

Align time series via aggregation. The resulting data point in the alignment period is the fraction of True-valued data points in the period. This alignment is valid for gauge metrics with Boolean values. The output value is in the range [0, 1] and has value type DOUBLE.

ALIGN_PERCENTILE_99

Align time series via aggregation. The resulting data point in the alignment period is the 99th percentile of all data points in the period. This alignment is valid for gauge and delta metrics with distribution values. The output is a gauge metric with value type DOUBLE.

ALIGN_PERCENTILE_95

Align time series via aggregation. The resulting data point in the alignment period is the 95th percentile of all data points in the period. This alignment is valid for gauge and delta metrics with distribution values. The output is a gauge metric with value type DOUBLE.

ALIGN_PERCENTILE_50

Align time series via aggregation. The resulting data point in the alignment period is the 50th percentile of all data points in the period. This alignment is valid for gauge and delta metrics with distribution values. The output is a gauge metric with value type DOUBLE.

ALIGN_PERCENTILE_05

Align time series via aggregation. The resulting data point in the alignment period is the 5th percentile of all data points in the period. This alignment is valid for gauge and delta metrics with distribution values. The output is a gauge metric with value type DOUBLE.

GroupResourceType

static

number

The supported resource types that can be used as values of group_resource.resource_type. gae_app and uptime_url are not allowed because group checks on App Engine modules and URLs are not allowed.

Value

RESOURCE_TYPE_UNSPECIFIED

Default value (not valid).

INSTANCE

A group of instances (could be either GCE or AWS_EC2).

AWS_ELB_LOAD_BALANCER

A group of AWS load balancers.

Reducer

static

number

A Reducer describes how to aggregate data points from multiple time series into a single time series.

Value

REDUCE_NONE

No cross-time series reduction. The output of the aligner is returned.

REDUCE_MEAN

Reduce by computing the mean across time series for each alignment period. This reducer is valid for delta and gauge metrics with numeric or distribution values. The value type of the output is DOUBLE.

REDUCE_MIN

Reduce by computing the minimum across time series for each alignment period. This reducer is valid for delta and gauge metrics with numeric values. The value type of the output is the same as the value type of the input.

REDUCE_MAX

Reduce by computing the maximum across time series for each alignment period. This reducer is valid for delta and gauge metrics with numeric values. The value type of the output is the same as the value type of the input.

REDUCE_SUM

Reduce by computing the sum across time series for each alignment period. This reducer is valid for delta and gauge metrics with numeric and distribution values. The value type of the output is the same as the value type of the input.

REDUCE_STDDEV

Reduce by computing the standard deviation across time series for each alignment period. This reducer is valid for delta and gauge metrics with numeric or distribution values. The value type of the output is DOUBLE.

REDUCE_COUNT

Reduce by computing the count of data points across time series for each alignment period. This reducer is valid for delta and gauge metrics of numeric, Boolean, distribution, and string value type. The value type of the output is INT64.

REDUCE_COUNT_TRUE

Reduce by computing the count of True-valued data points across time series for each alignment period. This reducer is valid for delta and gauge metrics of Boolean value type. The value type of the output is INT64.

REDUCE_FRACTION_TRUE

Reduce by computing the fraction of True-valued data points across time series for each alignment period. This reducer is valid for delta and gauge metrics of Boolean value type. The output value is in the range [0, 1] and has value type DOUBLE.

REDUCE_PERCENTILE_99

Reduce by computing 99th percentile of data points across time series for each alignment period. This reducer is valid for gauge and delta metrics of numeric and distribution type. The value of the output is DOUBLE

REDUCE_PERCENTILE_95

Reduce by computing 95th percentile of data points across time series for each alignment period. This reducer is valid for gauge and delta metrics of numeric and distribution type. The value of the output is DOUBLE

REDUCE_PERCENTILE_50

Reduce by computing 50th percentile of data points across time series for each alignment period. This reducer is valid for gauge and delta metrics of numeric and distribution type. The value of the output is DOUBLE

REDUCE_PERCENTILE_05

Reduce by computing 5th percentile of data points across time series for each alignment period. This reducer is valid for gauge and delta metrics of numeric and distribution type. The value of the output is DOUBLE

UptimeCheckRegion

static

number

The regions from which an uptime check can be run.

Value

REGION_UNSPECIFIED

Default value if no region is specified. Will result in uptime checks running from all regions.

USA

Allows checks to run from locations within the United States of America.

EUROPE

Allows checks to run from locations within the continent of Europe.

SOUTH_AMERICA

Allows checks to run from locations within the continent of South America.

ASIA_PACIFIC

Allows checks to run from locations within the Asia Pacific area (ex: Singapore).

Abstract types

Aggregation

static

Describes how to combine multiple time series to provide different views of the data. Aggregation consists of an alignment step on individual time series (per_series_aligner) followed by an optional reduction of the data across different time series (cross_series_reducer). For more details, see Aggregation.

Properties

Parameter

alignmentPeriod

Object

The alignment period for per-time series alignment. If present, alignmentPeriod must be at least 60 seconds. After per-time series alignment, each time series will contain data points only on the period boundaries. If perSeriesAligner is not specified or equals ALIGN_NONE, then this field is ignored. If perSeriesAligner is specified and does not equal ALIGN_NONE, then this field must be defined; otherwise an error is returned.

This object should have the same structure as Duration

perSeriesAligner

number

The approach to be used to align individual time series. Not all alignment functions may be applied to all time series, depending on the metric type and value type of the original time series. Alignment may change the metric type or the value type of the time series.

Time series data must be aligned in order to perform cross-time series reduction. If crossSeriesReducer is specified, then perSeriesAligner must be specified and not equal ALIGN_NONE and alignmentPeriod must be specified; otherwise, an error is returned.

The number should be among the values of Aligner

crossSeriesReducer

number

The approach to be used to combine time series. Not all reducer functions may be applied to all time series, depending on the metric type and the value type of the original time series. Reduction may change the metric type of value type of the time series.

Time series data must be aligned in order to perform cross-time series reduction. If crossSeriesReducer is specified, then perSeriesAligner must be specified and not equal ALIGN_NONE and alignmentPeriod must be specified; otherwise, an error is returned.

The number should be among the values of Reducer

groupByFields

Array of string

The set of fields to preserve when crossSeriesReducer is specified. The groupByFields determine how the time series are partitioned into subsets prior to applying the aggregation function. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The crossSeriesReducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in groupByFields are aggregated away. If groupByFields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If crossSeriesReducer is not defined, this field is ignored.

See also

google.monitoring.v3.Aggregation definition in proto format

BasicAuthentication

static

A type of authentication to perform against the specified resource or URL that uses username and password. Currently, only Basic authentication is supported in Uptime Monitoring.

Properties

Parameter

username

string

The username to authenticate.

password

string

The password to authenticate.

See also

google.monitoring.v3.UptimeCheckConfig.HttpCheck.BasicAuthentication definition in proto format

ContentMatcher

static

Used to perform string matching. Currently, this matches on the exact content. In the future, it can be expanded to allow for regular expressions and more complex matching.

Property

Parameter

content

string

String content to match

See also

google.monitoring.v3.UptimeCheckConfig.ContentMatcher definition in proto format

Group

static

The description of a dynamic collection of monitored resources. Each group has a filter that is matched against monitored resources and their associated metadata. If a group's filter matches an available monitored resource, then that resource is a member of that group. Groups can contain any number of monitored resources, and each monitored resource can be a member of any number of groups.

Groups can be nested in parent-child hierarchies. The parentName field identifies an optional parent for each group. If a group has a parent, then the only monitored resources available to be matched by the group's filter are the resources contained in the parent group. In other words, a group contains the monitored resources that match its filter and the filters of all the group's ancestors. A group without a parent can contain any monitored resource.

For example, consider an infrastructure running a set of instances with two user-defined tags: "environment" and "role". A parent group has a filter, environment="production". A child of that parent group has a filter, role="transcoder". The parent group contains all instances in the production environment, regardless of their roles. The child group contains instances that have the transcoder role and are in the production environment.

The monitored resources contained in a group can change at any moment, depending on what resources exist and what filters are associated with the group and its ancestors.

Properties

Parameter

name

string

Output only. The name of this group. The format is "projects/{project_id_or_number}/groups/{group_id}". When creating a group, this field is ignored and a new name is created consisting of the project specified in the call to CreateGroup and a unique {group_id} that is generated automatically.

displayName

string

A user-assigned name for this group, used only for display purposes.

parentName

string

The name of the group's parent, if it has one. The format is "projects/{project_id_or_number}/groups/{group_id}". For groups with no parent, parentName is the empty string, "".

filter

string

The filter used to determine which monitored resources belong to this group.

isCluster

boolean

If true, the members of this group are considered to be a cluster. The system can perform additional analysis on groups that are clusters.

See also

google.monitoring.v3.Group definition in proto format

HttpCheck

static

Information involved in an HTTP/HTTPS uptime check request.

Properties

Parameter

useSsl

boolean

If true, use HTTPS instead of HTTP to run the check.

path

string

The path to the page to run the check against. Will be combined with the host (specified within the MonitoredResource) and port to construct the full URL. Optional (defaults to "/").

port

number

The port to the page to run the check against. Will be combined with host (specified within the MonitoredResource) and path to construct the full URL. Optional (defaults to 80 without SSL, or 443 with SSL).

authInfo

Object

The authentication information. Optional when creating an HTTP check; defaults to empty.

This object should have the same structure as BasicAuthentication

maskHeaders

boolean

Boolean specifiying whether to encrypt the header information. Encryption should be specified for any headers related to authentication that you do not wish to be seen when retrieving the configuration. The server will be responsible for encrypting the headers. On Get/List calls, if mask_headers is set to True then the headers will be obscured with **.

headers

Object with string properties

The list of headers to send as part of the uptime check request. If two headers have the same key and different values, they should be entered as a single header, with the value being a comma-separated list of all the desired values as described at https://www.w3.org/Protocols/rfc2616/rfc2616.txt (page 31). Entering two separate headers with the same key in a Create call will cause the first to be overwritten by the second.

See also

google.monitoring.v3.UptimeCheckConfig.HttpCheck definition in proto format

Point

static

A single data point in a time series.

Properties

Parameter

interval

Object

The time interval to which the data point applies. For GAUGE metrics, only the end time of the interval is used. For DELTA metrics, the start and end time should specify a non-zero interval, with subsequent points specifying contiguous and non-overlapping intervals. For CUMULATIVE metrics, the start and end time should specify a non-zero interval, with subsequent points specifying the same start time and increasing end times, until an event resets the cumulative value to zero and sets a new start time for the following points.

This object should have the same structure as TimeInterval

value

Object

The value of the data point.

This object should have the same structure as TypedValue

See also

google.monitoring.v3.Point definition in proto format

ResourceGroup

static

The resource submessage for group checks. It can be used instead of a monitored resource, when multiple resources are being monitored.

Properties

Parameter

groupId

string

The group of resources being monitored. Should be only the group_id, not projects/ /groups/ .

resourceType

number

The resource type of the group members.

The number should be among the values of GroupResourceType

See also

google.monitoring.v3.UptimeCheckConfig.ResourceGroup definition in proto format

TcpCheck

static

Information required for a TCP uptime check request.

Property

Parameter

port

number

The port to the page to run the check against. Will be combined with host (specified within the MonitoredResource) to construct the full URL. Required.

See also

google.monitoring.v3.UptimeCheckConfig.TcpCheck definition in proto format

TimeInterval

static

A time interval extending just after a start time through an end time. If the start time is the same as the end time, then the interval represents a single point in time.

Properties

Parameter

endTime

Object

Required. The end of the time interval.

This object should have the same structure as Timestamp

startTime

Object

Optional. The beginning of the time interval. The default value for the start time is the end time. The start time must not be later than the end time.

This object should have the same structure as Timestamp

See also

google.monitoring.v3.TimeInterval definition in proto format

TimeSeries

static

A collection of data points that describes the time-varying values of a metric. A time series is identified by a combination of a fully-specified monitored resource and a fully-specified metric. This type is used for both listing and creating time series.

Properties

Parameter

metric

Object

The associated metric. A fully-specified metric used to identify the time series.

This object should have the same structure as Metric

resource

Object

The associated resource. A fully-specified monitored resource used to identify the time series.

This object should have the same structure as MonitoredResource

metricKind

number

The metric kind of the time series. When listing time series, this metric kind might be different from the metric kind of the associated metric if this time series is an alignment or reduction of other time series.

When creating a time series, this field is optional. If present, it must be the same as the metric kind of the associated metric. If the associated metric's descriptor must be auto-created, then this field specifies the metric kind of the new descriptor and must be either GAUGE (the default) or CUMULATIVE.

The number should be among the values of MetricKind

valueType

number

The value type of the time series. When listing time series, this value type might be different from the value type of the associated metric if this time series is an alignment or reduction of other time series.

When creating a time series, this field is optional. If present, it must be the same as the type of the data in the points field.

The number should be among the values of ValueType

points

Array of Object

The data points of this time series. When listing time series, the order of the points is specified by the list method.

When creating a time series, this field must contain exactly one point and the point's type must be the same as the value type of the associated metric. If the associated metric's descriptor must be auto-created, then the value type of the descriptor is determined by the point's type, which must be BOOL, INT64, DOUBLE, or DISTRIBUTION.

This object should have the same structure as Point

See also

google.monitoring.v3.TimeSeries definition in proto format

TypedValue

static

A single strongly-typed value.

Properties

Parameter

boolValue

boolean

A Boolean value: true or false.

int64Value

number

A 64-bit integer. Its range is approximately ±9.2x1018.

doubleValue

number

A 64-bit double-precision floating-point number. Its magnitude is approximately ±10±300 and it has 16 significant digits of precision.

stringValue

string

A variable-length string value.

distributionValue

Object

A distribution value.

This object should have the same structure as Distribution

See also

google.monitoring.v3.TypedValue definition in proto format

UptimeCheckConfig

static

This message configures which resources and services to monitor for availability.

Properties

Parameter

name

string

A unique resource name for this UptimeCheckConfig. The format is:

projects/[PROJECT_ID]/uptimeCheckConfigs/[UPTIME_CHECK_ID].

This field should be omitted when creating the uptime check configuration; on create, the resource name is assigned by the server and included in the response.

displayName

string

A human-friendly name for the uptime check configuration. The display name should be unique within a Stackdriver Account in order to make it easier to identify; however, uniqueness is not enforced. Required.

monitoredResource

Object

The monitored resource associated with the configuration.

This object should have the same structure as MonitoredResource

resourceGroup

Object

The group resource associated with the configuration.

This object should have the same structure as ResourceGroup

httpCheck

Object

Contains information needed to make an HTTP or HTTPS check.

This object should have the same structure as HttpCheck

tcpCheck

Object

Contains information needed to make a TCP check.

This object should have the same structure as TcpCheck

period

Object

How often the uptime check is performed. Currently, only 1, 5, 10, and 15 minutes are supported. Required.

This object should have the same structure as Duration

timeout

Object

The maximum amount of time to wait for the request to complete (must be between 1 and 60 seconds). Required.

This object should have the same structure as Duration

contentMatchers

Array of Object

The expected content on the page the check is run against. Currently, only the first entry in the list is supported, and other entries will be ignored. The server will look for an exact match of the string in the page response's content. This field is optional and should only be specified if a content match is required.

This object should have the same structure as ContentMatcher

selectedRegions

Array of number

The list of regions from which the check will be run. If this field is specified, enough regions to include a minimum of 3 locations must be provided, or an error message is returned. Not specifying this field will result in uptime checks running from all regions.

The number should be among the values of UptimeCheckRegion

See also

google.monitoring.v3.UptimeCheckConfig definition in proto format

UptimeCheckIp

static

Contains the region, location, and list of IP addresses where checkers in the location run from.

Properties

Parameter

region

number

A broad region category in which the IP address is located.

The number should be among the values of UptimeCheckRegion

location

string

A more specific location within the region that typically encodes a particular city/town/metro (and its containing state/province or country) within the broader umbrella region category.

ipAddress

string

The IP address from which the uptime check originates. This is a full IP address (not an IP address range). Most IP addresses, as of this publication, are in IPv4 format; however, one should not rely on the IP addresses being in IPv4 format indefinitely and should support interpreting this field in either IPv4 or IPv6 format.

See also

google.monitoring.v3.UptimeCheckIp definition in proto format