Package google.monitoring.dashboard.v1

Index

DashboardsService

Manages Stackdriver dashboards. A dashboard is an arrangement of data display widgets in a specific layout.

CreateDashboard

rpc CreateDashboard(CreateDashboardRequest) returns (Dashboard)

Creates a new custom dashboard.

This method requires the monitoring.dashboards.create permission on the specified project. For more information, see Google Cloud IAM.

Authorization Scopes

Requires one of the following OAuth scopes:

  • https://www.googleapis.com/auth/cloud-platform
  • https://www.googleapis.com/auth/monitoring
  • https://www.googleapis.com/auth/monitoring.write

For more information, see the Authentication Overview.

DeleteDashboard

rpc DeleteDashboard(DeleteDashboardRequest) returns (Empty)

Deletes an existing custom dashboard.

This method requires the monitoring.dashboards.delete permission on the specified dashboard. For more information, see Google Cloud IAM.

Authorization Scopes

Requires one of the following OAuth scopes:

  • https://www.googleapis.com/auth/cloud-platform
  • https://www.googleapis.com/auth/monitoring
  • https://www.googleapis.com/auth/monitoring.write

For more information, see the Authentication Overview.

GetDashboard

rpc GetDashboard(GetDashboardRequest) returns (Dashboard)

Fetches a specific dashboard.

This method requires the monitoring.dashboards.get permission on the specified dashboard. For more information, see Google Cloud IAM.

Authorization Scopes

Requires one of the following OAuth scopes:

  • https://www.googleapis.com/auth/cloud-platform
  • https://www.googleapis.com/auth/monitoring
  • https://www.googleapis.com/auth/monitoring.read

For more information, see the Authentication Overview.

ListDashboards

rpc ListDashboards(ListDashboardsRequest) returns (ListDashboardsResponse)

Lists the existing dashboards.

This method requires the monitoring.dashboards.list permission on the specified project. For more information, see Google Cloud IAM.

Authorization Scopes

Requires one of the following OAuth scopes:

  • https://www.googleapis.com/auth/cloud-platform
  • https://www.googleapis.com/auth/monitoring
  • https://www.googleapis.com/auth/monitoring.read

For more information, see the Authentication Overview.

UpdateDashboard

rpc UpdateDashboard(UpdateDashboardRequest) returns (Dashboard)

Replaces an existing custom dashboard with a new definition.

This method requires the monitoring.dashboards.update permission on the specified dashboard. For more information, see Google Cloud IAM.

Authorization Scopes

Requires one of the following OAuth scopes:

  • https://www.googleapis.com/auth/cloud-platform
  • https://www.googleapis.com/auth/monitoring
  • https://www.googleapis.com/auth/monitoring.write

For more information, see the Authentication Overview.

Aggregation

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

Fields
alignment_period

Duration

The alignment period for per-[time series][TimeSeries] 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.

per_series_aligner

Aligner

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.

cross_series_reducer

Reducer

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.

group_by_fields[]

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.

Aligner

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

Enums
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.

One can think of this aligner as a rate but without time units; that is, the output is conceptually (second_point - first_point).

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.

One can think of this aligner as conceptually providing the slope of the line that passes through the value at the start and end of the window. In other words, this is conceptually ((y1 - y0)/(t1 - t0)), and the output unit is one that has a "/time" dimension.

If, by rate, you are looking for percentage change, see the ALIGN_PERCENT_CHANGE aligner option.

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_COUNT_FALSE Align time series via aggregation. The resulting data point in the alignment period is the count of False-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.
ALIGN_PERCENT_CHANGE Align and convert to a percentage change. This alignment is valid for gauge and delta metrics with numeric values. This alignment conceptually computes the equivalent of "((current - previous)/previous)*100" where previous value is determined based on the alignmentPeriod. In the event that previous is 0 the calculated value is infinity with the exception that if both (current - previous) and previous are 0 the calculated value is 0. A 10 minute moving mean is computed at each point of the time window prior to the above calculation to smooth the metric and prevent false positives from very short lived spikes. Only applicable for data that is >= 0. Any values < 0 are treated as no data. While delta metrics are accepted by this alignment special care should be taken that the values for the metric will always be positive. The output is a gauge metric with value type DOUBLE.

Reducer

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

Enums
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_COUNT_FALSE Reduce by computing the count of False-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

ChartOptions

Options to control visual rendering of a chart.

Fields
mode

Mode

The chart mode.

Mode

Chart mode options.

Enums
MODE_UNSPECIFIED Mode is unspecified. The view will default to COLOR.
COLOR The chart distinguishes data series using different color. Line colors may get reused when there are many lines in the chart.
X_RAY The chart uses the Stackdriver x-ray mode, in which each data set is plotted using the same semi-transparent color.
STATS The chart displays statistics such as average, median, 95th percentile, and more.

ColumnLayout

A simplified layout that divides the available space into vertical columns and arranges a set of widgets vertically in each column.

Fields
columns[]

Column

The columns of content to display.

Column

Defines the layout properties and content for a column.

Fields
weight

int64

The relative weight of this column. The column weight is used to adjust the width of columns on the screen (relative to peers). Greater the weight, greater the width of the column on the screen. If omitted, a value of 1 is used while rendering.

widgets[]

Widget

The display widgets arranged vertically in this column.

CreateDashboardRequest

The CreateDashboard request.

Fields
parent

string

Required. The project on which to execute the request. The format is "projects/{project_id_or_number}". The {project_id_or_number} must match the dashboard resource name.

Authorization requires the following Google IAM permission on the specified resource parent:

  • monitoring.dashboards.create
dashboard

Dashboard

Required. The initial dashboard specification.

Dashboard

A Google Stackdriver dashboard. Dashboards define the content and layout of pages in the Stackdriver web application.

Fields
name

string

The resource name of the dashboard.

display_name

string

The mutable, human-readable name.

etag

string

etag is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. An etag is returned in the response to GetDashboard, and users are expected to put that etag in the request to UpdateDashboard to ensure that their change will be applied to the same version of the Dashboard configuration. The field should not be passed during dashboard creation.

Union field layout. A dashboard's root container element that defines the layout style. layout can be only one of the following:
grid_layout

GridLayout

Content is arranged with a basic layout that re-flows a simple list of informational elements like widgets or tiles.

row_layout

RowLayout

The content is divided into equally spaced rows and the widgets are arranged horizontally.

column_layout

ColumnLayout

The content is divided into equally spaced columns and the widgets are arranged vertically.

DeleteDashboardRequest

The DeleteDashboard request.

Fields
name

string

Required. The resource name of the Dashboard. The format is "projects/{project_id_or_number}/dashboards/{dashboard_id}".

Authorization requires the following Google IAM permission on the specified resource name:

  • monitoring.dashboards.delete

GetDashboardRequest

The GetDashboard request.

Fields
name

string

Required. The resource name of the Dashboard. The format is one of "dashboards/{dashboard_id}" (for system dashboards) or "projects/{project_id_or_number}/dashboards/{dashboard_id}" (for custom dashboards).

Authorization requires the following Google IAM permission on the specified resource name:

  • monitoring.dashboards.get

GridLayout

A basic layout divides the available space into vertical columns of equal width and arranges a list of widgets using a row-first strategy.

Fields
columns

int64

The number of columns into which the view's width is divided. If omitted or set to zero, a system default will be used while rendering.

widgets[]

Widget

The informational elements that are arranged into the columns row-first.

ListDashboardsRequest

The ListDashboards request.

Fields
parent

string

Required. The scope of the dashboards to list. A project scope must be specified in the form of "projects/{project_id_or_number}".

Authorization requires the following Google IAM permission on the specified resource parent:

  • monitoring.dashboards.list
page_size

int32

A positive number that is the maximum number of results to return. If unspecified, a default of 1000 is used.

page_token

string

If this field is not empty then it must contain the nextPageToken value returned by a previous call to this method. Using this field causes the method to return additional results from the previous method call.

ListDashboardsResponse

The ListDashboards request.

Fields
dashboards[]

Dashboard

The list of requested dashboards.

next_page_token

string

If there are more results than have been returned, then this field is set to a non-empty value. To see the additional results, use that value as pageToken in the next call to this method.

PickTimeSeriesFilter

Describes a ranking-based time series filter. Each input time series is ranked with an aligner. The filter lets through up to num_time_series time series, selecting them based on the relative ranking.

Fields
ranking_method

Method

rankingMethod is applied to each time series independently to produce the value which will be used to compare the time series to other time series.

num_time_series

int32

How many time series to return.

direction

Direction

How to use the ranking to select time series that pass through the filter.

Direction

Describes the ranking directions.

Enums
DIRECTION_UNSPECIFIED Not allowed in well-formed requests.
TOP Pass the highest ranking inputs.
BOTTOM Pass the lowest ranking inputs.

Method

The value reducers that can be applied to a PickTimeSeriesFilter.

Enums
METHOD_UNSPECIFIED Not allowed in well-formed requests.
METHOD_MEAN Select the mean of all values.
METHOD_MAX Select the maximum value.
METHOD_MIN Select the minimum value.
METHOD_SUM Compute the sum of all values.
METHOD_LATEST Select the most recent value.

RowLayout

A simplified layout that divides the available space into rows and arranges a set of widgets horizontally in each row.

Fields
rows[]

Row

The rows of content to display.

Row

Defines the layout properties and content for a row.

Fields
weight

int64

The relative weight of this row. The row weight is used to adjust the height of rows on the screen (relative to peers). Greater the weight, greater the height of the row on the screen. If omitted, a value of 1 is used while rendering.

widgets[]

Widget

The display widgets arranged horizontally in this row.

Scorecard

A widget showing the latest value of a metric, and how this value relates to one or more thresholds.

Fields
time_series_query

TimeSeriesQuery

Fields for querying time series data from the Stackdriver metrics API.

thresholds[]

Threshold

The thresholds used to determine the state of the scorecard given the time series' current value. For an actual value x, the scorecard is in a danger state if x is less than or equal to a danger threshold that triggers below, or greater than or equal to a danger threshold that triggers above. Similarly, if x is above/below a warning threshold that triggers above/below, then the scorecard is in a warning state - unless x also puts it in a danger state. (Danger trumps warning.)

As an example, consider a scorecard with the following four thresholds: { value: 90, category: 'DANGER', trigger: 'ABOVE', }, { value: 70, category: 'WARNING', trigger: 'ABOVE', }, { value: 10, category: 'DANGER', trigger: 'BELOW', }, { value: 20, category: 'WARNING', trigger: 'BELOW', }

Then: values less than or equal to 10 would put the scorecard in a DANGER state, values greater than 10 but less than or equal to 20 a WARNING state, values strictly between 20 and 70 an OK state, values greater than or equal to 70 but less than 90 a WARNING state, and values greater than or equal to 90 a DANGER state.

Union field data_view. Defines the optional additional chart shown on the scorecard. If neither is included - then a default scorecard is shown. data_view can be only one of the following:
gauge_view

GaugeView

Will cause the scorecard to show a gauge chart.

spark_chart_view

SparkChartView

Will cause the scorecard to show a spark chart.

GaugeView

A gauge chart shows where the current value sits within a pre-defined range. The upper and lower bounds should define the possible range of values for the scorecard's query (inclusive).

Fields
lower_bound

double

The lower bound for this gauge chart. The value of the chart should always be greater than or equal to this.

upper_bound

double

The upper bound for this gauge chart. The value of the chart should always be less than or equal to this.

SparkChartView

A sparkChart is a small chart suitable for inclusion in a table-cell or inline in text. This message contains the configuration for a sparkChart to show up on a Scorecard, showing recent trends of the scorecard's timeseries.

Fields
spark_chart_type

SparkChartType

The type of sparkchart to show in this chartView.

min_alignment_period

Duration

The lower bound on data point frequency in the chart implemented by specifying the minimum alignment period to use in a time series query. For example, if the data is published once every 10 minutes it would not make sense to fetch and align data at one minute intervals. This field is optional and exists only as a hint.

SparkChartType

Defines the possible types of spark chart supported by the Scorecard.

Enums
SPARK_CHART_TYPE_UNSPECIFIED Not allowed in well-formed requests.
SPARK_LINE The sparkline will be rendered as a small line chart.
SPARK_BAR The sparkbar will be rendered as a small bar chart.

StatisticalTimeSeriesFilter

A filter that ranks streams based on their statistical relation to other streams in a request.

Fields
ranking_method

Method

rankingMethod is applied to a set of time series, and then the produced value for each individual time series is used to compare a given time series to others. These are methods that cannot be applied stream-by-stream, but rather require the full context of a request to evaluate time series.

num_time_series

int32

How many time series to output.

Method

The filter methods that can be applied to a stream.

Enums
METHOD_UNSPECIFIED Not allowed in well-formed requests.
METHOD_CLUSTER_OUTLIER Compute the outlier score of each stream.

Text

A widget that displays textual content.

Fields
content

string

The text content to be displayed.

format

Format

How the text content is formatted.

Format

The format type of the text content.

Enums
FORMAT_UNSPECIFIED Format is unspecified. Defaults to MARKDOWN.
MARKDOWN The text contains Markdown formatting.
RAW The text contains no special formatting.

Threshold

Defines a threshold for categorizing time series values.

Fields
label

string

A label for the threshold.

value

double

The value of the threshold. The value should be defined in the native scale of the metric.

color

Color

The state color for this threshold. Color is not allowed in a XyChart.

direction

Direction

The direction for the current threshold. Direction is not allowed in a XyChart.

Color

The color suggests an interpretation to the viewer when actual values cross the threshold. Comments on each color provide UX guidance on how users can be expected to interpret a given state color.

Enums
COLOR_UNSPECIFIED Color is unspecified. Not allowed in well-formed requests.
YELLOW Crossing the threshold is "concerning" behavior.
RED Crossing the threshold is "emergency" behavior.

Direction

Whether the threshold is considered crossed by an actual value above or below its threshold value.

Enums
DIRECTION_UNSPECIFIED Not allowed in well-formed requests.
ABOVE The threshold will be considered crossed if the actual value is above the threshold value.
BELOW The threshold will be considered crossed if the actual value is below the threshold value.

TimeSeriesFilter

A filter that defines a subset of time series data that is displayed in a widget. Time series data is fetched using the ListTimeSeries method.

Fields
filter

string

Required. The monitoring filter that identifies the metric types, resources, and projects to query.

aggregation

Aggregation

By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.

Union field output_filter. Selects an optional time series filter. output_filter can be only one of the following:
pick_time_series_filter

PickTimeSeriesFilter

Ranking based time series filter.

statistical_time_series_filter

StatisticalTimeSeriesFilter

Statistics based time series filter.

TimeSeriesFilterRatio

A pair of time series filters that define a ratio computation. The output time series is the pair-wise division of each aligned element from the numerator and denominator time series.

Fields
numerator

RatioPart

The numerator of the ratio.

denominator

RatioPart

The denominator of the ratio.

secondary_aggregation

Aggregation

Apply a second aggregation after the ratio is computed.

Union field output_filter. Selects an optional filter that is applied to the time series after computing the ratio. output_filter can be only one of the following:
pick_time_series_filter

PickTimeSeriesFilter

Ranking based time series filter.

statistical_time_series_filter

StatisticalTimeSeriesFilter

Statistics based time series filter.

RatioPart

Describes a query to build the numerator or denominator of a TimeSeriesFilterRatio.

Fields
filter

string

Required. The monitoring filter that identifies the metric types, resources, and projects to query.

aggregation

Aggregation

By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.

TimeSeriesQuery

TimeSeriesQuery collects the set of supported methods for querying time series data from the Stackdriver metrics API.

Fields
unit_override

string

The unit of data contained in fetched time series. If non-empty, this unit will override any unit that accompanies fetched data. The format is the same as the unit field in MetricDescriptor.

Union field source. Parameters needed to obtain data for the chart. source can be only one of the following:
time_series_filter

TimeSeriesFilter

Filter parameters to fetch time series.

time_series_filter_ratio

TimeSeriesFilterRatio

Parameters to fetch a ratio between two time series filters.

UpdateDashboardRequest

The UpdateDashboard request.

Fields
dashboard

Dashboard

Required. The dashboard that will replace the existing dashboard.

Authorization requires the following Google IAM permission on the specified resource dashboard:

  • monitoring.dashboards.update

Widget

Widget contains a single dashboard component and configuration of how to present the component in the dashboard.

Fields
title

string

Optional. The title of the widget.

Union field content. Content defines the component used to populate the widget. content can be only one of the following:
xy_chart

XyChart

A chart of time series data.

scorecard

Scorecard

A scorecard summarizing time series data.

text

Text

A raw string or markdown displaying textual content.

blank

Empty

A blank space.

XyChart

A chart that displays data on a 2D (X and Y axes) plane.

Fields
data_sets[]

DataSet

The data displayed in this chart.

timeshift_duration

Duration

The duration used to display a comparison chart. A comparison chart simultaneously shows values from two similar-length time periods (e.g., week-over-week metrics). The duration must be positive, and it can only be applied to charts with data sets of LINE plot type.

thresholds[]

Threshold

Threshold lines drawn horizontally across the chart.

x_axis

Axis

The properties applied to the X axis.

y_axis

Axis

The properties applied to the Y axis.

chart_options

ChartOptions

Display options for the chart.

Axis

A chart axis.

Fields
label

string

The label of the axis.

scale

Scale

The axis scale. By default, a linear scale is used.

Scale

Types of scales used in axes.

Enums
SCALE_UNSPECIFIED Scale is unspecified. The view will default to LINEAR.
LINEAR Linear scale.
LOG10 Logarithmic scale (base 10).

DataSet

Groups a time series query definition with charting options.

Fields
time_series_query

TimeSeriesQuery

Fields for querying time series data from the Stackdriver metrics API.

plot_type

PlotType

How this data should be plotted on the chart.

legend_template

string

A template string for naming TimeSeries in the resulting data set. This should be a string with interpolations of the form ${label_name}, which will resolve to the label's value.

min_alignment_period

Duration

Optional. The lower bound on data point frequency for this data set, implemented by specifying the minimum alignment period to use in a time series query For example, if the data is published once every 10 minutes, the min_alignment_period should be at least 10 minutes. It would not make sense to fetch and align data at one minute intervals.

PlotType

The types of plotting strategies for data sets.

Enums
PLOT_TYPE_UNSPECIFIED Plot type is unspecified. The view will default to LINE.
LINE The data is plotted as a set of lines (one line per series).
STACKED_AREA The data is plotted as a set of filled areas (one area per series), with the areas stacked vertically (the base of each area is the top of its predecessor, and the base of the first area is the X axis). Since the areas do not overlap, each is filled with a different opaque color.
STACKED_BAR The data is plotted as a set of rectangular boxes (one box per series), with the boxes stacked vertically (the base of each box is the top of its predecessor, and the base of the first box is the X axis). Since the boxes do not overlap, each is filled with a different opaque color.
HEATMAP The data is plotted as a heatmap. The series being plotted must have a DISTRIBUTION value type. The value of each bucket in the distribution is displayed as a color. This type is not currently available in the Stackdriver Monitoring application.
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