package google.monitoring.dashboard.v1
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Manages Stackdriver dashboards. A dashboard is an arrangement of data display widgets in a specific layout.
Creates a new custom dashboard. For examples on how you can use this API to create dashboards, see [Managing dashboards by API](https://cloud.google.com/monitoring/dashboards/api-dashboard). This method requires the `monitoring.dashboards.create` permission on the specified project. For more information about permissions, see [Cloud Identity and Access Management](https://cloud.google.com/iam).
message
dashboards_service.proto:108The `CreateDashboard` request.
string parent = 1
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.
optional dashboard = 2
Required. The initial dashboard specification.
bool validate_only = 3
If set, validate the request and preview the review, but do not actually save it.
Lists the existing dashboards. This method requires the `monitoring.dashboards.list` permission on the specified project. For more information, see [Cloud Identity and Access Management](https://cloud.google.com/iam).
message
dashboards_service.proto:130The `ListDashboards` request.
string parent = 1
Required. The scope of the dashboards to list. The format is: projects/[PROJECT_ID_OR_NUMBER]
int32 page_size = 2
A positive number that is the maximum number of results to return. If unspecified, a default of 1000 is used.
string page_token = 3
Optional. 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.
message
dashboards_service.proto:153The `ListDashboards` request.
repeated dashboards = 1
The list of requested dashboards.
string next_page_token = 2
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 `page_token` in the next call to this method.
Fetches a specific dashboard. This method requires the `monitoring.dashboards.get` permission on the specified dashboard. For more information, see [Cloud Identity and Access Management](https://cloud.google.com/iam).
message
dashboards_service.proto:164The `GetDashboard` request.
string name = 1
Required. The resource name of the Dashboard. The format is one of: - `dashboards/[DASHBOARD_ID]` (for system dashboards) - `projects/[PROJECT_ID_OR_NUMBER]/dashboards/[DASHBOARD_ID]` (for custom dashboards).
Deletes an existing custom dashboard. This method requires the `monitoring.dashboards.delete` permission on the specified dashboard. For more information, see [Cloud Identity and Access Management](https://cloud.google.com/iam).
message
dashboards_service.proto:179The `DeleteDashboard` request.
string name = 1
Required. The resource name of the Dashboard. The format is: projects/[PROJECT_ID_OR_NUMBER]/dashboards/[DASHBOARD_ID]
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 [Cloud Identity and Access Management](https://cloud.google.com/iam).
message
dashboards_service.proto:192The `UpdateDashboard` request.
optional dashboard = 1
Required. The dashboard that will replace the existing dashboard.
bool validate_only = 3
If set, validate the request and preview the review, but do not actually save it.
message
common.proto:56Describes how to combine multiple time series to provide a different view of the data. Aggregation of time series is done in two steps. First, each time series in the set is _aligned_ to the same time interval boundaries, then the set of time series is optionally _reduced_ in number. Alignment consists of applying the `per_series_aligner` operation to each time series after its data has been divided into regular `alignment_period` time intervals. This process takes _all_ of the data points in an alignment period, applies a mathematical transformation such as averaging, minimum, maximum, delta, etc., and converts them into a single data point per period. Reduction is when the aligned and transformed time series can optionally be combined, reducing the number of time series through similar mathematical transformations. Reduction involves applying a `cross_series_reducer` to all the time series, optionally sorting the time series into subsets with `group_by_fields`, and applying the reducer to each subset. The raw time series data can contain a huge amount of information from multiple sources. Alignment and reduction transforms this mass of data into a more manageable and representative collection of data, for example "the 95% latency across the average of all tasks in a cluster". This representative data can be more easily graphed and comprehended, and the individual time series data is still available for later drilldown. For more details, see [Filtering and aggregation](https://cloud.google.com/monitoring/api/v3/aggregation).
Used in: , ,
optional alignment_period = 1
The `alignment_period` specifies a time interval, in seconds, that is used to divide the data in all the [time series][google.monitoring.v3.TimeSeries] into consistent blocks of time. This will be done before the per-series aligner can be applied to the data. The value must be at least 60 seconds. If a per-series aligner other than `ALIGN_NONE` is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner `ALIGN_NONE` is specified, then this field is ignored. The maximum value of the `alignment_period` is 2 years, or 104 weeks.
Aggregation.Aligner per_series_aligner = 2
An `Aligner` describes how to bring the data points in a single time series into temporal alignment. Except for `ALIGN_NONE`, all alignments cause all the data points in an `alignment_period` to be mathematically grouped together, resulting in a single data point for each `alignment_period` with end timestamp at the end of the period. Not all alignment operations may be applied to all time series. The valid choices depend on the `metric_kind` and `value_type` of the original time series. Alignment can change the `metric_kind` or the `value_type` of the time series. Time series data must be aligned in order to perform cross-time series reduction. If `cross_series_reducer` is specified, then `per_series_aligner` must be specified and not equal to `ALIGN_NONE` and `alignment_period` must be specified; otherwise, an error is returned.
Aggregation.Reducer cross_series_reducer = 4
The reduction operation to be used to combine time series into a single time series, where the value of each data point in the resulting series is a function of all the already aligned values in the input time series. Not all reducer operations can be applied to all time series. The valid choices depend on the `metric_kind` and the `value_type` of the original time series. Reduction can yield a time series with a different `metric_kind` or `value_type` than the input time series. Time series data must first be aligned (see `per_series_aligner`) in order to perform cross-time series reduction. If `cross_series_reducer` is specified, then `per_series_aligner` must be specified, and must not be `ALIGN_NONE`. An `alignment_period` must also be specified; otherwise, an error is returned.
repeated string group_by_fields = 5
The set of fields to preserve when `cross_series_reducer` is specified. The `group_by_fields` determine how the time series are partitioned into subsets prior to applying the aggregation operation. 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 `cross_series_reducer` 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 `group_by_fields` are aggregated away. If `group_by_fields` 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 `cross_series_reducer` is not defined, this field is ignored.
The `Aligner` specifies the operation that will be applied to the data points in each alignment period in a time series. Except for `ALIGN_NONE`, which specifies that no operation be applied, each alignment operation replaces the set of data values in each alignment period with a single value: the result of applying the operation to the data values. An aligned time series has a single data value at the end of each `alignment_period`. An alignment operation can change the data type of the values, too. For example, if you apply a counting operation to boolean values, the data `value_type` in the original time series is `BOOLEAN`, but the `value_type` in the aligned result is `INT64`.
Used in:
ALIGN_NONE = 0
No alignment. Raw data is returned. Not valid if cross-series reduction is requested. The `value_type` of the result is the same as the `value_type` of the input.
ALIGN_DELTA = 1
Align and convert to [DELTA][google.api.MetricDescriptor.MetricKind.DELTA]. The output is `delta = y1 - y0`. This alignment is valid for [CUMULATIVE][google.api.MetricDescriptor.MetricKind.CUMULATIVE] and `DELTA` metrics. If the selected alignment period results in periods with no data, then the aligned value for such a period is created by interpolation. The `value_type` of the aligned result is the same as the `value_type` of the input.
ALIGN_RATE = 2
Align and convert to a rate. The result is computed as `rate = (y1 - y0)/(t1 - t0)`, or "delta over time". Think of this aligner as providing the slope of the line that passes through the value at the start and at the end of the `alignment_period`. This aligner is valid for `CUMULATIVE` and `DELTA` metrics with numeric values. If the selected alignment period results in periods with no data, then the aligned value for such a period is created by interpolation. The output is a `GAUGE` metric with `value_type` `DOUBLE`. If, by "rate", you mean "percentage change", see the `ALIGN_PERCENT_CHANGE` aligner instead.
ALIGN_INTERPOLATE = 3
Align by interpolating between adjacent points around the alignment period boundary. This aligner is valid for `GAUGE` metrics with numeric values. The `value_type` of the aligned result is the same as the `value_type` of the input.
ALIGN_NEXT_OLDER = 4
Align by moving the most recent data point before the end of the alignment period to the boundary at the end of the alignment period. This aligner is valid for `GAUGE` metrics. The `value_type` of the aligned result is the same as the `value_type` of the input.
ALIGN_MIN = 10
Align the time series by returning the minimum value in each alignment period. This aligner is valid for `GAUGE` and `DELTA` metrics with numeric values. The `value_type` of the aligned result is the same as the `value_type` of the input.
ALIGN_MAX = 11
Align the time series by returning the maximum value in each alignment period. This aligner is valid for `GAUGE` and `DELTA` metrics with numeric values. The `value_type` of the aligned result is the same as the `value_type` of the input.
ALIGN_MEAN = 12
Align the time series by returning the mean value in each alignment period. This aligner is valid for `GAUGE` and `DELTA` metrics with numeric values. The `value_type` of the aligned result is `DOUBLE`.
ALIGN_COUNT = 13
Align the time series by returning the number of values in each alignment period. This aligner is valid for `GAUGE` and `DELTA` metrics with numeric or Boolean values. The `value_type` of the aligned result is `INT64`.
ALIGN_SUM = 14
Align the time series by returning the sum of the values in each alignment period. This aligner is valid for `GAUGE` and `DELTA` metrics with numeric and distribution values. The `value_type` of the aligned result is the same as the `value_type` of the input.
ALIGN_STDDEV = 15
Align the time series by returning the standard deviation of the values in each alignment period. This aligner is valid for `GAUGE` and `DELTA` metrics with numeric values. The `value_type` of the output is `DOUBLE`.
ALIGN_COUNT_TRUE = 16
Align the time series by returning the number of `True` values in each alignment period. This aligner is valid for `GAUGE` metrics with Boolean values. The `value_type` of the output is `INT64`.
ALIGN_COUNT_FALSE = 24
Align the time series by returning the number of `False` values in each alignment period. This aligner is valid for `GAUGE` metrics with Boolean values. The `value_type` of the output is `INT64`.
ALIGN_FRACTION_TRUE = 17
Align the time series by returning the ratio of the number of `True` values to the total number of values in each alignment period. This aligner is valid for `GAUGE` metrics with Boolean values. The output value is in the range [0.0, 1.0] and has `value_type` `DOUBLE`.
ALIGN_PERCENTILE_99 = 18
Align the time series by using [percentile aggregation](https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 99th percentile of all data points in the period. This aligner is valid for `GAUGE` and `DELTA` metrics with distribution values. The output is a `GAUGE` metric with `value_type` `DOUBLE`.
ALIGN_PERCENTILE_95 = 19
Align the time series by using [percentile aggregation](https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 95th percentile of all data points in the period. This aligner is valid for `GAUGE` and `DELTA` metrics with distribution values. The output is a `GAUGE` metric with `value_type` `DOUBLE`.
ALIGN_PERCENTILE_50 = 20
Align the time series by using [percentile aggregation](https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 50th percentile of all data points in the period. This aligner is valid for `GAUGE` and `DELTA` metrics with distribution values. The output is a `GAUGE` metric with `value_type` `DOUBLE`.
ALIGN_PERCENTILE_05 = 21
Align the time series by using [percentile aggregation](https://en.wikipedia.org/wiki/Percentile). The resulting data point in each alignment period is the 5th percentile of all data points in the period. This aligner is valid for `GAUGE` and `DELTA` metrics with distribution values. The output is a `GAUGE` metric with `value_type` `DOUBLE`.
ALIGN_PERCENT_CHANGE = 23
Align and convert to a percentage change. This aligner is valid for `GAUGE` and `DELTA` metrics with numeric values. This alignment returns `((current - previous)/previous) * 100`, where the value of `previous` is determined based on the `alignment_period`. If the values of `current` and `previous` are both 0, then the returned value is 0. If only `previous` is 0, the returned value is infinity. A 10-minute moving mean is computed at each point of the alignment period prior to the above calculation to smooth the metric and prevent false positives from very short-lived spikes. The moving mean is only applicable for data whose values are `>= 0`. Any values `< 0` are treated as a missing datapoint, and are ignored. 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`.
A Reducer operation describes how to aggregate data points from multiple time series into a single time series, where the value of each data point in the resulting series is a function of all the already aligned values in the input time series.
Used in:
REDUCE_NONE = 0
No cross-time series reduction. The output of the `Aligner` is returned.
REDUCE_MEAN = 1
Reduce by computing the mean value across time series for each alignment period. This reducer is valid for [DELTA][google.api.MetricDescriptor.MetricKind.DELTA] and [GAUGE][google.api.MetricDescriptor.MetricKind.GAUGE] metrics with numeric or distribution values. The `value_type` of the output is [DOUBLE][google.api.MetricDescriptor.ValueType.DOUBLE].
REDUCE_MIN = 2
Reduce by computing the minimum value 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 = 3
Reduce by computing the maximum value 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 = 4
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 = 5
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 = 6
Reduce by computing the number 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 = 7
Reduce by computing the number 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 = 15
Reduce by computing the number 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 = 8
Reduce by computing the ratio of the number of `True`-valued data points to the total number of data points for each alignment period. This reducer is valid for `DELTA` and `GAUGE` metrics of Boolean `value_type`. The output value is in the range [0.0, 1.0] and has `value_type` `DOUBLE`.
REDUCE_PERCENTILE_99 = 9
Reduce by computing the [99th percentile](https://en.wikipedia.org/wiki/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 = 10
Reduce by computing the [95th percentile](https://en.wikipedia.org/wiki/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 = 11
Reduce by computing the [50th percentile](https://en.wikipedia.org/wiki/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 = 12
Reduce by computing the [5th percentile](https://en.wikipedia.org/wiki/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`.
message
alertchart.proto:31A chart that displays alert policy data.
Used in:
string name = 1
Required. The resource name of the alert policy. The format is: projects/[PROJECT_ID_OR_NUMBER]/alertPolicies/[ALERT_POLICY_ID]
message
xychart.proto:147Options to control visual rendering of a chart.
Used in:
ChartOptions.Mode mode = 1
The chart mode.
Chart mode options.
Used in:
MODE_UNSPECIFIED = 0
Mode is unspecified. The view will default to `COLOR`.
COLOR = 1
The chart distinguishes data series using different color. Line colors may get reused when there are many lines in the chart.
X_RAY = 2
The chart uses the Stackdriver x-ray mode, in which each data set is plotted using the same semi-transparent color.
STATS = 3
The chart displays statistics such as average, median, 95th percentile, and more.
message
collapsible_group.proto:29A widget that groups the other widgets. All widgets that are within the area spanned by the grouping widget are considered member widgets.
Used in:
bool collapsed = 1
The collapsed state of the widget on first page load.
message
layouts.proto:97A simplified layout that divides the available space into vertical columns and arranges a set of widgets vertically in each column.
Used in:
repeated columns = 1
The columns of content to display.
message
layouts.proto:99Defines the layout properties and content for a column.
Used in:
int64 weight = 1
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.
repeated widgets = 2
The display widgets arranged vertically in this column.
message
dashboard.proto:34A Google Stackdriver dashboard. Dashboards define the content and layout of pages in the Stackdriver web application.
Used as response type in: DashboardsService.CreateDashboard, DashboardsService.GetDashboard, DashboardsService.UpdateDashboard
Used as field type in: , ,
string name = 1
Identifier. The resource name of the dashboard.
string display_name = 2
Required. The mutable, human-readable name.
string etag = 4
`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.
oneof layout
A dashboard's root container element that defines the layout style.
grid_layout = 5
Content is arranged with a basic layout that re-flows a simple list of informational elements like widgets or tiles.
mosaic_layout = 6
The content is arranged as a grid of tiles, with each content widget occupying one or more grid blocks.
row_layout = 8
The content is divided into equally spaced rows and the widgets are arranged horizontally.
column_layout = 9
The content is divided into equally spaced columns and the widgets are arranged vertically.
repeated dashboard_filters = 11
Filters to reduce the amount of data charted based on the filter criteria.
map<string, string> labels = 12
Labels applied to the dashboard
message
dashboard_filter.proto:30A filter to reduce the amount of data charted in relevant widgets.
Used in:
string label_key = 1
Required. The key for the label
string template_variable = 3
The placeholder text that can be referenced in a filter string or MQL query. If omitted, the dashboard filter will be applied to all relevant widgets in the dashboard.
oneof default_value
The default value used in the filter comparison
string string_value = 4
A variable-length string value.
DashboardFilter.FilterType filter_type = 5
The specified filter type
The type for the dashboard filter
Used in:
FILTER_TYPE_UNSPECIFIED = 0
Filter type is unspecified. This is not valid in a well-formed request.
RESOURCE_LABEL = 1
Filter on a resource label value
METRIC_LABEL = 2
Filter on a metrics label value
USER_METADATA_LABEL = 3
Filter on a user metadata label value
SYSTEM_METADATA_LABEL = 4
Filter on a system metadata label value
GROUP = 5
Filter on a group id
message
error_reporting_panel.proto:27A widget that displays a list of error groups.
Used in:
repeated string project_names = 1
The resource name of the Google Cloud Platform project. Written as `projects/{projectID}` or `projects/{projectNumber}`, where `{projectID}` and `{projectNumber}` can be found in the [Google Cloud console](https://support.google.com/cloud/answer/6158840). Examples: `projects/my-project-123`, `projects/5551234`.
repeated string services = 2
An identifier of the service, such as the name of the executable, job, or Google App Engine service name. This field is expected to have a low number of values that are relatively stable over time, as opposed to `version`, which can be changed whenever new code is deployed. Contains the service name for error reports extracted from Google App Engine logs or `default` if the App Engine default service is used.
repeated string versions = 3
Represents the source code version that the developer provided, which could represent a version label or a Git SHA-1 hash, for example. For App Engine standard environment, the version is set to the version of the app.
message
layouts.proto:31A basic layout divides the available space into vertical columns of equal width and arranges a list of widgets using a row-first strategy.
Used in:
int64 columns = 1
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.
repeated widgets = 2
The informational elements that are arranged into the columns row-first.
message
incident_list.proto:31A widget that displays a list of incidents
Used in:
repeated monitored_resources = 1
Optional. The monitored resource for which incidents are listed. The resource doesn't need to be fully specified. That is, you can specify the resource type but not the values of the resource labels. The resource type and labels are used for filtering.
repeated string policy_names = 2
Optional. A list of alert policy names to filter the incident list by. Don't include the project ID prefix in the policy name. For example, use `alertPolicies/utilization`.
message
logs_panel.proto:28A widget that displays a stream of log.
Used in:
string filter = 1
A filter that chooses which log entries to return. See [Advanced Logs Queries](https://cloud.google.com/logging/docs/view/advanced-queries). Only log entries that match the filter are returned. An empty filter matches all log entries.
repeated string resource_names = 2
The names of logging resources to collect logs for. Currently only projects are supported. If empty, the widget will default to the host project.
message
layouts.proto:43A mosaic layout divides the available space into a grid of blocks, and overlays the grid with tiles. Unlike `GridLayout`, tiles may span multiple grid blocks and can be placed at arbitrary locations in the grid.
Used in:
int32 columns = 1
The number of columns in the mosaic grid. The number of columns must be between 1 and 12, inclusive.
repeated tiles = 3
The tiles to display.
message
layouts.proto:46A single tile in the mosaic. The placement and size of the tile are configurable.
Used in:
int32 x_pos = 1
The zero-indexed position of the tile in grid blocks relative to the left edge of the grid. Tiles must be contained within the specified number of columns. `x_pos` cannot be negative.
int32 y_pos = 2
The zero-indexed position of the tile in grid blocks relative to the top edge of the grid. `y_pos` cannot be negative.
int32 width = 3
The width of the tile, measured in grid blocks. Tiles must have a minimum width of 1.
int32 height = 4
The height of the tile, measured in grid blocks. Tiles must have a minimum height of 1.
optional widget = 5
The informational widget contained in the tile. For example an `XyChart`.
message
common.proto:383Describes a ranking-based time series filter. Each input time series is ranked with an aligner. The filter will allow up to `num_time_series` time series to pass through it, selecting them based on the relative ranking. For example, if `ranking_method` is `METHOD_MEAN`,`direction` is `BOTTOM`, and `num_time_series` is 3, then the 3 times series with the lowest mean values will pass through the filter.
Used in: ,
PickTimeSeriesFilter.Method ranking_method = 1
`ranking_method` is applied to each time series independently to produce the value which will be used to compare the time series to other time series.
int32 num_time_series = 2
How many time series to allow to pass through the filter.
PickTimeSeriesFilter.Direction direction = 3
How to use the ranking to select time series that pass through the filter.
optional interval = 4
Select the top N streams/time series within this time interval
Describes the ranking directions.
Used in:
DIRECTION_UNSPECIFIED = 0
Not allowed. You must specify a different `Direction` if you specify a `PickTimeSeriesFilter`.
TOP = 1
Pass the highest `num_time_series` ranking inputs.
BOTTOM = 2
Pass the lowest `num_time_series` ranking inputs.
The value reducers that can be applied to a `PickTimeSeriesFilter`.
Used in:
METHOD_UNSPECIFIED = 0
Not allowed. You must specify a different `Method` if you specify a `PickTimeSeriesFilter`.
METHOD_MEAN = 1
Select the mean of all values.
METHOD_MAX = 2
Select the maximum value.
METHOD_MIN = 3
Select the minimum value.
METHOD_SUM = 4
Compute the sum of all values.
METHOD_LATEST = 5
Select the most recent value.
message
piechart.proto:32A widget that displays timeseries data as a pie or a donut.
Used in:
repeated data_sets = 1
Required. The queries for the chart's data.
PieChart.PieChartType chart_type = 2
Required. Indicates the visualization type for the PieChart.
bool show_labels = 4
Optional. Indicates whether or not the pie chart should show slices' labels
message
piechart.proto:34Groups a time series query definition.
Used in:
optional time_series_query = 1
Required. The query for the PieChart. See, `google.monitoring.dashboard.v1.TimeSeriesQuery`.
string slice_name_template = 2
Optional. A template for the name of the slice. This name will be displayed in the legend and the tooltip of the pie chart. It replaces the auto-generated names for the slices. For example, if the template is set to `${resource.labels.zone}`, the zone's value will be used for the name instead of the default name.
optional min_alignment_period = 3
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.
Types for the pie chart.
Used in:
PIE_CHART_TYPE_UNSPECIFIED = 0
The zero value. No type specified. Do not use.
PIE = 1
A Pie type PieChart.
DONUT = 2
Similar to PIE, but the DONUT type PieChart has a hole in the middle.
message
layouts.proto:78A simplified layout that divides the available space into rows and arranges a set of widgets horizontally in each row.
Used in:
repeated rows = 1
The rows of content to display.
message
layouts.proto:80Defines the layout properties and content for a row.
Used in:
int64 weight = 1
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.
repeated widgets = 2
The display widgets arranged horizontally in this row.
message
scorecard.proto:34A widget showing the latest value of a metric, and how this value relates to one or more thresholds.
Used in:
optional time_series_query = 1
Required. Fields for querying time series data from the Stackdriver metrics API.
oneof data_view
Defines the optional additional chart shown on the scorecard. If neither is included - then a default scorecard is shown.
gauge_view = 4
Will cause the scorecard to show a gauge chart.
spark_chart_view = 5
Will cause the scorecard to show a spark chart.
blank_view = 7
Will cause the `Scorecard` to show only the value, with no indicator to its value relative to its thresholds.
repeated thresholds = 6
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.
message
scorecard.proto:38A 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).
Used in:
double lower_bound = 1
The lower bound for this gauge chart. The value of the chart should always be greater than or equal to this.
double upper_bound = 2
The upper bound for this gauge chart. The value of the chart should always be less than or equal to this.
message
scorecard.proto:52A 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.
Used in:
SparkChartType spark_chart_type = 1
Required. The type of sparkchart to show in this chartView.
optional min_alignment_period = 2
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.
message
section_header.proto:29A widget that defines a new section header. Sections populate a table of contents and allow easier navigation of long-form content.
Used in:
string subtitle = 1
The subtitle of the section
bool divider_below = 2
Whether to insert a divider below the section in the table of contents
message
single_view_group.proto:30A widget that groups the other widgets by using a dropdown menu. All widgets that are within the area spanned by the grouping widget are considered member widgets.
Used in:
(message has no fields)
Defines the possible types of spark chart supported by the `Scorecard`.
Used in:
SPARK_CHART_TYPE_UNSPECIFIED = 0
Not allowed in well-formed requests.
SPARK_LINE = 1
The sparkline will be rendered as a small line chart.
SPARK_BAR = 2
The sparkbar will be rendered as a small bar chart.
message
common.proto:437A filter that ranks streams based on their statistical relation to other streams in a request. Note: This field is deprecated and completely ignored by the API.
Used in: ,
StatisticalTimeSeriesFilter.Method ranking_method = 1
`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.
int32 num_time_series = 2
How many time series to output.
The filter methods that can be applied to a stream.
Used in:
METHOD_UNSPECIFIED = 0
Not allowed in well-formed requests.
METHOD_CLUSTER_OUTLIER = 1
Compute the outlier score of each stream.
message
table_display_options.proto:30Table display options that can be reused.
Used in:
repeated string shown_columns = 1
Optional. This field is unused and has been replaced by TimeSeriesTable.column_settings
message
text.proto:28A widget that displays textual content.
Used in:
string content = 1
The text content to be displayed.
Text.Format format = 2
How the text content is formatted.
optional style = 3
How the text is styled
The format type of the text content.
Used in:
FORMAT_UNSPECIFIED = 0
Format is unspecified. Defaults to MARKDOWN.
MARKDOWN = 1
The text contains Markdown formatting.
RAW = 2
The text contains no special formatting.
message
text.proto:42Properties that determine how the title and content are styled
Used in:
string background_color = 1
The background color as a hex string. "#RRGGBB" or "#RGB"
string text_color = 2
The text color as a hex string. "#RRGGBB" or "#RGB"
TextStyle.HorizontalAlignment horizontal_alignment = 3
The horizontal alignment of both the title and content
TextStyle.VerticalAlignment vertical_alignment = 4
The vertical alignment of both the title and content
TextStyle.PaddingSize padding = 5
The amount of padding around the widget
TextStyle.FontSize font_size = 6
Font sizes for both the title and content. The title will still be larger relative to the content.
TextStyle.PointerLocation pointer_location = 7
The pointer location for this widget (also sometimes called a "tail")
Specifies a font size for the title and content of a text widget
Used in:
FONT_SIZE_UNSPECIFIED = 0
No font size specified, will default to FS_LARGE
FS_EXTRA_SMALL = 1
Extra small font size
FS_SMALL = 2
Small font size
FS_MEDIUM = 3
Medium font size
FS_LARGE = 4
Large font size
FS_EXTRA_LARGE = 5
Extra large font size
The horizontal alignment of both the title and content on a text widget
Used in:
HORIZONTAL_ALIGNMENT_UNSPECIFIED = 0
No horizontal alignment specified, will default to H_LEFT
H_LEFT = 1
Left-align
H_CENTER = 2
Center-align
H_RIGHT = 3
Right-align
Specifies padding size around a text widget
Used in:
PADDING_SIZE_UNSPECIFIED = 0
No padding size specified, will default to P_EXTRA_SMALL
P_EXTRA_SMALL = 1
Extra small padding
P_SMALL = 2
Small padding
P_MEDIUM = 3
Medium padding
P_LARGE = 4
Large padding
P_EXTRA_LARGE = 5
Extra large padding
Specifies where a visual pointer is placed on a text widget (also sometimes called a "tail")
Used in:
POINTER_LOCATION_UNSPECIFIED = 0
No visual pointer
PL_TOP = 1
Placed in the middle of the top of the widget
PL_RIGHT = 2
Placed in the middle of the right side of the widget
PL_BOTTOM = 3
Placed in the middle of the bottom of the widget
PL_LEFT = 4
Placed in the middle of the left side of the widget
PL_TOP_LEFT = 5
Placed on the left side of the top of the widget
PL_TOP_RIGHT = 6
Placed on the right side of the top of the widget
PL_RIGHT_TOP = 7
Placed on the top of the right side of the widget
PL_RIGHT_BOTTOM = 8
Placed on the bottom of the right side of the widget
PL_BOTTOM_RIGHT = 9
Placed on the right side of the bottom of the widget
PL_BOTTOM_LEFT = 10
Placed on the left side of the bottom of the widget
PL_LEFT_BOTTOM = 11
Placed on the bottom of the left side of the widget
PL_LEFT_TOP = 12
Placed on the top of the left side of the widget
The vertical alignment of both the title and content on a text widget
Used in:
VERTICAL_ALIGNMENT_UNSPECIFIED = 0
No vertical alignment specified, will default to V_TOP
V_TOP = 1
Top-align
V_CENTER = 2
Center-align
V_BOTTOM = 3
Bottom-align
message
metrics.proto:136Defines a threshold for categorizing time series values.
Used in: ,
string label = 1
A label for the threshold.
double value = 2
The value of the threshold. The value should be defined in the native scale of the metric.
Threshold.Color color = 3
The state color for this threshold. Color is not allowed in a XyChart.
Threshold.Direction direction = 4
The direction for the current threshold. Direction is not allowed in a XyChart.
Threshold.TargetAxis target_axis = 5
The target axis to use for plotting the threshold. Target axis is not allowed in a Scorecard.
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.
Used in:
COLOR_UNSPECIFIED = 0
Color is unspecified. Not allowed in well-formed requests.
YELLOW = 4
Crossing the threshold is "concerning" behavior.
RED = 6
Crossing the threshold is "emergency" behavior.
Whether the threshold is considered crossed by an actual value above or below its threshold value.
Used in:
DIRECTION_UNSPECIFIED = 0
Not allowed in well-formed requests.
ABOVE = 1
The threshold will be considered crossed if the actual value is above the threshold value.
BELOW = 2
The threshold will be considered crossed if the actual value is below the threshold value.
An axis identifier.
Used in:
TARGET_AXIS_UNSPECIFIED = 0
The target axis was not specified. Defaults to Y1.
Y1 = 1
The y_axis (the right axis of chart).
Y2 = 2
The y2_axis (the left axis of chart).
message
metrics.proto:69A filter that defines a subset of time series data that is displayed in a widget. Time series data is fetched using the [`ListTimeSeries`](https://cloud.google.com/monitoring/api/ref_v3/rest/v3/projects.timeSeries/list) method.
Used in:
string filter = 1
Required. The [monitoring filter](https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
optional aggregation = 2
By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
optional secondary_aggregation = 3
Apply a second aggregation after `aggregation` is applied.
oneof output_filter
Selects an optional time series filter.
pick_time_series_filter = 4
Ranking based time series filter.
statistical_time_series_filter = 5
Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.
message
metrics.proto:98A 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.
Used in:
optional numerator = 1
The numerator of the ratio.
optional denominator = 2
The denominator of the ratio.
optional secondary_aggregation = 3
Apply a second aggregation after the ratio is computed.
oneof output_filter
Selects an optional filter that is applied to the time series after computing the ratio.
pick_time_series_filter = 4
Ranking based time series filter.
statistical_time_series_filter = 5
Statistics based time series filter. Note: This field is deprecated and completely ignored by the API.
message
metrics.proto:101Describes a query to build the numerator or denominator of a TimeSeriesFilterRatio.
Used in:
string filter = 1
Required. The [monitoring filter](https://cloud.google.com/monitoring/api/v3/filters) that identifies the metric types, resources, and projects to query.
optional aggregation = 2
By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data.
message
metrics.proto:32TimeSeriesQuery collects the set of supported methods for querying time series data from the Stackdriver metrics API.
Used in: , , ,
oneof source
Parameters needed to obtain data for the chart.
time_series_filter = 1
Filter parameters to fetch time series.
time_series_filter_ratio = 2
Parameters to fetch a ratio between two time series filters.
string time_series_query_language = 3
A query used to fetch time series with MQL.
string prometheus_query = 6
A query used to fetch time series with PromQL.
string unit_override = 5
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`](https://cloud.google.com/monitoring/api/ref_v3/rest/v3/projects.metricDescriptors) field in `MetricDescriptor`.
bool output_full_duration = 7
Optional. If set, Cloud Monitoring will treat the full query duration as the alignment period so that there will be only 1 output value. *Note: This could override the configured alignment period except for the cases where a series of data points are expected, like - XyChart - Scorecard's spark chart
message
table.proto:33A table that displays time series data.
Used in:
repeated data_sets = 1
Required. The data displayed in this table.
TimeSeriesTable.MetricVisualization metric_visualization = 2
Optional. Store rendering strategy
repeated column_settings = 4
Optional. The list of the persistent column settings for the table.
message
table.proto:74The persistent settings for a table's columns.
Used in:
string column = 1
Required. The id of the column.
bool visible = 2
Required. Whether the column should be visible on page load.
Enum for metric metric_visualization
Used in:
METRIC_VISUALIZATION_UNSPECIFIED = 0
Unspecified state
NUMBER = 1
Default text rendering
BAR = 2
Horizontal bar rendering
message
table.proto:35Groups a time series query definition with table options.
Used in:
optional time_series_query = 1
Required. Fields for querying time series data from the Stackdriver metrics API.
string table_template = 2
Optional. 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 i.e. "${resource.labels.project_id}."
optional min_alignment_period = 3
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.
optional table_display_options = 4
Optional. Table display options for configuring how the table is rendered.
message
widget.proto:44Widget contains a single dashboard component and configuration of how to present the component in the dashboard.
Used in: , , ,
string title = 1
Optional. The title of the widget.
oneof content
Content defines the component used to populate the widget.
xy_chart = 2
A chart of time series data.
scorecard = 3
A scorecard summarizing time series data.
text = 4
A raw string or markdown displaying textual content.
blank = 5
A blank space.
alert_chart = 7
A chart of alert policy data.
time_series_table = 8
A widget that displays time series data in a tabular format.
collapsible_group = 9
A widget that groups the other widgets. All widgets that are within the area spanned by the grouping widget are considered member widgets.
logs_panel = 10
A widget that shows a stream of logs.
incident_list = 12
A widget that shows list of incidents.
pie_chart = 14
A widget that displays timeseries data as a pie chart.
error_reporting_panel = 19
A widget that displays a list of error groups.
section_header = 21
A widget that defines a section header for easier navigation of the dashboard.
single_view_group = 22
A widget that groups the other widgets by using a dropdown menu.
string id = 17
Optional. The widget id. Ids may be made up of alphanumerics, dashes and underscores. Widget ids are optional.
message
xychart.proto:32A chart that displays data on a 2D (X and Y axes) plane.
Used in:
repeated data_sets = 1
Required. The data displayed in this chart.
optional timeshift_duration = 4
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.
repeated thresholds = 5
Threshold lines drawn horizontally across the chart.
optional x_axis = 6
The properties applied to the x-axis.
optional y_axis = 7
The properties applied to the y-axis.
optional y2_axis = 9
The properties applied to the y2-axis.
optional chart_options = 8
Display options for the chart.
message
xychart.proto:100A chart axis.
Used in:
string label = 1
The label of the axis.
Axis.Scale scale = 2
The axis scale. By default, a linear scale is used.
Types of scales used in axes.
Used in:
SCALE_UNSPECIFIED = 0
Scale is unspecified. The view will default to `LINEAR`.
LINEAR = 1
Linear scale.
LOG10 = 2
Logarithmic scale (base 10).
message
xychart.proto:34Groups a time series query definition with charting options.
Used in:
optional time_series_query = 1
Required. Fields for querying time series data from the Stackdriver metrics API.
DataSet.PlotType plot_type = 2
How this data should be plotted on the chart.
string legend_template = 3
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.
optional min_alignment_period = 4
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.
DataSet.TargetAxis target_axis = 5
Optional. The target axis to use for plotting the metric.
The types of plotting strategies for data sets.
Used in:
PLOT_TYPE_UNSPECIFIED = 0
Plot type is unspecified. The view will default to `LINE`.
LINE = 1
The data is plotted as a set of lines (one line per series).
STACKED_AREA = 2
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 = 3
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 = 4
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.
An axis identifier.
Used in:
TARGET_AXIS_UNSPECIFIED = 0
The target axis was not specified. Defaults to Y1.
Y1 = 1
The y_axis (the right axis of chart).
Y2 = 2
The y2_axis (the left axis of chart).