 HTTP request
 Path parameters
 Query parameters
 Request body
 Response body
 Authorization
 Aggregation
 Aligner
 Reducer
 TimeSeriesView
Lists time series that match a filter. This method does not require a Stackdriver account.
HTTP request
GET https://monitoring.googleapis.com/v3/{name}/timeSeries
Path parameters
Parameters  

name 
The project on which to execute the request. The format is "projects/{project_id_or_number}". 
Query parameters
Parameters  

filter 
A monitoring filter that specifies which time series should be returned. The filter must specify a single metric type, and can additionally specify metric labels and other information. For example:

interval 
The time interval for which results should be returned. Only time series that contain data points in the specified interval are included in the response. 
aggregation 
By default, the raw time series data is returned. Use this field to combine multiple time series for different views of the data. 
orderBy 
Specifies the order in which the points of the time series should be returned. By default, results are not ordered. Currently, this field must be left blank. 
view 
Specifies which information is returned about the time series. 
pageSize 
A positive number that is the maximum number of results to return. When 
pageToken 
If this field is not empty then it must contain the 
Request body
The request body must be empty.
Response body
If successful, the response body contains data with the following structure:
The timeSeries.list
response.
JSON representation  

{
"timeSeries": [
{
object( 
Fields  

timeSeries[] 
One or more time series that match the filter included in the request. 
nextPageToken 
If there are more results than have been returned, then this field is set to a nonempty value. To see the additional results, use that value as 
Authorization
Requires one of the following OAuth scopes:
https://www.googleapis.com/auth/cloudplatform
https://www.googleapis.com/auth/monitoring
https://www.googleapis.com/auth/monitoring.read
For more information, see the Auth Guide.
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 (alignmentPeriod
and perSeriesAligner
) followed by an optional reduction step of the data across the aligned time series (crossSeriesReducer
and `groupByFields). For more details, see Aggregation.
JSON representation  

{ "alignmentPeriod": string, "perSeriesAligner": enum( 
Fields  

alignmentPeriod 
The alignment period for per A duration in seconds with up to nine fractional digits, terminated by ' 
perSeriesAligner 
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 crosstime series reduction. If 
crossSeriesReducer 
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 crosstime series reduction. If 
groupByFields[] 
The set of fields to preserve when 
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 crosstime 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 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. 
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 Truevalued 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 Truevalued 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 . 
Reducer
A Reducer describes how to aggregate data points from multiple time series into a single time series.
Enums  

REDUCE_NONE 
No crosstime 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 Truevalued 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 Truevalued 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 
TimeSeriesView
Controls which fields are returned by timeSeries.list
.
Enums  

FULL 
Returns the identity of the metric(s), the time series, and the time series data. 
HEADERS 
Returns the identity of the metric and the time series resource, but not the time series data. 