Add stackdriver input plugin (#5406)
This commit is contained in:
Daniel Nelson
GitHub
parent
463df273ee
commit
843d842d02
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@ -253,6 +253,7 @@ For documentation on the latest development code see the [documentation index][d
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* [socket_listener](./plugins/inputs/socket_listener)
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* [socket_listener](./plugins/inputs/socket_listener)
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* [solr](./plugins/inputs/solr)
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* [solr](./plugins/inputs/solr)
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* [sql server](./plugins/inputs/sqlserver) (microsoft)
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* [sql server](./plugins/inputs/sqlserver) (microsoft)
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* [stackdriver](./plugins/inputs/stackdriver)
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* [statsd](./plugins/inputs/statsd)
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* [statsd](./plugins/inputs/statsd)
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* [swap](./plugins/inputs/swap)
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* [swap](./plugins/inputs/swap)
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* [syslog](./plugins/inputs/syslog)
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* [syslog](./plugins/inputs/syslog)
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@ -0,0 +1,86 @@
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package metric
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import (
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"hash/fnv"
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"io"
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"sort"
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"strconv"
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"time"
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"github.com/influxdata/telegraf"
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)
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// NewSeriesGrouper returns a type that can be used to group fields by series
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// and time, so that fields which share these values will be combined into a
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// single telegraf.Metric.
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//
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// This is useful to build telegraf.Metric's when all fields for a series are
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// not available at once.
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//
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// ex:
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// - cpu,host=localhost usage_time=42
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// - cpu,host=localhost idle_time=42
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// + cpu,host=localhost idle_time=42,usage_time=42
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func NewSeriesGrouper() *SeriesGrouper {
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return &SeriesGrouper{
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metrics: make(map[uint64]telegraf.Metric),
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ordered: []telegraf.Metric{},
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}
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}
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type SeriesGrouper struct {
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metrics map[uint64]telegraf.Metric
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ordered []telegraf.Metric
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}
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// Add adds a field key and value to the series.
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func (g *SeriesGrouper) Add(
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measurement string,
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tags map[string]string,
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tm time.Time,
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field string,
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fieldValue interface{},
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) error {
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var err error
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id := groupID(measurement, tags, tm)
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metric := g.metrics[id]
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if metric == nil {
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metric, err = New(measurement, tags, map[string]interface{}{field: fieldValue}, tm)
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if err != nil {
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return err
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}
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g.metrics[id] = metric
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g.ordered = append(g.ordered, metric)
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} else {
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metric.AddField(field, fieldValue)
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}
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return nil
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}
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// Metrics returns the metrics grouped by series and time.
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func (g *SeriesGrouper) Metrics() []telegraf.Metric {
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return g.ordered
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}
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func groupID(measurement string, tags map[string]string, tm time.Time) uint64 {
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h := fnv.New64a()
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h.Write([]byte(measurement))
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h.Write([]byte("\n"))
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taglist := make([]*telegraf.Tag, 0, len(tags))
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for k, v := range tags {
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taglist = append(taglist,
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&telegraf.Tag{Key: k, Value: v})
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}
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sort.Slice(taglist, func(i, j int) bool { return taglist[i].Key < taglist[j].Key })
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for _, tag := range taglist {
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h.Write([]byte(tag.Key))
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h.Write([]byte("\n"))
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h.Write([]byte(tag.Value))
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h.Write([]byte("\n"))
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}
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h.Write([]byte("\n"))
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io.WriteString(h, strconv.FormatInt(tm.UnixNano(), 10))
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return h.Sum64()
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}
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@ -122,6 +122,7 @@ import (
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_ "github.com/influxdata/telegraf/plugins/inputs/socket_listener"
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_ "github.com/influxdata/telegraf/plugins/inputs/socket_listener"
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_ "github.com/influxdata/telegraf/plugins/inputs/solr"
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_ "github.com/influxdata/telegraf/plugins/inputs/solr"
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_ "github.com/influxdata/telegraf/plugins/inputs/sqlserver"
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_ "github.com/influxdata/telegraf/plugins/inputs/sqlserver"
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_ "github.com/influxdata/telegraf/plugins/inputs/stackdriver"
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_ "github.com/influxdata/telegraf/plugins/inputs/statsd"
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_ "github.com/influxdata/telegraf/plugins/inputs/statsd"
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_ "github.com/influxdata/telegraf/plugins/inputs/swap"
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_ "github.com/influxdata/telegraf/plugins/inputs/swap"
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_ "github.com/influxdata/telegraf/plugins/inputs/syslog"
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_ "github.com/influxdata/telegraf/plugins/inputs/syslog"
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@ -0,0 +1,161 @@
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# Stackdriver Input Plugin
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Stackdriver gathers metrics from the [Stackdriver Monitoring API][stackdriver].
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This plugin accesses APIs which are [chargeable][pricing]; you might incur
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costs.
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### Configuration
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```toml
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[[inputs.stackdriver]]
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## GCP Project
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project = "erudite-bloom-151019"
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## Include timeseries that start with the given metric type.
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metric_type_prefix_include = [
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"compute.googleapis.com/",
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]
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## Exclude timeseries that start with the given metric type.
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# metric_type_prefix_exclude = []
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## Most metrics are updated no more than once per minute; it is recommended
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## to override the agent level interval with a value of 1m or greater.
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interval = "1m"
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## Maximum number of API calls to make per second. The quota for accounts
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## varies, it can be viewed on the API dashboard:
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## https://cloud.google.com/monitoring/quotas#quotas_and_limits
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# rate_limit = 14
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## The delay and window options control the number of points selected on
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## each gather. When set, metrics are gathered between:
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## start: now() - delay - window
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## end: now() - delay
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#
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## Collection delay; if set too low metrics may not yet be available.
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# delay = "5m"
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#
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## If unset, the window will start at 1m and be updated dynamically to span
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## the time between calls (approximately the length of the plugin interval).
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# window = "1m"
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## TTL for cached list of metric types. This is the maximum amount of time
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## it may take to discover new metrics.
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# cache_ttl = "1h"
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## If true, raw bucket counts are collected for distribution value types.
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## For a more lightweight collection, you may wish to disable and use
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## distribution_aggregation_aligners instead.
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# gather_raw_distribution_buckets = true
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## Aggregate functions to be used for metrics whose value type is
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## distribution. These aggregate values are recorded in in addition to raw
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## bucket counts; if they are enabled.
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##
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## For a list of aligner strings see:
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## https://cloud.google.com/monitoring/api/ref_v3/rpc/google.monitoring.v3#aligner
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# distribution_aggregation_aligners = [
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# "ALIGN_PERCENTILE_99",
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# "ALIGN_PERCENTILE_95",
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# "ALIGN_PERCENTILE_50",
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# ]
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## Filters can be added to reduce the number of time series matched. All
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## functions are supported: starts_with, ends_with, has_substring, and
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## one_of. Only the '=' operator is supported.
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##
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## The logical operators when combining filters are defined statically using
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## the following values:
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## filter ::= <resource_labels> {AND <metric_labels>}
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## resource_labels ::= <resource_labels> {OR <resource_label>}
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## metric_labels ::= <metric_labels> {OR <metric_label>}
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##
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## For more details, see https://cloud.google.com/monitoring/api/v3/filters
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#
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## Resource labels refine the time series selection with the following expression:
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## resource.labels.<key> = <value>
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# [[inputs.stackdriver.filter.resource_labels]]
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# key = "instance_name"
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# value = 'starts_with("localhost")'
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#
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## Metric labels refine the time series selection with the following expression:
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## metric.labels.<key> = <value>
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# [[inputs.stackdriver.filter.metric_labels]]
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# key = "device_name"
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# value = 'one_of("sda", "sdb")'
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```
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#### Authentication
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It is recommended to use a service account to authenticate with the
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Stackdriver Monitoring API. [Getting Started with Authentication][auth].
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### Metrics
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Metrics are created using one of there patterns depending on if the value type
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is a scalar value, raw distribution buckets, or aligned bucket values.
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In all cases, the Stackdriver metric type is split on the last component into
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the measurement and field:
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```
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compute.googleapis.com/instance/disk/read_bytes_count
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└────────── measurement ─────────┘ └── field ───┘
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```
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**Scalar Values:**
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- measurement
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- tags:
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- resource_labels
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- metric_labels
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- fields:
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- field
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**Distributions:**
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Distributions are represented by a set of fields along with the bucket values
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tagged with the bucket boundary. Buckets are cumulative: each bucket
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represents the total number of items less than the `lt` tag.
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- measurement
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- tags:
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- resource_labels
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- metric_labels
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- fields:
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- field_count
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- field_mean
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- field_sum_of_squared_deviation
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- field_range_min
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- field_range_max
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+ measurement
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- tags:
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- resource_labels
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- metric_labels
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- lt (less than)
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- fields:
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- field_bucket
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**Aligned Aggregations:**
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- measurement
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- tags:
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- resource_labels
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- metric_labels
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- fields:
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- field_alignment_function
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### Troubleshooting
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When Telegraf is ran with `--debug`, detailed information about the performed
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queries will be logged.
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### Example Output
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```
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```
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[stackdriver]: https://cloud.google.com/monitoring/api/v3/
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[auth]: https://cloud.google.com/docs/authentication/getting-started
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[pricing]: https://cloud.google.com/stackdriver/pricing#stackdriver_monitoring_services
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@ -0,0 +1,709 @@
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package stackdriver
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import (
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"context"
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"fmt"
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"log"
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"math"
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"strconv"
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"strings"
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"sync"
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"time"
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monitoring "cloud.google.com/go/monitoring/apiv3"
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googlepbduration "github.com/golang/protobuf/ptypes/duration"
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googlepbts "github.com/golang/protobuf/ptypes/timestamp"
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"github.com/influxdata/telegraf"
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"github.com/influxdata/telegraf/internal"
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"github.com/influxdata/telegraf/internal/limiter"
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"github.com/influxdata/telegraf/metric"
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"github.com/influxdata/telegraf/plugins/inputs" // Imports the Stackdriver Monitoring client package.
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"github.com/influxdata/telegraf/selfstat"
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"google.golang.org/api/iterator"
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distributionpb "google.golang.org/genproto/googleapis/api/distribution"
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metricpb "google.golang.org/genproto/googleapis/api/metric"
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monitoringpb "google.golang.org/genproto/googleapis/monitoring/v3"
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)
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const (
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defaultRateLimit = 14
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description = "Gather timeseries from Google Cloud Platform v3 monitoring API"
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sampleConfig = `
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## GCP Project
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project = "erudite-bloom-151019"
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## Include timeseries that start with the given metric type.
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metric_type_prefix_include = [
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"compute.googleapis.com/",
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]
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## Exclude timeseries that start with the given metric type.
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# metric_type_prefix_exclude = []
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|
|
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## Many metrics are updated once per minute; it is recommended to override
|
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## the agent level interval with a value of 1m or greater.
|
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interval = "1m"
|
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|
|
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|
## Maximum number of API calls to make per second. The quota for accounts
|
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|
## varies, it can be viewed on the API dashboard:
|
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## https://cloud.google.com/monitoring/quotas#quotas_and_limits
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# rate_limit = 14
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## The delay and window options control the number of points selected on
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## each gather. When set, metrics are gathered between:
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## start: now() - delay - window
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## end: now() - delay
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#
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## Collection delay; if set too low metrics may not yet be available.
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# delay = "5m"
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#
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## If unset, the window will start at 1m and be updated dynamically to span
|
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|
## the time between calls (approximately the length of the plugin interval).
|
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# window = "1m"
|
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|
|
||||||
|
## TTL for cached list of metric types. This is the maximum amount of time
|
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|
## it may take to discover new metrics.
|
||||||
|
# cache_ttl = "1h"
|
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|
|
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## If true, raw bucket counts are collected for distribution value types.
|
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|
## For a more lightweight collection, you may wish to disable and use
|
||||||
|
## distribution_aggregation_aligners instead.
|
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# gather_raw_distribution_buckets = true
|
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|
|
||||||
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## Aggregate functions to be used for metrics whose value type is
|
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|
## distribution. These aggregate values are recorded in in addition to raw
|
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|
## bucket counts; if they are enabled.
|
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|
##
|
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## For a list of aligner strings see:
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## https://cloud.google.com/monitoring/api/ref_v3/rpc/google.monitoring.v3#aligner
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# distribution_aggregation_aligners = [
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# "ALIGN_PERCENTILE_99",
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# "ALIGN_PERCENTILE_95",
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# "ALIGN_PERCENTILE_50",
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# ]
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|
|
||||||
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## Filters can be added to reduce the number of time series matched. All
|
||||||
|
## functions are supported: starts_with, ends_with, has_substring, and
|
||||||
|
## one_of. Only the '=' operator is supported.
|
||||||
|
##
|
||||||
|
## The logical operators when combining filters are defined statically using
|
||||||
|
## the following values:
|
||||||
|
## filter ::= <resource_labels> {AND <metric_labels>}
|
||||||
|
## resource_labels ::= <resource_labels> {OR <resource_label>}
|
||||||
|
## metric_labels ::= <metric_labels> {OR <metric_label>}
|
||||||
|
##
|
||||||
|
## For more details, see https://cloud.google.com/monitoring/api/v3/filters
|
||||||
|
#
|
||||||
|
## Resource labels refine the time series selection with the following expression:
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||||||
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## resource.labels.<key> = <value>
|
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|
# [[inputs.stackdriver.filter.resource_labels]]
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# key = "instance_name"
|
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# value = 'starts_with("localhost")'
|
||||||
|
#
|
||||||
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## Metric labels refine the time series selection with the following expression:
|
||||||
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## metric.labels.<key> = <value>
|
||||||
|
# [[inputs.stackdriver.filter.metric_labels]]
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# key = "device_name"
|
||||||
|
# value = 'one_of("sda", "sdb")'
|
||||||
|
`
|
||||||
|
)
|
||||||
|
|
||||||
|
var (
|
||||||
|
defaultCacheTTL = internal.Duration{Duration: 1 * time.Hour}
|
||||||
|
defaultWindow = internal.Duration{Duration: 1 * time.Minute}
|
||||||
|
defaultDelay = internal.Duration{Duration: 5 * time.Minute}
|
||||||
|
)
|
||||||
|
|
||||||
|
type (
|
||||||
|
// Stackdriver is the Google Stackdriver config info.
|
||||||
|
Stackdriver struct {
|
||||||
|
Project string `toml:"project"`
|
||||||
|
RateLimit int `toml:"rate_limit"`
|
||||||
|
Window internal.Duration `toml:"window"`
|
||||||
|
Delay internal.Duration `toml:"delay"`
|
||||||
|
CacheTTL internal.Duration `toml:"cache_ttl"`
|
||||||
|
MetricTypePrefixInclude []string `toml:"metric_type_prefix_include"`
|
||||||
|
MetricTypePrefixExclude []string `toml:"metric_type_prefix_exclude"`
|
||||||
|
GatherRawDistributionBuckets bool `toml:"gather_raw_distribution_buckets"`
|
||||||
|
DistributionAggregationAligners []string `toml:"distribution_aggregation_aligners"`
|
||||||
|
Filter *ListTimeSeriesFilter `toml:"filter"`
|
||||||
|
|
||||||
|
client metricClient
|
||||||
|
timeSeriesConfCache *timeSeriesConfCache
|
||||||
|
prevEnd time.Time
|
||||||
|
}
|
||||||
|
|
||||||
|
// ListTimeSeriesFilter contains resource labels and metric labels
|
||||||
|
ListTimeSeriesFilter struct {
|
||||||
|
ResourceLabels []*Label `json:"resource_labels"`
|
||||||
|
MetricLabels []*Label `json:"metric_labels"`
|
||||||
|
}
|
||||||
|
|
||||||
|
// Label contains key and value
|
||||||
|
Label struct {
|
||||||
|
Key string `toml:"key"`
|
||||||
|
Value string `toml:"value"`
|
||||||
|
}
|
||||||
|
|
||||||
|
// TimeSeriesConfCache caches generated timeseries configurations
|
||||||
|
timeSeriesConfCache struct {
|
||||||
|
TTL time.Duration
|
||||||
|
Generated time.Time
|
||||||
|
TimeSeriesConfs []*timeSeriesConf
|
||||||
|
}
|
||||||
|
|
||||||
|
// Internal structure which holds our configuration for a particular GCP time
|
||||||
|
// series.
|
||||||
|
timeSeriesConf struct {
|
||||||
|
// The influx measurement name this time series maps to
|
||||||
|
measurement string
|
||||||
|
// The prefix to use before any influx field names that we'll write for
|
||||||
|
// this time series. (Or, if we only decide to write one field name, this
|
||||||
|
// field just holds the value of the field name.)
|
||||||
|
fieldKey string
|
||||||
|
// The GCP API request that we'll use to fetch data for this time series.
|
||||||
|
listTimeSeriesRequest *monitoringpb.ListTimeSeriesRequest
|
||||||
|
}
|
||||||
|
|
||||||
|
// stackdriverMetricClient is a metric client for stackdriver
|
||||||
|
stackdriverMetricClient struct {
|
||||||
|
conn *monitoring.MetricClient
|
||||||
|
|
||||||
|
listMetricDescriptorsCalls selfstat.Stat
|
||||||
|
listTimeSeriesCalls selfstat.Stat
|
||||||
|
}
|
||||||
|
|
||||||
|
// metricClient is convenient for testing
|
||||||
|
metricClient interface {
|
||||||
|
ListMetricDescriptors(ctx context.Context, req *monitoringpb.ListMetricDescriptorsRequest) (<-chan *metricpb.MetricDescriptor, error)
|
||||||
|
ListTimeSeries(ctx context.Context, req *monitoringpb.ListTimeSeriesRequest) (<-chan *monitoringpb.TimeSeries, error)
|
||||||
|
Close() error
|
||||||
|
}
|
||||||
|
|
||||||
|
lockedSeriesGrouper struct {
|
||||||
|
sync.Mutex
|
||||||
|
*metric.SeriesGrouper
|
||||||
|
}
|
||||||
|
)
|
||||||
|
|
||||||
|
func (g *lockedSeriesGrouper) Add(
|
||||||
|
measurement string,
|
||||||
|
tags map[string]string,
|
||||||
|
tm time.Time,
|
||||||
|
field string,
|
||||||
|
fieldValue interface{},
|
||||||
|
) error {
|
||||||
|
g.Lock()
|
||||||
|
defer g.Unlock()
|
||||||
|
return g.SeriesGrouper.Add(measurement, tags, tm, field, fieldValue)
|
||||||
|
}
|
||||||
|
|
||||||
|
// ListMetricDescriptors implements metricClient interface
|
||||||
|
func (c *stackdriverMetricClient) ListMetricDescriptors(
|
||||||
|
ctx context.Context,
|
||||||
|
req *monitoringpb.ListMetricDescriptorsRequest,
|
||||||
|
) (<-chan *metricpb.MetricDescriptor, error) {
|
||||||
|
mdChan := make(chan *metricpb.MetricDescriptor, 1000)
|
||||||
|
|
||||||
|
go func() {
|
||||||
|
log.Printf("D! [inputs.stackdriver] ListMetricDescriptors: %s", req.Filter)
|
||||||
|
defer close(mdChan)
|
||||||
|
|
||||||
|
// Iterate over metric descriptors and send them to buffered channel
|
||||||
|
mdResp := c.conn.ListMetricDescriptors(ctx, req)
|
||||||
|
c.listMetricDescriptorsCalls.Incr(1)
|
||||||
|
for {
|
||||||
|
mdDesc, mdErr := mdResp.Next()
|
||||||
|
if mdErr != nil {
|
||||||
|
if mdErr != iterator.Done {
|
||||||
|
log.Printf("E! [inputs.stackdriver] Received error response: %s: %v", req, mdErr)
|
||||||
|
}
|
||||||
|
break
|
||||||
|
}
|
||||||
|
mdChan <- mdDesc
|
||||||
|
}
|
||||||
|
}()
|
||||||
|
|
||||||
|
return mdChan, nil
|
||||||
|
}
|
||||||
|
|
||||||
|
// ListTimeSeries implements metricClient interface
|
||||||
|
func (c *stackdriverMetricClient) ListTimeSeries(
|
||||||
|
ctx context.Context,
|
||||||
|
req *monitoringpb.ListTimeSeriesRequest,
|
||||||
|
) (<-chan *monitoringpb.TimeSeries, error) {
|
||||||
|
tsChan := make(chan *monitoringpb.TimeSeries, 1000)
|
||||||
|
|
||||||
|
go func() {
|
||||||
|
log.Printf("D! [inputs.stackdriver] ListTimeSeries: %s", req.Filter)
|
||||||
|
defer close(tsChan)
|
||||||
|
|
||||||
|
// Iterate over timeseries and send them to buffered channel
|
||||||
|
tsResp := c.conn.ListTimeSeries(ctx, req)
|
||||||
|
c.listTimeSeriesCalls.Incr(1)
|
||||||
|
for {
|
||||||
|
tsDesc, tsErr := tsResp.Next()
|
||||||
|
if tsErr != nil {
|
||||||
|
if tsErr != iterator.Done {
|
||||||
|
log.Printf("E! [inputs.stackdriver] Received error response: %s: %v", req, tsErr)
|
||||||
|
}
|
||||||
|
break
|
||||||
|
}
|
||||||
|
tsChan <- tsDesc
|
||||||
|
}
|
||||||
|
}()
|
||||||
|
|
||||||
|
return tsChan, nil
|
||||||
|
}
|
||||||
|
|
||||||
|
// Close implements metricClient interface
|
||||||
|
func (s *stackdriverMetricClient) Close() error {
|
||||||
|
return s.conn.Close()
|
||||||
|
}
|
||||||
|
|
||||||
|
// Description implements telegraf.Input interface
|
||||||
|
func (s *Stackdriver) Description() string {
|
||||||
|
return description
|
||||||
|
}
|
||||||
|
|
||||||
|
// SampleConfig implements telegraf.Input interface
|
||||||
|
func (s *Stackdriver) SampleConfig() string {
|
||||||
|
return sampleConfig
|
||||||
|
}
|
||||||
|
|
||||||
|
// Gather implements telegraf.Input interface
|
||||||
|
func (s *Stackdriver) Gather(acc telegraf.Accumulator) error {
|
||||||
|
ctx := context.Background()
|
||||||
|
|
||||||
|
if s.RateLimit == 0 {
|
||||||
|
s.RateLimit = defaultRateLimit
|
||||||
|
}
|
||||||
|
|
||||||
|
err := s.initializeStackdriverClient(ctx)
|
||||||
|
if err != nil {
|
||||||
|
return err
|
||||||
|
}
|
||||||
|
|
||||||
|
start, end := s.updateWindow(s.prevEnd)
|
||||||
|
s.prevEnd = end
|
||||||
|
|
||||||
|
tsConfs, err := s.generatetimeSeriesConfs(ctx, start, end)
|
||||||
|
if err != nil {
|
||||||
|
return err
|
||||||
|
}
|
||||||
|
|
||||||
|
lmtr := limiter.NewRateLimiter(s.RateLimit, time.Second)
|
||||||
|
defer lmtr.Stop()
|
||||||
|
|
||||||
|
grouper := &lockedSeriesGrouper{
|
||||||
|
SeriesGrouper: metric.NewSeriesGrouper(),
|
||||||
|
}
|
||||||
|
|
||||||
|
var wg sync.WaitGroup
|
||||||
|
wg.Add(len(tsConfs))
|
||||||
|
for _, tsConf := range tsConfs {
|
||||||
|
<-lmtr.C
|
||||||
|
go func(tsConf *timeSeriesConf) {
|
||||||
|
defer wg.Done()
|
||||||
|
acc.AddError(s.gatherTimeSeries(ctx, grouper, tsConf))
|
||||||
|
}(tsConf)
|
||||||
|
}
|
||||||
|
wg.Wait()
|
||||||
|
|
||||||
|
for _, metric := range grouper.Metrics() {
|
||||||
|
acc.AddMetric(metric)
|
||||||
|
}
|
||||||
|
|
||||||
|
return nil
|
||||||
|
}
|
||||||
|
|
||||||
|
// Returns the start and end time for the next collection.
|
||||||
|
func (s *Stackdriver) updateWindow(prevEnd time.Time) (time.Time, time.Time) {
|
||||||
|
var start time.Time
|
||||||
|
if s.Window.Duration != 0 {
|
||||||
|
start = time.Now().Add(-s.Delay.Duration).Add(-s.Window.Duration)
|
||||||
|
} else if prevEnd.IsZero() {
|
||||||
|
start = time.Now().Add(-s.Delay.Duration).Add(-defaultWindow.Duration)
|
||||||
|
} else {
|
||||||
|
start = prevEnd
|
||||||
|
}
|
||||||
|
end := time.Now().Add(-s.Delay.Duration)
|
||||||
|
return start, end
|
||||||
|
}
|
||||||
|
|
||||||
|
// Generate filter string for ListTimeSeriesRequest
|
||||||
|
func (s *Stackdriver) newListTimeSeriesFilter(metricType string) string {
|
||||||
|
functions := []string{
|
||||||
|
"starts_with",
|
||||||
|
"ends_with",
|
||||||
|
"has_substring",
|
||||||
|
"one_of",
|
||||||
|
}
|
||||||
|
filterString := fmt.Sprintf(`metric.type = "%s"`, metricType)
|
||||||
|
if s.Filter == nil {
|
||||||
|
return filterString
|
||||||
|
}
|
||||||
|
|
||||||
|
var valueFmt string
|
||||||
|
if len(s.Filter.ResourceLabels) > 0 {
|
||||||
|
resourceLabelsFilter := make([]string, len(s.Filter.ResourceLabels))
|
||||||
|
for i, resourceLabel := range s.Filter.ResourceLabels {
|
||||||
|
// check if resource label value contains function
|
||||||
|
if includeExcludeHelper(resourceLabel.Value, functions, nil) {
|
||||||
|
valueFmt = `resource.labels.%s = %s`
|
||||||
|
} else {
|
||||||
|
valueFmt = `resource.labels.%s = "%s"`
|
||||||
|
}
|
||||||
|
resourceLabelsFilter[i] = fmt.Sprintf(valueFmt, resourceLabel.Key, resourceLabel.Value)
|
||||||
|
}
|
||||||
|
if len(resourceLabelsFilter) == 1 {
|
||||||
|
filterString += fmt.Sprintf(" AND %s", resourceLabelsFilter[0])
|
||||||
|
} else {
|
||||||
|
filterString += fmt.Sprintf(" AND (%s)", strings.Join(resourceLabelsFilter, " OR "))
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
if len(s.Filter.MetricLabels) > 0 {
|
||||||
|
metricLabelsFilter := make([]string, len(s.Filter.MetricLabels))
|
||||||
|
for i, metricLabel := range s.Filter.MetricLabels {
|
||||||
|
// check if metric label value contains function
|
||||||
|
if includeExcludeHelper(metricLabel.Value, functions, nil) {
|
||||||
|
valueFmt = `metric.labels.%s = %s`
|
||||||
|
} else {
|
||||||
|
valueFmt = `metric.labels.%s = "%s"`
|
||||||
|
}
|
||||||
|
metricLabelsFilter[i] = fmt.Sprintf(valueFmt, metricLabel.Key, metricLabel.Value)
|
||||||
|
}
|
||||||
|
if len(metricLabelsFilter) == 1 {
|
||||||
|
filterString += fmt.Sprintf(" AND %s", metricLabelsFilter[0])
|
||||||
|
} else {
|
||||||
|
filterString += fmt.Sprintf(" AND (%s)", strings.Join(metricLabelsFilter, " OR "))
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
return filterString
|
||||||
|
}
|
||||||
|
|
||||||
|
// Create and initialize a timeSeriesConf for a given GCP metric type with
|
||||||
|
// defaults taken from the gcp_stackdriver plugin configuration.
|
||||||
|
func (s *Stackdriver) newTimeSeriesConf(
|
||||||
|
metricType string, startTime, endTime time.Time,
|
||||||
|
) *timeSeriesConf {
|
||||||
|
filter := s.newListTimeSeriesFilter(metricType)
|
||||||
|
interval := &monitoringpb.TimeInterval{
|
||||||
|
EndTime: &googlepbts.Timestamp{Seconds: endTime.Unix()},
|
||||||
|
StartTime: &googlepbts.Timestamp{Seconds: startTime.Unix()},
|
||||||
|
}
|
||||||
|
tsReq := &monitoringpb.ListTimeSeriesRequest{
|
||||||
|
Name: monitoring.MetricProjectPath(s.Project),
|
||||||
|
Filter: filter,
|
||||||
|
Interval: interval,
|
||||||
|
}
|
||||||
|
cfg := &timeSeriesConf{
|
||||||
|
measurement: metricType,
|
||||||
|
fieldKey: "value",
|
||||||
|
listTimeSeriesRequest: tsReq,
|
||||||
|
}
|
||||||
|
|
||||||
|
// GCP metric types have at least one slash, but we'll be defensive anyway.
|
||||||
|
slashIdx := strings.LastIndex(metricType, "/")
|
||||||
|
if slashIdx > 0 {
|
||||||
|
cfg.measurement = metricType[:slashIdx]
|
||||||
|
cfg.fieldKey = metricType[slashIdx+1:]
|
||||||
|
}
|
||||||
|
|
||||||
|
return cfg
|
||||||
|
}
|
||||||
|
|
||||||
|
// Change this configuration to query an aggregate by specifying an "aligner".
|
||||||
|
// In GCP monitoring, "aligning" is aggregation performed *within* a time
|
||||||
|
// series, to distill a pile of data points down to a single data point for
|
||||||
|
// some given time period (here, we specify 60s as our time period). This is
|
||||||
|
// especially useful for scraping GCP "distribution" metric types, whose raw
|
||||||
|
// data amounts to a ~60 bucket histogram, which is fairly hard to query and
|
||||||
|
// visualize in the TICK stack.
|
||||||
|
func (t *timeSeriesConf) initForAggregate(alignerStr string) {
|
||||||
|
// Check if alignerStr is valid
|
||||||
|
alignerInt, isValid := monitoringpb.Aggregation_Aligner_value[alignerStr]
|
||||||
|
if !isValid {
|
||||||
|
alignerStr = monitoringpb.Aggregation_Aligner_name[alignerInt]
|
||||||
|
}
|
||||||
|
aligner := monitoringpb.Aggregation_Aligner(alignerInt)
|
||||||
|
agg := &monitoringpb.Aggregation{
|
||||||
|
AlignmentPeriod: &googlepbduration.Duration{Seconds: 60},
|
||||||
|
PerSeriesAligner: aligner,
|
||||||
|
}
|
||||||
|
t.fieldKey = t.fieldKey + "_" + strings.ToLower(alignerStr)
|
||||||
|
t.listTimeSeriesRequest.Aggregation = agg
|
||||||
|
}
|
||||||
|
|
||||||
|
// IsValid checks timeseriesconf cache validity
|
||||||
|
func (c *timeSeriesConfCache) IsValid() bool {
|
||||||
|
return c.TimeSeriesConfs != nil && time.Since(c.Generated) < c.TTL
|
||||||
|
}
|
||||||
|
|
||||||
|
func (s *Stackdriver) initializeStackdriverClient(ctx context.Context) error {
|
||||||
|
if s.client == nil {
|
||||||
|
client, err := monitoring.NewMetricClient(ctx)
|
||||||
|
if err != nil {
|
||||||
|
return fmt.Errorf("failed to create stackdriver monitoring client: %v", err)
|
||||||
|
}
|
||||||
|
|
||||||
|
tags := map[string]string{
|
||||||
|
"project_id": s.Project,
|
||||||
|
}
|
||||||
|
listMetricDescriptorsCalls := selfstat.Register(
|
||||||
|
"stackdriver", "list_metric_descriptors_calls", tags)
|
||||||
|
listTimeSeriesCalls := selfstat.Register(
|
||||||
|
"stackdriver", "list_timeseries_calls", tags)
|
||||||
|
|
||||||
|
s.client = &stackdriverMetricClient{
|
||||||
|
conn: client,
|
||||||
|
listMetricDescriptorsCalls: listMetricDescriptorsCalls,
|
||||||
|
listTimeSeriesCalls: listTimeSeriesCalls,
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
return nil
|
||||||
|
}
|
||||||
|
|
||||||
|
func includeExcludeHelper(key string, includes []string, excludes []string) bool {
|
||||||
|
if len(includes) > 0 {
|
||||||
|
for _, includeStr := range includes {
|
||||||
|
if strings.HasPrefix(key, includeStr) {
|
||||||
|
return true
|
||||||
|
}
|
||||||
|
}
|
||||||
|
return false
|
||||||
|
}
|
||||||
|
if len(excludes) > 0 {
|
||||||
|
for _, excludeStr := range excludes {
|
||||||
|
if strings.HasPrefix(key, excludeStr) {
|
||||||
|
return false
|
||||||
|
}
|
||||||
|
}
|
||||||
|
return true
|
||||||
|
}
|
||||||
|
return true
|
||||||
|
}
|
||||||
|
|
||||||
|
// Test whether a particular GCP metric type should be scraped by this plugin
|
||||||
|
// by checking the plugin name against the configuration's
|
||||||
|
// "includeMetricTypePrefixes" and "excludeMetricTypePrefixes"
|
||||||
|
func (s *Stackdriver) includeMetricType(metricType string) bool {
|
||||||
|
k := metricType
|
||||||
|
inc := s.MetricTypePrefixInclude
|
||||||
|
exc := s.MetricTypePrefixExclude
|
||||||
|
|
||||||
|
return includeExcludeHelper(k, inc, exc)
|
||||||
|
}
|
||||||
|
|
||||||
|
// Generates filter for list metric descriptors request
|
||||||
|
func (s *Stackdriver) newListMetricDescriptorsFilters() []string {
|
||||||
|
if len(s.MetricTypePrefixInclude) == 0 {
|
||||||
|
return nil
|
||||||
|
}
|
||||||
|
|
||||||
|
metricTypeFilters := make([]string, len(s.MetricTypePrefixInclude))
|
||||||
|
for i, metricTypePrefix := range s.MetricTypePrefixInclude {
|
||||||
|
metricTypeFilters[i] = fmt.Sprintf(`metric.type = starts_with(%q)`, metricTypePrefix)
|
||||||
|
}
|
||||||
|
return metricTypeFilters
|
||||||
|
}
|
||||||
|
|
||||||
|
// Generate a list of timeSeriesConfig structs by making a ListMetricDescriptors
|
||||||
|
// API request and filtering the result against our configuration.
|
||||||
|
func (s *Stackdriver) generatetimeSeriesConfs(
|
||||||
|
ctx context.Context, startTime, endTime time.Time,
|
||||||
|
) ([]*timeSeriesConf, error) {
|
||||||
|
if s.timeSeriesConfCache != nil && s.timeSeriesConfCache.IsValid() {
|
||||||
|
// Update interval for timeseries requests in timeseries cache
|
||||||
|
interval := &monitoringpb.TimeInterval{
|
||||||
|
EndTime: &googlepbts.Timestamp{Seconds: endTime.Unix()},
|
||||||
|
StartTime: &googlepbts.Timestamp{Seconds: startTime.Unix()},
|
||||||
|
}
|
||||||
|
for _, timeSeriesConf := range s.timeSeriesConfCache.TimeSeriesConfs {
|
||||||
|
timeSeriesConf.listTimeSeriesRequest.Interval = interval
|
||||||
|
}
|
||||||
|
return s.timeSeriesConfCache.TimeSeriesConfs, nil
|
||||||
|
}
|
||||||
|
|
||||||
|
ret := []*timeSeriesConf{}
|
||||||
|
req := &monitoringpb.ListMetricDescriptorsRequest{
|
||||||
|
Name: monitoring.MetricProjectPath(s.Project),
|
||||||
|
}
|
||||||
|
|
||||||
|
filters := s.newListMetricDescriptorsFilters()
|
||||||
|
if len(filters) == 0 {
|
||||||
|
filters = []string{""}
|
||||||
|
}
|
||||||
|
|
||||||
|
for _, filter := range filters {
|
||||||
|
// Add filter for list metric descriptors if
|
||||||
|
// includeMetricTypePrefixes is specified,
|
||||||
|
// this is more effecient than iterating over
|
||||||
|
// all metric descriptors
|
||||||
|
req.Filter = filter
|
||||||
|
mdRespChan, err := s.client.ListMetricDescriptors(ctx, req)
|
||||||
|
if err != nil {
|
||||||
|
return nil, err
|
||||||
|
}
|
||||||
|
|
||||||
|
for metricDescriptor := range mdRespChan {
|
||||||
|
metricType := metricDescriptor.Type
|
||||||
|
valueType := metricDescriptor.ValueType
|
||||||
|
|
||||||
|
if filter == "" && !s.includeMetricType(metricType) {
|
||||||
|
continue
|
||||||
|
}
|
||||||
|
|
||||||
|
if valueType == metricpb.MetricDescriptor_DISTRIBUTION {
|
||||||
|
if s.GatherRawDistributionBuckets {
|
||||||
|
tsConf := s.newTimeSeriesConf(metricType, startTime, endTime)
|
||||||
|
ret = append(ret, tsConf)
|
||||||
|
}
|
||||||
|
for _, alignerStr := range s.DistributionAggregationAligners {
|
||||||
|
tsConf := s.newTimeSeriesConf(metricType, startTime, endTime)
|
||||||
|
tsConf.initForAggregate(alignerStr)
|
||||||
|
ret = append(ret, tsConf)
|
||||||
|
}
|
||||||
|
} else {
|
||||||
|
ret = append(ret, s.newTimeSeriesConf(metricType, startTime, endTime))
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
s.timeSeriesConfCache = &timeSeriesConfCache{
|
||||||
|
TimeSeriesConfs: ret,
|
||||||
|
Generated: time.Now(),
|
||||||
|
TTL: s.CacheTTL.Duration,
|
||||||
|
}
|
||||||
|
|
||||||
|
return ret, nil
|
||||||
|
}
|
||||||
|
|
||||||
|
// Do the work to gather an individual time series. Runs inside a
|
||||||
|
// timeseries-specific goroutine.
|
||||||
|
func (s *Stackdriver) gatherTimeSeries(
|
||||||
|
ctx context.Context, grouper *lockedSeriesGrouper, tsConf *timeSeriesConf,
|
||||||
|
) error {
|
||||||
|
tsReq := tsConf.listTimeSeriesRequest
|
||||||
|
|
||||||
|
tsRespChan, err := s.client.ListTimeSeries(ctx, tsReq)
|
||||||
|
if err != nil {
|
||||||
|
return err
|
||||||
|
}
|
||||||
|
|
||||||
|
for tsDesc := range tsRespChan {
|
||||||
|
tags := map[string]string{
|
||||||
|
"resource_type": tsDesc.Resource.Type,
|
||||||
|
}
|
||||||
|
for k, v := range tsDesc.Resource.Labels {
|
||||||
|
tags[k] = v
|
||||||
|
}
|
||||||
|
for k, v := range tsDesc.Metric.Labels {
|
||||||
|
tags[k] = v
|
||||||
|
}
|
||||||
|
|
||||||
|
for _, p := range tsDesc.Points {
|
||||||
|
ts := time.Unix(p.Interval.EndTime.Seconds, 0)
|
||||||
|
|
||||||
|
if tsDesc.ValueType == metricpb.MetricDescriptor_DISTRIBUTION {
|
||||||
|
dist := p.Value.GetDistributionValue()
|
||||||
|
s.addDistribution(dist, tags, ts, grouper, tsConf)
|
||||||
|
} else {
|
||||||
|
var value interface{}
|
||||||
|
|
||||||
|
// Types that are valid to be assigned to Value
|
||||||
|
// See: https://godoc.org/google.golang.org/genproto/googleapis/monitoring/v3#TypedValue
|
||||||
|
switch tsDesc.ValueType {
|
||||||
|
case metricpb.MetricDescriptor_BOOL:
|
||||||
|
value = p.Value.GetBoolValue()
|
||||||
|
case metricpb.MetricDescriptor_INT64:
|
||||||
|
value = p.Value.GetInt64Value()
|
||||||
|
case metricpb.MetricDescriptor_DOUBLE:
|
||||||
|
value = p.Value.GetDoubleValue()
|
||||||
|
case metricpb.MetricDescriptor_STRING:
|
||||||
|
value = p.Value.GetStringValue()
|
||||||
|
}
|
||||||
|
|
||||||
|
grouper.Add(tsConf.measurement, tags, ts, tsConf.fieldKey, value)
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
return nil
|
||||||
|
}
|
||||||
|
|
||||||
|
// AddDistribution adds metrics from a distribution value type.
|
||||||
|
func (s *Stackdriver) addDistribution(
|
||||||
|
metric *distributionpb.Distribution,
|
||||||
|
tags map[string]string, ts time.Time, grouper *lockedSeriesGrouper, tsConf *timeSeriesConf,
|
||||||
|
) {
|
||||||
|
field := tsConf.fieldKey
|
||||||
|
name := tsConf.measurement
|
||||||
|
|
||||||
|
grouper.Add(name, tags, ts, field+"_count", metric.Count)
|
||||||
|
grouper.Add(name, tags, ts, field+"_mean", metric.Mean)
|
||||||
|
grouper.Add(name, tags, ts, field+"_sum_of_squared_deviation", metric.SumOfSquaredDeviation)
|
||||||
|
|
||||||
|
if metric.Range != nil {
|
||||||
|
grouper.Add(name, tags, ts, field+"_range_min", metric.Range.Min)
|
||||||
|
grouper.Add(name, tags, ts, field+"_range_max", metric.Range.Max)
|
||||||
|
}
|
||||||
|
|
||||||
|
linearBuckets := metric.BucketOptions.GetLinearBuckets()
|
||||||
|
exponentialBuckets := metric.BucketOptions.GetExponentialBuckets()
|
||||||
|
explicitBuckets := metric.BucketOptions.GetExplicitBuckets()
|
||||||
|
|
||||||
|
var numBuckets int32
|
||||||
|
if linearBuckets != nil {
|
||||||
|
numBuckets = linearBuckets.NumFiniteBuckets + 2
|
||||||
|
} else if exponentialBuckets != nil {
|
||||||
|
numBuckets = exponentialBuckets.NumFiniteBuckets + 2
|
||||||
|
} else {
|
||||||
|
numBuckets = int32(len(explicitBuckets.Bounds)) + 1
|
||||||
|
}
|
||||||
|
|
||||||
|
var i int32
|
||||||
|
var count int64
|
||||||
|
for i = 0; i < numBuckets; i++ {
|
||||||
|
// The last bucket is the overflow bucket, and includes all values
|
||||||
|
// greater than the previous bound.
|
||||||
|
if i == numBuckets-1 {
|
||||||
|
tags["lt"] = "+Inf"
|
||||||
|
} else {
|
||||||
|
var upperBound float64
|
||||||
|
if linearBuckets != nil {
|
||||||
|
upperBound = linearBuckets.Offset + (linearBuckets.Width * float64(i))
|
||||||
|
} else if exponentialBuckets != nil {
|
||||||
|
width := math.Pow(exponentialBuckets.GrowthFactor, float64(i))
|
||||||
|
upperBound = exponentialBuckets.Scale * width
|
||||||
|
} else if explicitBuckets != nil {
|
||||||
|
upperBound = explicitBuckets.Bounds[i]
|
||||||
|
}
|
||||||
|
tags["lt"] = strconv.FormatFloat(upperBound, 'f', -1, 64)
|
||||||
|
}
|
||||||
|
|
||||||
|
// Add to the cumulative count; trailing buckets with value 0 are
|
||||||
|
// omitted from the response.
|
||||||
|
if i < int32(len(metric.BucketCounts)) {
|
||||||
|
count += metric.BucketCounts[i]
|
||||||
|
}
|
||||||
|
grouper.Add(name, tags, ts, field+"_bucket", count)
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
func init() {
|
||||||
|
f := func() telegraf.Input {
|
||||||
|
return &Stackdriver{
|
||||||
|
CacheTTL: defaultCacheTTL,
|
||||||
|
RateLimit: defaultRateLimit,
|
||||||
|
Delay: defaultDelay,
|
||||||
|
GatherRawDistributionBuckets: true,
|
||||||
|
DistributionAggregationAligners: []string{},
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
inputs.Add("stackdriver", f)
|
||||||
|
}
|
||||||
File diff suppressed because it is too large
Load Diff
|
|
@ -103,3 +103,11 @@ func MustMetric(
|
||||||
}
|
}
|
||||||
return m
|
return m
|
||||||
}
|
}
|
||||||
|
|
||||||
|
func FromTestMetric(met *Metric) telegraf.Metric {
|
||||||
|
m, err := metric.New(met.Measurement, met.Tags, met.Fields, met.Time)
|
||||||
|
if err != nil {
|
||||||
|
panic("MustMetric")
|
||||||
|
}
|
||||||
|
return m
|
||||||
|
}
|
||||||
|
|
|
||||||
Loading…
Reference in New Issue