Adding upstream version 1.34.4.
Signed-off-by: Daniel Baumann <daniel@debian.org>
This commit is contained in:
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4963 changed files with 677545 additions and 0 deletions
425
plugins/outputs/cloudwatch/cloudwatch.go
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425
plugins/outputs/cloudwatch/cloudwatch.go
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@ -0,0 +1,425 @@
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//go:generate ../../../tools/readme_config_includer/generator
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package cloudwatch
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import (
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"context"
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_ "embed"
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"math"
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"net/http"
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"sort"
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"strings"
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"time"
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"github.com/aws/aws-sdk-go-v2/aws"
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"github.com/aws/aws-sdk-go-v2/service/cloudwatch"
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"github.com/aws/aws-sdk-go-v2/service/cloudwatch/types"
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"github.com/influxdata/telegraf"
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common_aws "github.com/influxdata/telegraf/plugins/common/aws"
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common_http "github.com/influxdata/telegraf/plugins/common/http"
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"github.com/influxdata/telegraf/plugins/outputs"
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)
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//go:embed sample.conf
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var sampleConfig string
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type CloudWatch struct {
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Namespace string `toml:"namespace"` // CloudWatch Metrics Namespace
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HighResolutionMetrics bool `toml:"high_resolution_metrics"`
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svc *cloudwatch.Client
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WriteStatistics bool `toml:"write_statistics"`
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Log telegraf.Logger `toml:"-"`
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common_aws.CredentialConfig
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common_http.HTTPClientConfig
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client *http.Client
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}
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type statisticType int
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const (
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statisticTypeNone statisticType = iota
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statisticTypeMax
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statisticTypeMin
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statisticTypeSum
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statisticTypeCount
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)
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type cloudwatchField interface {
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addValue(sType statisticType, value float64)
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buildDatum() []types.MetricDatum
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}
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type statisticField struct {
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metricName string
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fieldName string
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tags map[string]string
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values map[statisticType]float64
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timestamp time.Time
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storageResolution int64
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}
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func (f *statisticField) addValue(sType statisticType, value float64) {
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if sType != statisticTypeNone {
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f.values[sType] = value
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}
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}
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func (f *statisticField) buildDatum() []types.MetricDatum {
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var datums []types.MetricDatum
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if f.hasAllFields() {
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// If we have all required fields, we build datum with StatisticValues
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vmin := f.values[statisticTypeMin]
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vmax := f.values[statisticTypeMax]
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vsum := f.values[statisticTypeSum]
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vcount := f.values[statisticTypeCount]
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datum := types.MetricDatum{
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MetricName: aws.String(strings.Join([]string{f.metricName, f.fieldName}, "_")),
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Dimensions: BuildDimensions(f.tags),
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Timestamp: aws.Time(f.timestamp),
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StatisticValues: &types.StatisticSet{
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Minimum: aws.Float64(vmin),
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Maximum: aws.Float64(vmax),
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Sum: aws.Float64(vsum),
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SampleCount: aws.Float64(vcount),
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},
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StorageResolution: aws.Int32(int32(f.storageResolution)),
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}
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datums = append(datums, datum)
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} else {
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// If we don't have all required fields, we build each field as independent datum
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for sType, value := range f.values {
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datum := types.MetricDatum{
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Value: aws.Float64(value),
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Dimensions: BuildDimensions(f.tags),
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Timestamp: aws.Time(f.timestamp),
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}
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switch sType {
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case statisticTypeMin:
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datum.MetricName = aws.String(strings.Join([]string{f.metricName, f.fieldName, "min"}, "_"))
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case statisticTypeMax:
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datum.MetricName = aws.String(strings.Join([]string{f.metricName, f.fieldName, "max"}, "_"))
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case statisticTypeSum:
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datum.MetricName = aws.String(strings.Join([]string{f.metricName, f.fieldName, "sum"}, "_"))
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case statisticTypeCount:
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datum.MetricName = aws.String(strings.Join([]string{f.metricName, f.fieldName, "count"}, "_"))
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default:
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// should not be here
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continue
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}
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datums = append(datums, datum)
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}
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}
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return datums
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}
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func (f *statisticField) hasAllFields() bool {
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_, hasMin := f.values[statisticTypeMin]
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_, hasMax := f.values[statisticTypeMax]
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_, hasSum := f.values[statisticTypeSum]
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_, hasCount := f.values[statisticTypeCount]
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return hasMin && hasMax && hasSum && hasCount
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}
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type valueField struct {
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metricName string
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fieldName string
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tags map[string]string
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value float64
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timestamp time.Time
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storageResolution int64
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}
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func (f *valueField) addValue(sType statisticType, value float64) {
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if sType == statisticTypeNone {
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f.value = value
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}
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}
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func (f *valueField) buildDatum() []types.MetricDatum {
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return []types.MetricDatum{
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{
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MetricName: aws.String(strings.Join([]string{f.metricName, f.fieldName}, "_")),
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Value: aws.Float64(f.value),
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Dimensions: BuildDimensions(f.tags),
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Timestamp: aws.Time(f.timestamp),
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StorageResolution: aws.Int32(int32(f.storageResolution)),
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},
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}
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}
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func (*CloudWatch) SampleConfig() string {
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return sampleConfig
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}
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func (c *CloudWatch) Connect() error {
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cfg, err := c.CredentialConfig.Credentials()
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if err != nil {
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return err
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}
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ctx := context.Background()
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client, err := c.HTTPClientConfig.CreateClient(ctx, c.Log)
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if err != nil {
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return err
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}
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c.client = client
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c.svc = cloudwatch.NewFromConfig(cfg, func(options *cloudwatch.Options) {
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options.HTTPClient = c.client
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})
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return nil
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}
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func (c *CloudWatch) Close() error {
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if c.client != nil {
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c.client.CloseIdleConnections()
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}
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return nil
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}
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func (c *CloudWatch) Write(metrics []telegraf.Metric) error {
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var datums []types.MetricDatum
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for _, m := range metrics {
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d := BuildMetricDatum(c.WriteStatistics, c.HighResolutionMetrics, m)
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datums = append(datums, d...)
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}
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// PutMetricData only supports up to 1000 data metrics per call
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// https://docs.aws.amazon.com/AmazonCloudWatch/latest/APIReference/API_PutMetricData.html
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const maxDatumsPerCall = 1000
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for _, partition := range PartitionDatums(maxDatumsPerCall, datums) {
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err := c.WriteToCloudWatch(partition)
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if err != nil {
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return err
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}
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}
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return nil
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}
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func (c *CloudWatch) WriteToCloudWatch(datums []types.MetricDatum) error {
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params := &cloudwatch.PutMetricDataInput{
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MetricData: datums,
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Namespace: aws.String(c.Namespace),
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}
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_, err := c.svc.PutMetricData(context.Background(), params)
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if err != nil {
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c.Log.Errorf("Unable to write to CloudWatch : %+v", err.Error())
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}
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return err
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}
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// PartitionDatums partitions the MetricDatums into smaller slices of a max size so that are under the limit
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// for the AWS API calls.
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func PartitionDatums(size int, datums []types.MetricDatum) [][]types.MetricDatum {
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numberOfPartitions := len(datums) / size
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if len(datums)%size != 0 {
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numberOfPartitions++
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}
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partitions := make([][]types.MetricDatum, numberOfPartitions)
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for i := 0; i < numberOfPartitions; i++ {
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start := size * i
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end := size * (i + 1)
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if end > len(datums) {
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end = len(datums)
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}
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partitions[i] = datums[start:end]
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}
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return partitions
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}
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// BuildMetricDatum makes a MetricDatum from telegraf.Metric. It would check if all required fields of
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// cloudwatch.StatisticSet are available. If so, it would build MetricDatum from statistic values.
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// Otherwise, fields would still been built independently.
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func BuildMetricDatum(buildStatistic, highResolutionMetrics bool, point telegraf.Metric) []types.MetricDatum {
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fields := make(map[string]cloudwatchField)
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tags := point.Tags()
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storageResolution := int64(60)
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if highResolutionMetrics {
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storageResolution = 1
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}
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for k, v := range point.Fields() {
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val, ok := convert(v)
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if !ok {
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// Only fields with values that can be converted to float64 (and within CloudWatch boundary) are supported.
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// Non-supported fields are skipped.
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continue
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}
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sType, fieldName := getStatisticType(k)
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// If statistic metric is not enabled or non-statistic type, just take current field as a value field.
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if !buildStatistic || sType == statisticTypeNone {
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fields[k] = &valueField{
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metricName: point.Name(),
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fieldName: k,
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tags: tags,
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timestamp: point.Time(),
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value: val,
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storageResolution: storageResolution,
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}
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continue
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}
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// Otherwise, it shall be a statistic field.
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if _, ok := fields[fieldName]; !ok {
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// Hit an uncached field, create statisticField for first time
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fields[fieldName] = &statisticField{
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metricName: point.Name(),
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fieldName: fieldName,
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tags: tags,
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timestamp: point.Time(),
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values: map[statisticType]float64{
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sType: val,
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},
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storageResolution: storageResolution,
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}
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} else {
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// Add new statistic value to this field
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fields[fieldName].addValue(sType, val)
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}
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}
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var datums []types.MetricDatum
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for _, f := range fields {
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d := f.buildDatum()
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datums = append(datums, d...)
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}
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return datums
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}
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// BuildDimensions makes a list of Dimensions by using a Point's tags. CloudWatch supports up to
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// 10 dimensions per metric, so we only keep up to the first 10 alphabetically.
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// This always includes the "host" tag if it exists.
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func BuildDimensions(mTags map[string]string) []types.Dimension {
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const maxDimensions = 10
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dimensions := make([]types.Dimension, 0, maxDimensions)
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// This is pretty ugly, but we always want to include the "host" tag if it exists.
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if host, ok := mTags["host"]; ok {
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dimensions = append(dimensions, types.Dimension{
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Name: aws.String("host"),
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Value: aws.String(host),
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})
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}
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var keys []string
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for k := range mTags {
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if k != "host" {
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keys = append(keys, k)
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}
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}
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sort.Strings(keys)
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for _, k := range keys {
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if len(dimensions) >= maxDimensions {
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break
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}
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value := mTags[k]
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if value == "" {
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continue
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}
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dimensions = append(dimensions, types.Dimension{
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Name: aws.String(k),
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Value: aws.String(mTags[k]),
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})
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}
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return dimensions
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}
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func getStatisticType(name string) (sType statisticType, fieldName string) {
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switch {
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case strings.HasSuffix(name, "_max"):
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sType = statisticTypeMax
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fieldName = strings.TrimSuffix(name, "_max")
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case strings.HasSuffix(name, "_min"):
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sType = statisticTypeMin
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fieldName = strings.TrimSuffix(name, "_min")
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case strings.HasSuffix(name, "_sum"):
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sType = statisticTypeSum
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fieldName = strings.TrimSuffix(name, "_sum")
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case strings.HasSuffix(name, "_count"):
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sType = statisticTypeCount
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fieldName = strings.TrimSuffix(name, "_count")
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default:
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sType = statisticTypeNone
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fieldName = name
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}
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return sType, fieldName
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}
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func convert(v interface{}) (value float64, ok bool) {
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ok = true
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switch t := v.(type) {
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case int:
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value = float64(t)
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case int32:
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value = float64(t)
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case int64:
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value = float64(t)
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case uint64:
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value = float64(t)
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case float64:
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value = t
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case bool:
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if t {
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value = 1
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} else {
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value = 0
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}
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case time.Time:
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value = float64(t.Unix())
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default:
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// Skip unsupported type.
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ok = false
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return value, ok
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}
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// Do CloudWatch boundary checking
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// Constraints at: http://docs.aws.amazon.com/AmazonCloudWatch/latest/APIReference/API_MetricDatum.html
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switch {
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case math.IsNaN(value):
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return 0, false
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case math.IsInf(value, 0):
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return 0, false
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case value > 0 && value < float64(8.515920e-109):
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return 0, false
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case value > float64(1.174271e+108):
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return 0, false
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}
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return value, ok
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}
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func init() {
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outputs.Add("cloudwatch", func() telegraf.Output {
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return &CloudWatch{}
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})
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}
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