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Scale applications based on a metric obtained from Stackdriver.

Availability: 2.7+ Maintainer: Community

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Trigger Specification

This specification describes the gcp-stackdriver trigger for GCP Stackdriver. It scales based on a metric obtained from issuing a query to Stackdriver.

triggers:
- type: gcp-stackdriver
  metadata:
    projectId: my-project-id
    filter: 'metric.type="storage.googleapis.com/network/received_bytes_count" AND resource.type="gcs_bucket" AND metric.label.method="WriteObject" AND resource.label.bucket_name="my-gcp-bucket"'
    targetValue: '100.50'
    valueIfNull: '0.0' #Optional - Default is ""
    filterDuration: '1' # Optional - Default is 2
    activationTargetValue: "10.5" # Optional - Default is 0
    credentialsFromEnv: GOOGLE_APPLICATION_CREDENTIALS_JSON
    alignmentPeriodSeconds: '60'
    alignmentAligner: mean
    alignmentReducer: none

Parameter list:

  • projectId - GCP project Id that contains the metric.
  • filter - The stackdriver query filter for obtaining the metric. The metric is for the last minute and if multiple values are returned, the first one is used.
  • targetValue - Average target value to trigger scaling actions. (Default: 5, Optional, This value can be a float)
  • activationTargetValue - Target value for activating the scaler. Learn more about activation here.(Default: 0, Optional, This value can be a float)
  • valueIfNull - Value return if request return no timeseries.(Default: "", Optional, This value can be a float)
  • filterDuration - Duration (in minutes) for filtering metrics. (Default: 2)

The credentialsFromEnv property maps to the name of an environment variable in the scale target (scaleTargetRef) that contains the service account credentials (JSON). KEDA will use those to connect to Google Cloud Platform and collect the configured stack driver metrics.

The alignmentPeriodSeconds, alignmentAligner and alignmentReducer properties controls time series aggregation before the metrics are returned. See below for more details.

Timeseries alignment properties

It is much better to aggregate the time series values before they are returned from stackdriver instead of getting the raw values. For that, you must specify a value of 60 or more for the alignmentPeriodSeconds property as well as an alignment operation in the alignmentAligner property and/or a reducer in the alignmentReducer property.

Valid values for the alignmentAligner property are: none, delta, rate, interpolate, next_older, min, max, mean, count, sum, stddev, count_true, count_false, fraction_true, percentile_99, percentile_95, percentile_50, percentile_05 and percent_change. Valid values for the alignmentReducer property are: none, mean, min, max, sum, stddev, count, count_true, count_false, fraction_true, percentile_99, percentile_95, percentile_50 and percentile_05.

For more information on aggregation, see here.

Authentication Parameters

You can use TriggerAuthentication CRD to configure the authenticate by providing the service account credentials in JSON.

Credential based authentication:

  • GoogleApplicationCredentials - Service account credentials in JSON.

Identity based authentication:

You can also use TriggerAuthentication CRD to configure the authentication using the associated service account of the running machine in Google Cloud. You only need to create a TriggerAuthentication as this example, and reference it in the ScaledObject. ClusterTriggerAuthentication can also be used if you intend to use it globally in your cluster.

Examples

apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
  name: gcp-stackdriver-scaledobject
  namespace: keda-gcp-stackdriver-test
spec:
  scaleTargetRef:
    name: keda-gcp-stackdriver-go
  triggers:
  - type: gcp-stackdriver
    metadata:
      projectId: my-project-id
      filter: 'metric.type="storage.googleapis.com/network/received_bytes_count" AND resource.type="gcs_bucket" AND metric.label.method="WriteObject" AND resource.label.bucket_name="my-gcp-bucket"'
      targetValue: "5"
      credentialsFromEnv: GOOGLE_APPLICATION_CREDENTIALS_JSON

Use TriggerAuthentication with Kubernetes secret

apiVersion: keda.sh/v1alpha1
kind: TriggerAuthentication
metadata:
  name: keda-trigger-auth-gcp-credentials
spec:
  secretTargetRef:
  - parameter: GoogleApplicationCredentials
    name: gcp-stackdriver-secret        # Required. Refers to the name of the secret
    key: GOOGLE_APPLICATION_CREDENTIALS_JSON       # Required.
---
apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
  name: gcp-stackdriver-scaledobject
spec:
  scaleTargetRef:
    name: keda-gcp-stackdriver-go
  triggers:
  - type: gcp-stackdriver
    authenticationRef:
      name: keda-trigger-auth-gcp-credentials
    metadata:
      projectId: my-project-id
      filter: 'metric.type="storage.googleapis.com/network/received_bytes_count" AND resource.type="gcs_bucket" AND metric.label.method="WriteObject" AND resource.label.bucket_name="my-gcp-bucket"'

Use TriggerAuthentication with GCP Identity

apiVersion: keda.sh/v1alpha1
kind: TriggerAuthentication
metadata:
  name: keda-trigger-auth-gcp-credentials
spec:
  podIdentity:
    provider: gcp
---
apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
  name: gcp-stackdriver-scaledobject
spec:
  scaleTargetRef:
    name: keda-gcp-stackdriver-go
  triggers:
  - type: gcp-stackdriver
    authenticationRef:
      name: keda-trigger-auth-gcp-credentials
    metadata:
      projectId: my-project-id
      filter: 'metric.type="storage.googleapis.com/network/received_bytes_count" AND resource.type="gcs_bucket" AND metric.label.method="WriteObject" AND resource.label.bucket_name="my-gcp-bucket"'