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Progressive Traffic Shift

Scenario: Progressive traffic shift

Progressive traffic shift is a type of canary rollout strategy. It enables you to incrementally shift traffic towards the winning version over multiple iterations of an experiment as shown below.

Progressive traffic shift

Tutorials with progressive traffic shift

The hybrid (A/B + SLOs) testing tutorial demonstrates progressive traffic shift.

Specifying weightObjRef

Iter8 uses the weightObjRef field in the experiment resource to get the current traffic split between versions and/or modify the traffic split. Ensure that this field is specified correctly for each version. The following example demonstrates how to specify weightObjRef in experiments.

Example

The hybrid (A/B + SLOs) testing tutorial uses an Istio virtual service for traffic shifting. Hence, the experiment manifest specifies the weightObjRef field for each version by referencing this Istio virtual service and the traffic fields within the Istio virtual service corresponding to the versions.

versionInfo:
  baseline:
    name: iris-v1
    weightObjRef:
      apiVersion: networking.istio.io/v1alpha3
      kind: VirtualService
      name: routing-rule
      namespace: default
      fieldPath: .spec.http[0].route[0].weight      
  candidates:
  - name: iris-v2
    weightObjRef:
      apiVersion: networking.istio.io/v1alpha3
      kind: VirtualService
      name: routing-rule
      namespace: default
      fieldPath: .spec.http[0].route[1].weight

Traffic controls

You can specify the maximum traffic percentage that is allowed for a candidate version during the experiment. You can also specify the maximum increase in traffic percentage that is allowed for a candidate version during a single iteration of the experiment. You can specify these two controls in the strategy section of an experiment as follows.

strategy:
  weights: # additional traffic controls to be used during an experiment
    # candidate weight will not exceed 75 in any iteration
    maxCandidateWeight: 75
    # candidate weight will not increase by more than 20 in a single iteration
    maxCandidateWeightIncrement: 20
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