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fix: rollout weights moved to canary doc

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robq99
2020-11-18 10:09:04 +01:00
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docs/gitbook/tutorials/rollout-weights.md
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# Linkerd Rollout Weights
This guide shows you how to use weights in Flagger to have more fine-grained rollouts.
By default Flagger allows to use linear promotion metrics, with the start value, the step and maximum weight value in 0 to 100 range.
Example:
```yaml
canary:
analysis:
promotion:
maxWeight: 50
stepWeight: 20
```
This configuration performs analysis starting from 20, increasing by 20 until weight goes above 50.
We would have steps (canary weight : primary weight):
* 20 (20 : 80)
* 40 (40 : 60)
* 60 (60 : 40)
* promotion
In order to enable non-linear promotion a new parameters were introduced:
* `stepWeights` - determines the ordered array of weights, which shall be used during canary promotion.
Example:
```yaml
canary:
analysis:
promotion:
stepWeights: [1, 2, 10, 80]
```
This configuration performs analysis starting from 1, going through `stepWeights` values till 800.
We would have steps (canary weight : primary weight):
* 1 (1 : 99)
* 2 (2 : 98)
* 10 (10 : 90)
* 80 (80 : 20)
* promotion
docs/gitbook/usage/deployment-strategies.md
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@@ -116,6 +116,43 @@ Gated canary promotion stages:
* send notification with the canary analysis result
* wait for the canary deployment to be updated and start over
#### Rollout Weights
By default Flagger uses linear weight values for the promotion, with the start value, the step and the maximum weight value in 0 to 100 range.
Example:
```yaml
canary:
analysis:
promotion:
maxWeight: 50
stepWeight: 20
```
This configuration performs analysis starting from 20, increasing by 20 until weight goes above 50.
We would have steps (canary weight : primary weight):
* 20 (20 : 80)
* 40 (40 : 60)
* 60 (60 : 40)
* promotion
In order to enable non-linear promotion a new parameter was introduced:
* `stepWeights` - determines the ordered array of weights, which shall be used during canary promotion.
Example:
```yaml
canary:
analysis:
promotion:
stepWeights: [1, 2, 10, 80]
```
This configuration performs analysis starting from 1, going through `stepWeights` values till 80.
We would have steps (canary weight : primary weight):
* 1 (1 : 99)
* 2 (2 : 98)
* 10 (10 : 90)
* 80 (20 : 60)
* promotion
### A/B Testing
For frontend applications that require session affinity you should use HTTP headers or cookies match conditions