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Docs tidy up

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Split feature comparison into two tables: service mesh and ingress.
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stefanprodan
2020-08-19 11:29:08 +03:00
parent 6494893812
commit 06dab2e137
3 changed files with 42 additions and 35 deletions
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docs/gitbook/tutorials/skipper-progressive-delivery.md
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@@ -281,33 +281,25 @@ the canary is scaled to zero and the rollout is marked as failed.
```text
kubectl -n flagger-system logs deploy/flagger -f | jq .msg
"New revision detected! Scaling up podinfo.test"
"canary deployment podinfo.test not ready: waiting for rollout to finish: 0 of 1 updated replicas are available"
"Starting canary analysis for podinfo.test"
"Pre-rollout check acceptance-test passed"
"primaryWeight: 95, canaryWeight: 5"
"Advance podinfo.test canary weight 5"
"primaryWeight: 90, canaryWeight: 10"
"Advance podinfo.test canary weight 10"
"primaryWeight: 85, canaryWeight: 15"
"Advance podinfo.test canary weight 15"
"primaryWeight: 80, canaryWeight: 20"
"Advance podinfo.test canary weight 20"
"Halt podinfo.test advancement success rate 53.42% < 99%"
"Halt podinfo.test advancement success rate 53.19% < 99%"
"Halt podinfo.test advancement success rate 48.05% < 99%"
"Rolling back podinfo.test failed checks threshold reached 3"
"primaryWeight: 100, canaryWeight: 0"
"Canary failed! Scaling down podinfo.test"
New revision detected! Scaling up podinfo.test
Canary deployment podinfo.test not ready: waiting for rollout to finish: 0 of 1 updated replicas are available
Starting canary analysis for podinfo.test
Pre-rollout check acceptance-test passed
Advance podinfo.test canary weight 5
Advance podinfo.test canary weight 10
Advance podinfo.test canary weight 15
Advance podinfo.test canary weight 20
Halt podinfo.test advancement success rate 53.42% < 99%
Halt podinfo.test advancement success rate 53.19% < 99%
Halt podinfo.test advancement success rate 48.05% < 99%
Rolling back podinfo.test failed checks threshold reached 3
Canary failed! Scaling down podinfo.test
```
## Custom metrics
The canary analysis can be extended with Prometheus queries.
The demo app is instrumented with Prometheus so you can create a custom check that will use the
HTTP request duration histogram to validate the canary.
Create a metric template and apply it on the cluster:
```yaml