Add SMI tutorial

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stefanprodan
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# Flagger SMI
This guide shows you how to use the SMI Istio adapter and Flagger to automate canary deployments.
### Prerequisites
Flagger requires a Kubernetes cluster **v1.11** or newer with the following admission controllers enabled:
* MutatingAdmissionWebhook
* ValidatingAdmissionWebhook
Flagger depends on [Istio](https://istio.io/docs/setup/kubernetes/quick-start/) **v1.0.3** or newer
with traffic management, telemetry and Prometheus enabled.
A minimal Istio installation should contain the following services:
* istio-pilot
* istio-ingressgateway
* istio-sidecar-injector
* istio-telemetry
* prometheus
### Install Istio and the SMI adapter
Add Istio Helm repository:
```bash
helm repo add istio.io https://storage.googleapis.com/istio-release/releases/1.1.5/charts
```
Install Istio CRDs:
```bash
helm upgrade -i istio-init istio.io/istio-init --wait --namespace istio-system
kubectl -n istio-system wait --for=condition=complete job/istio-init-crd-11
```
Install Istio:
```bash
helm upgrade -i istio istio.io/istio --wait --namespace istio-system
```
Create a generic Istio gateway to expose services outside the mesh on HTTP:
```yaml
apiVersion: networking.istio.io/v1alpha3
kind: Gateway
metadata:
name: public-gateway
namespace: istio-system
spec:
selector:
istio: ingressgateway
servers:
- port:
number: 80
name: http
protocol: HTTP
hosts:
- "*"
```
Save the above resource as public-gateway.yaml and then apply it:
```bash
kubectl apply -f ./public-gateway.yaml
```
Find the Gateway load balancer IP and add a DNS record for it:
```bash
kubectl -n istio-system get svc/istio-ingressgateway -ojson | jq -r .status.loadBalancer.ingress[0].ip
```
Install the SMI adapter:
```bash
REPO=https://raw.githubusercontent.com/weaveworks/flagger/master
kubectl apply -f ${REPO}/artifacts/smi/istio-adapter.yaml
```
### Install Flagger and Grafana
Add Flagger Helm repository:
```bash
helm repo add flagger https://flagger.app
```
Deploy Flagger in the _**istio-system**_ namespace:
```bash
helm upgrade -i flagger flagger/flagger \
--namespace=istio-system \
--set image.tag=master-fd44f1f \
--set meshProvider=smi:istio
```
Flagger comes with a Grafana dashboard made for monitoring the canary deployments.
Deploy Grafana in the _**istio-system**_ namespace:
```bash
helm upgrade -i flagger-grafana flagger/grafana \
--namespace=istio-system \
--set url=http://prometheus.istio-system:9090
```
You can access Grafana using port forwarding:
```bash
kubectl -n istio-system port-forward svc/flagger-grafana 3000:80
```
### Workloads bootstrap
Create a test namespace with Istio sidecar injection enabled:
```bash
export REPO=https://raw.githubusercontent.com/weaveworks/flagger/master
kubectl apply -f ${REPO}/artifacts/namespaces/test.yaml
```
Create a deployment and a horizontal pod autoscaler:
```bash
kubectl apply -f ${REPO}/artifacts/canaries/deployment.yaml
kubectl apply -f ${REPO}/artifacts/canaries/hpa.yaml
```
Deploy the load testing service to generate traffic during the canary analysis:
```bash
kubectl -n test apply -f ${REPO}/artifacts/loadtester/deployment.yaml
kubectl -n test apply -f ${REPO}/artifacts/loadtester/service.yaml
```
Create a canary custom resource (replace example.com with your own domain):
```yaml
apiVersion: flagger.app/v1alpha3
kind: Canary
metadata:
name: podinfo
namespace: test
spec:
# deployment reference
targetRef:
apiVersion: apps/v1
kind: Deployment
name: podinfo
# the maximum time in seconds for the canary deployment
# to make progress before it is rollback (default 600s)
progressDeadlineSeconds: 60
# HPA reference (optional)
autoscalerRef:
apiVersion: autoscaling/v2beta1
kind: HorizontalPodAutoscaler
name: podinfo
service:
# container port
port: 9898
# Istio gateways (optional)
gateways:
- public-gateway.istio-system.svc.cluster.local
# Istio virtual service host names (optional)
hosts:
- app.example.com
canaryAnalysis:
# schedule interval (default 60s)
interval: 10s
# max number of failed metric checks before rollback
threshold: 5
# max traffic percentage routed to canary
# percentage (0-100)
maxWeight: 50
# canary increment step
# percentage (0-100)
stepWeight: 10
metrics:
- name: request-success-rate
# minimum req success rate (non 5xx responses)
# percentage (0-100)
threshold: 99
interval: 1m
- name: request-duration
# maximum req duration P99
# milliseconds
threshold: 500
interval: 30s
# generate traffic during analysis
webhooks:
- name: load-test
url: http://flagger-loadtester.test/
timeout: 5s
metadata:
cmd: "hey -z 1m -q 10 -c 2 http://podinfo.test:9898/"
```
Save the above resource as podinfo-canary.yaml and then apply it:
```bash
kubectl apply -f ./podinfo-canary.yaml
```
After a couple of seconds Flagger will create the canary objects:
```bash
# applied
deployment.apps/podinfo
horizontalpodautoscaler.autoscaling/podinfo
canary.flagger.app/podinfo
# generated
deployment.apps/podinfo-primary
horizontalpodautoscaler.autoscaling/podinfo-primary
service/podinfo
service/podinfo-canary
service/podinfo-primary
trafficsplits.split.smi-spec.io/podinfo
```
### Automated canary promotion
Flagger implements a control loop that gradually shifts traffic to the canary while measuring key performance indicators
like HTTP requests success rate, requests average duration and pod health.
Based on analysis of the KPIs a canary is promoted or aborted, and the analysis result is published to Slack.
![Flagger Canary Stages](https://raw.githubusercontent.com/weaveworks/flagger/master/docs/diagrams/flagger-canary-steps.png)
Trigger a canary deployment by updating the container image:
```bash
kubectl -n test set image deployment/podinfo \
podinfod=quay.io/stefanprodan/podinfo:1.4.1
```
Flagger detects that the deployment revision changed and starts a new rollout:
```text
kubectl -n istio-system logs deployment/flagger -f | jq .msg
New revision detected podinfo.test
Scaling up podinfo.test
Waiting for podinfo.test rollout to finish: 0 of 1 updated replicas are available
Advance podinfo.test canary weight 5
Advance podinfo.test canary weight 10
Advance podinfo.test canary weight 15
Advance podinfo.test canary weight 20
Advance podinfo.test canary weight 25
Advance podinfo.test canary weight 30
Advance podinfo.test canary weight 35
Advance podinfo.test canary weight 40
Advance podinfo.test canary weight 45
Advance podinfo.test canary weight 50
Copying podinfo.test template spec to podinfo-primary.test
Waiting for podinfo-primary.test rollout to finish: 1 of 2 updated replicas are available
Promotion completed! Scaling down podinfo.test
```
**Note** that if you apply new changes to the deployment during the canary analysis, Flagger will restart the analysis.
During the analysis the canarys progress can be monitored with Grafana. The Istio dashboard URL is
http://localhost:3000/d/flagger-istio/istio-canary?refresh=10s&orgId=1&var-namespace=test&var-primary=podinfo-primary&var-canary=podinfo
You can monitor all canaries with:
```bash
watch kubectl get canaries --all-namespaces
NAMESPACE NAME STATUS WEIGHT LASTTRANSITIONTIME
test podinfo Progressing 15 2019-05-16T14:05:07Z
prod frontend Succeeded 0 2019-05-15T16:15:07Z
prod backend Failed 0 2019-05-14T17:05:07Z
```
### Automated rollback
During the canary analysis you can generate HTTP 500 errors and high latency to test if Flagger pauses the rollout.
Create a tester pod and exec into it:
```bash
kubectl -n test run tester \
--image=quay.io/stefanprodan/podinfo:1.2.1 \
-- ./podinfo --port=9898
kubectl -n test exec -it tester-xx-xx sh
```
Generate HTTP 500 errors:
```bash
watch curl http://podinfo-canary:9898/status/500
```
Generate latency:
```bash
watch curl http://podinfo-canary:9898/delay/1
```
When the number of failed checks reaches the canary analysis threshold, the traffic is routed back to the primary,
the canary is scaled to zero and the rollout is marked as failed.
```text
kubectl -n test describe canary/podinfo
Status:
Canary Weight: 0
Failed Checks: 10
Phase: Failed
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Normal Synced 3m flagger Starting canary deployment for podinfo.test
Normal Synced 3m flagger Advance podinfo.test canary weight 5
Normal Synced 3m flagger Advance podinfo.test canary weight 10
Normal Synced 3m flagger Advance podinfo.test canary weight 15
Normal Synced 3m flagger Halt podinfo.test advancement success rate 69.17% < 99%
Normal Synced 2m flagger Halt podinfo.test advancement success rate 61.39% < 99%
Normal Synced 2m flagger Halt podinfo.test advancement success rate 55.06% < 99%
Normal Synced 2m flagger Halt podinfo.test advancement success rate 47.00% < 99%
Normal Synced 2m flagger (combined from similar events): Halt podinfo.test advancement success rate 38.08% < 99%
Warning Synced 1m flagger Rolling back podinfo.test failed checks threshold reached 10
Warning Synced 1m flagger Canary failed! Scaling down podinfo.test
```