Merge pull request #185 from weaveworks/docs-gloo

Add Gloo ingress controller docs
This commit is contained in:
Stefan Prodan
2019-05-21 13:24:19 +02:00
committed by GitHub
11 changed files with 546 additions and 4 deletions
+6
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@@ -30,6 +30,12 @@ run-smi:
-slack-url=https://hooks.slack.com/services/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 \
-slack-channel="devops-alerts"
run-gloo:
go run cmd/flagger/* -kubeconfig=$$HOME/.kube/config -log-level=info -mesh-provider=gloo -namespace=gloo \
-metrics-server=https://prometheus.istio.weavedx.com \
-slack-url=https://hooks.slack.com/services/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 \
-slack-channel="devops-alerts"
build:
docker build -t weaveworks/flagger:$(TAG) . -f Dockerfile
+15
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@@ -64,6 +64,21 @@ rules:
resources:
- trafficsplits
verbs: ["*"]
- apiGroups:
- gloo.solo.io
resources:
- settings
- upstreams
- upstreamgroups
- proxies
- virtualservices
verbs: ["*"]
- apiGroups:
- gateway.solo.io
resources:
- virtualservices
- gateways
verbs: ["*"]
- nonResourceURLs:
- /version
verbs:
+36
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@@ -0,0 +1,36 @@
apiVersion: flagger.app/v1alpha3
kind: Canary
metadata:
name: podinfo
namespace: test
spec:
targetRef:
apiVersion: apps/v1
kind: Deployment
name: podinfo
progressDeadlineSeconds: 60
autoscalerRef:
apiVersion: autoscaling/v2beta1
kind: HorizontalPodAutoscaler
name: podinfo
service:
port: 9898
canaryAnalysis:
interval: 10s
threshold: 10
maxWeight: 50
stepWeight: 5
metrics:
- name: request-success-rate
threshold: 99
interval: 1m
- name: request-duration
threshold: 500
interval: 30s
webhooks:
- name: load-test
url: http://flagger-loadtester.test/
timeout: 5s
metadata:
type: cmd
cmd: "hey -z 1m -q 10 -c 2 http://gloo.example.com/"
+67
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@@ -0,0 +1,67 @@
apiVersion: apps/v1
kind: Deployment
metadata:
name: podinfo
namespace: test
labels:
app: podinfo
spec:
minReadySeconds: 5
revisionHistoryLimit: 5
progressDeadlineSeconds: 60
strategy:
rollingUpdate:
maxUnavailable: 0
type: RollingUpdate
selector:
matchLabels:
app: podinfo
template:
metadata:
annotations:
prometheus.io/scrape: "true"
labels:
app: podinfo
spec:
containers:
- name: podinfod
image: quay.io/stefanprodan/podinfo:1.4.0
imagePullPolicy: IfNotPresent
ports:
- containerPort: 9898
name: http
protocol: TCP
command:
- ./podinfo
- --port=9898
- --level=info
- --random-delay=false
- --random-error=false
env:
- name: PODINFO_UI_COLOR
value: blue
livenessProbe:
exec:
command:
- podcli
- check
- http
- localhost:9898/healthz
initialDelaySeconds: 5
timeoutSeconds: 5
readinessProbe:
exec:
command:
- podcli
- check
- http
- localhost:9898/readyz
initialDelaySeconds: 5
timeoutSeconds: 5
resources:
limits:
cpu: 2000m
memory: 512Mi
requests:
cpu: 100m
memory: 64Mi
+19
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@@ -0,0 +1,19 @@
apiVersion: autoscaling/v2beta1
kind: HorizontalPodAutoscaler
metadata:
name: podinfo
namespace: test
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: podinfo
minReplicas: 1
maxReplicas: 4
metrics:
- type: Resource
resource:
name: cpu
# scale up if usage is above
# 99% of the requested CPU (100m)
targetAverageUtilization: 99
+17
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@@ -0,0 +1,17 @@
apiVersion: gateway.solo.io/v1
kind: VirtualService
metadata:
name: podinfo
namespace: test
spec:
virtualHost:
domains:
- '*'
name: podinfo.default
routes:
- matcher:
prefix: /
routeAction:
upstreamGroup:
name: podinfo
namespace: gloo
+15
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@@ -60,6 +60,21 @@ rules:
resources:
- trafficsplits
verbs: ["*"]
- apiGroups:
- gloo.solo.io
resources:
- settings
- upstreams
- upstreamgroups
- proxies
- virtualservices
verbs: ["*"]
- apiGroups:
- gateway.solo.io
resources:
- virtualservices
- gateways
verbs: ["*"]
- nonResourceURLs:
- /version
verbs:
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@@ -163,7 +163,7 @@ Deploy Grafana in the _**appmesh-system**_ namespace:
```bash
helm upgrade -i flagger-grafana flagger/grafana \
--namespace=appmesh-system \
--set url=http://prometheus.appmesh-system:9090
--set url=http://flagger-prometheus.appmesh-system:9090
```
You can access Grafana using port forwarding:
@@ -0,0 +1,366 @@
# NGNIX Ingress Controller Canary Deployments
This guide shows you how to use the [Gloo](https://gloo.solo.io/) ingress controller and Flagger to automate canary deployments.
![Flagger Gloo Ingress Controller](https://raw.githubusercontent.com/weaveworks/flagger/master/docs/diagrams/flagger-gloo-overview.png)
### Prerequisites
Flagger requires a Kubernetes cluster **v1.11** or newer and Gloo ingress **0.13.29** or newer.
Install Gloo with Helm:
```bash
helm repo add gloo https://storage.googleapis.com/solo-public-helm
helm upgrade -i gloo gloo/gloo \
--namespace gloo-system
```
Install Flagger and the Prometheus add-on in the same namespace as Gloo:
```bash
helm repo add flagger https://flagger.app
helm upgrade -i flagger flagger/flagger \
--namespace gloo-system \
--set prometheus.install=true \
--set meshProvider=gloo
```
Optionally you can enable Slack notifications:
```bash
helm upgrade -i flagger flagger/flagger \
--reuse-values \
--namespace gloo-system \
--set slack.url=https://hooks.slack.com/services/YOUR/SLACK/WEBHOOK \
--set slack.channel=general \
--set slack.user=flagger
```
### Bootstrap
Flagger takes a Kubernetes deployment and optionally a horizontal pod autoscaler (HPA),
then creates a series of objects (Kubernetes deployments, ClusterIP services and Gloo upstream groups).
These objects expose the application outside the cluster and drive the canary analysis and promotion.
Create a test namespace:
```bash
kubectl create ns test
```
Create a deployment and a horizontal pod autoscaler:
```bash
kubectl apply -f ${REPO}/artifacts/gloo/deployment.yaml
kubectl apply -f ${REPO}/artifacts/gloo/hpa.yaml
```
Deploy the load testing service to generate traffic during the canary analysis:
```bash
helm upgrade -i flagger-loadtester flagger/loadtester \
--namespace=test
```
Create an virtual service definition that references an upstream group that will be generated by Flagger
(replace `app.example.com` with your own domain):
```yaml
apiVersion: gateway.solo.io/v1
kind: VirtualService
metadata:
name: podinfo
namespace: test
spec:
virtualHost:
domains:
- 'app.example.com'
name: podinfo.test
routes:
- matcher:
prefix: /
routeAction:
upstreamGroup:
name: podinfo
namespace: test
```
Save the above resource as podinfo-virtualservice.yaml and then apply it:
```bash
kubectl apply -f ./podinfo-virtualservice.yaml
```
Create a canary custom resource (replace `app.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
# HPA reference (optional)
autoscalerRef:
apiVersion: autoscaling/v2beta1
kind: HorizontalPodAutoscaler
name: podinfo
# the maximum time in seconds for the canary deployment
# to make progress before it is rollback (default 600s)
progressDeadlineSeconds: 60
service:
# container port
port: 9898
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: 5
# Gloo Prometheus checks
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
# load testing (optional)
webhooks:
- name: load-test
url: http://flagger-loadtester.test/
timeout: 5s
metadata:
type: cmd
cmd: "hey -z 1m -q 10 -c 2 http://app.example.com/"
```
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
virtualservices.gateway.solo.io/podinfo
canary.flagger.app/podinfo
# generated
deployment.apps/podinfo-primary
horizontalpodautoscaler.autoscaling/podinfo-primary
service/podinfo
service/podinfo-canary
service/podinfo-primary
upstreamgroups.gloo.solo.io/podinfo
```
When the bootstrap finishes Flagger will set the canary status to initialized:
```bash
kubectl -n test get canary podinfo
NAME STATUS WEIGHT LASTTRANSITIONTIME
podinfo Initialized 0 2019-05-17T08:09:51Z
```
### 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 test describe canary/podinfo
Status:
Canary Weight: 0
Failed Checks: 0
Phase: Succeeded
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Normal Synced 3m flagger New revision detected podinfo.test
Normal Synced 3m flagger Scaling up podinfo.test
Warning Synced 3m flagger Waiting for podinfo.test rollout to finish: 0 of 1 updated replicas are available
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 2m flagger Advance podinfo.test canary weight 20
Normal Synced 2m flagger Advance podinfo.test canary weight 25
Normal Synced 1m flagger Advance podinfo.test canary weight 30
Normal Synced 1m flagger Advance podinfo.test canary weight 35
Normal Synced 55s flagger Advance podinfo.test canary weight 40
Normal Synced 45s flagger Advance podinfo.test canary weight 45
Normal Synced 35s flagger Advance podinfo.test canary weight 50
Normal Synced 25s flagger Copying podinfo.test template spec to podinfo-primary.test
Warning Synced 15s flagger Waiting for podinfo-primary.test rollout to finish: 1 of 2 updated replicas are available
Normal Synced 5s flagger 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.
You can monitor all canaries with:
```bash
watch kubectl get canaries --all-namespaces
NAMESPACE NAME STATUS WEIGHT LASTTRANSITIONTIME
test podinfo Progressing 15 2019-05-17T14:05:07Z
prod frontend Succeeded 0 2019-05-17T16:15:07Z
prod backend Failed 0 2019-05-17T17:05:07Z
```
### Automated rollback
During the canary analysis you can generate HTTP 500 errors and high latency to test if Flagger pauses and rolls back the faulted version.
Trigger another canary deployment:
```bash
kubectl -n test set image deployment/podinfo \
podinfod=quay.io/stefanprodan/podinfo:1.4.2
```
Generate HTTP 500 errors:
```bash
watch curl http://app.example.com/status/500
```
Generate high latency:
```bash
watch curl http://app.example.com/delay/2
```
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
```
### 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.
Edit the canary analysis and add the following metric:
```yaml
canaryAnalysis:
metrics:
- name: "404s percentage"
threshold: 5
query: |
100 - sum(
rate(
http_request_duration_seconds_count{
kubernetes_namespace="test",
kubernetes_pod_name=~"podinfo-[0-9a-zA-Z]+(-[0-9a-zA-Z]+)"
status!="404"
}[1m]
)
)
/
sum(
rate(
http_request_duration_seconds_count{
kubernetes_namespace="test",
kubernetes_pod_name=~"podinfo-[0-9a-zA-Z]+(-[0-9a-zA-Z]+)"
}[1m]
)
) * 100
```
The above configuration validates the canary by checking if the HTTP 404 req/sec percentage is below 5
percent of the total traffic. If the 404s rate reaches the 5% threshold, then the canary fails.
Trigger a canary deployment by updating the container image:
```bash
kubectl -n test set image deployment/podinfo \
podinfod=quay.io/stefanprodan/podinfo:1.4.3
```
Generate 404s:
```bash
watch curl http://app.example.com/status/400
```
Watch Flagger logs:
```
kubectl -n gloo-system logs deployment/flagger -f | jq .msg
Starting canary deployment for podinfo.test
Advance podinfo.test canary weight 5
Advance podinfo.test canary weight 10
Advance podinfo.test canary weight 15
Halt podinfo.test advancement 404s percentage 6.20 > 5
Halt podinfo.test advancement 404s percentage 6.45 > 5
Halt podinfo.test advancement 404s percentage 7.60 > 5
Halt podinfo.test advancement 404s percentage 8.69 > 5
Halt podinfo.test advancement 404s percentage 9.70 > 5
Rolling back podinfo.test failed checks threshold reached 5
Canary failed! Scaling down podinfo.test
```
If you have Slack configured, Flagger will send a notification with the reason why the canary failed.
+4 -3
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@@ -152,8 +152,10 @@ func (gr *GlooRouter) writeUpstreamGroupRuleForCanary(canary *flaggerv1.Canary,
targetName := canary.Spec.TargetRef.Name
if oldUg, err := gr.ugClient.Read(ug.Metadata.Namespace, ug.Metadata.Name, solokitclients.ReadOpts{}); err != nil {
// ignore not exist errors..
if !solokiterror.IsNotExist(err) {
if solokiterror.IsNotExist(err) {
gr.logger.With("canary", fmt.Sprintf("%s.%s", canary.Name, canary.Namespace)).
Infof("UpstreamGroup %s created", ug.Metadata.Name)
} else {
return fmt.Errorf("RoutingRule %s.%s read failed: %v", targetName, canary.Namespace, err)
}
} else {
@@ -181,6 +183,5 @@ func (gr *GlooRouter) writeUpstreamGroupRuleForCanary(canary *flaggerv1.Canary,
if err != nil {
return fmt.Errorf("UpstreamGroup %s.%s update failed: %v", targetName, canary.Namespace, err)
}
gr.logger.With("canary", fmt.Sprintf("%s.%s", canary.Name, canary.Namespace)).Infof("UpstreamGroup %s updated", ug.Metadata.Name)
return nil
}